from_exploration_to_linear_regression_prediction.ipynb

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    },
    "colab": {
      "name": "from-exploration-to-linear-regression-prediction.ipynb",
      "provenance": [],
      "collapsed_sections": []
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "e3666d1ff6031205edf5e06d98963397f780573d",
        "_cell_guid": "5762324b-f44e-4f06-a1c0-978a7142a29e",
        "id": "YJ9I2SuDkEtl"
      },
      "source": [
        "#Introduction to the problem - **Prediction of each trip duration.** \n",
        "\n",
        "The data was originally published by the NYC Taxi and Limousine Commission (TLC).\n",
        "\n",
        "This notebook is made with reference to [this notebook](https://www.kaggle.com/ashishc17/from-exploration-to-linear-regression-prediction)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4idJAWaTkmbs"
      },
      "source": [
        "# Here's several helpful packages to load in \n",
        "import numpy as np # linear algebra\n",
        "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
        "import matplotlib.pyplot as plt\n",
        "import math\n",
        "import seaborn as sns\n",
        "%matplotlib inline\n",
        "import datetime as dt\n",
        "plt.style.use('ggplot')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wN9Io_-ZJ0iq"
      },
      "source": [
        "Find the dataset [here](https://www.kaggle.com/c/nyc-taxi-trip-duration/data)\n",
        "For easier access to data, follow the steps:\n",
        "\n",
        "\n",
        "1.   Unzip the data folder on local computer, after downloading data from above link, you should see train csv and test csv among other files.\n",
        "2.   Make a *data* folder on your Google drive, and upload these files to that folder.\n",
        "3. If you choose to save file at any other location, mention that paths in path command below.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0ESdxpVZntCF",
        "outputId": "a46ce90d-1927-4555-cbfa-11fb4c13cf76",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I4ydDGiIpLzy"
      },
      "source": [
        "train_data_path = \"/content/drive/My Drive/data/train.csv\"\n",
        "test_data_path = \"/content/drive/My Drive/data/test.csv\""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w8kanOvkpar_"
      },
      "source": [
        "train=pd.read_csv(train_data_path,infer_datetime_format=True,parse_dates=[2,3])\n",
        "test=pd.read_csv(test_data_path,infer_datetime_format=True,parse_dates=[2,3])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "8f8012532efea5d55eff61f1eed3aec6356d1a56",
        "_cell_guid": "d64a1701-0100-4dce-853a-4802ba217f6f",
        "id": "4HO6GoOXkEtr"
      },
      "source": [
        "**1. Introduction to the dataset**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "ed6d9e6d536aabab05fff7e5b9dbc983ef6168ae",
        "_cell_guid": "e64e35bb-c361-4c20-900b-fc04845abb01",
        "id": "y_bzF31OkEtr"
      },
      "source": [
        "Revealing the basic info about the train dataset and optimizing dtypes of variables to reduce memory usage."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "06136c50619efa442f79c93c3be651ef8aa0fe40",
        "_cell_guid": "f2b61a38-9127-4245-b002-35016e896ea1",
        "id": "N8E5k7xUkEts",
        "outputId": "1f82a04a-7a12-4726-df2f-14dde53d7277",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 326
        }
      },
      "source": [
        "#Checking the 1ast 5 rows as to how data looks.\n",
        "\n",
        "print(train.shape)\n",
        "train.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(1458644, 11)\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>vendor_id</th>\n",
              "      <th>pickup_datetime</th>\n",
              "      <th>dropoff_datetime</th>\n",
              "      <th>passenger_count</th>\n",
              "      <th>pickup_longitude</th>\n",
              "      <th>pickup_latitude</th>\n",
              "      <th>dropoff_longitude</th>\n",
              "      <th>dropoff_latitude</th>\n",
              "      <th>store_and_fwd_flag</th>\n",
              "      <th>trip_duration</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id2875421</td>\n",
              "      <td>2</td>\n",
              "      <td>2016-03-14 17:24:55</td>\n",
              "      <td>2016-03-14 17:32:30</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.982155</td>\n",
              "      <td>40.767937</td>\n",
              "      <td>-73.964630</td>\n",
              "      <td>40.765602</td>\n",
              "      <td>N</td>\n",
              "      <td>455</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id2377394</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-06-12 00:43:35</td>\n",
              "      <td>2016-06-12 00:54:38</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.980415</td>\n",
              "      <td>40.738564</td>\n",
              "      <td>-73.999481</td>\n",
              "      <td>40.731152</td>\n",
              "      <td>N</td>\n",
              "      <td>663</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id3858529</td>\n",
              "      <td>2</td>\n",
              "      <td>2016-01-19 11:35:24</td>\n",
              "      <td>2016-01-19 12:10:48</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.979027</td>\n",
              "      <td>40.763939</td>\n",
              "      <td>-74.005333</td>\n",
              "      <td>40.710087</td>\n",
              "      <td>N</td>\n",
              "      <td>2124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id3504673</td>\n",
              "      <td>2</td>\n",
              "      <td>2016-04-06 19:32:31</td>\n",
              "      <td>2016-04-06 19:39:40</td>\n",
              "      <td>1</td>\n",
              "      <td>-74.010040</td>\n",
              "      <td>40.719971</td>\n",
              "      <td>-74.012268</td>\n",
              "      <td>40.706718</td>\n",
              "      <td>N</td>\n",
              "      <td>429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id2181028</td>\n",
              "      <td>2</td>\n",
              "      <td>2016-03-26 13:30:55</td>\n",
              "      <td>2016-03-26 13:38:10</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.973053</td>\n",
              "      <td>40.793209</td>\n",
              "      <td>-73.972923</td>\n",
              "      <td>40.782520</td>\n",
              "      <td>N</td>\n",
              "      <td>435</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          id  vendor_id  ... store_and_fwd_flag trip_duration\n",
              "0  id2875421          2  ...                  N           455\n",
              "1  id2377394          1  ...                  N           663\n",
              "2  id3858529          2  ...                  N          2124\n",
              "3  id3504673          2  ...                  N           429\n",
              "4  id2181028          2  ...                  N           435\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "c37bf71ed44f578ad505e930854ef20476c84d5d",
        "_cell_guid": "bfadd1f4-4a75-4246-9ae8-f2ba78cb50db",
        "id": "AacBONjekEtw",
        "outputId": "1af09ad2-bb5b-4142-b38a-8e57748b8cc6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 326
        }
      },
      "source": [
        "print(test.shape)\n",
        "test.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(625134, 9)\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>vendor_id</th>\n",
              "      <th>pickup_datetime</th>\n",
              "      <th>passenger_count</th>\n",
              "      <th>pickup_longitude</th>\n",
              "      <th>pickup_latitude</th>\n",
              "      <th>dropoff_longitude</th>\n",
              "      <th>dropoff_latitude</th>\n",
              "      <th>store_and_fwd_flag</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id3004672</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-06-30 23:59:58</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.988129</td>\n",
              "      <td>40.732029</td>\n",
              "      <td>-73.990173</td>\n",
              "      <td>40.756680</td>\n",
              "      <td>N</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id3505355</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-06-30 23:59:53</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.964203</td>\n",
              "      <td>40.679993</td>\n",
              "      <td>-73.959808</td>\n",
              "      <td>40.655403</td>\n",
              "      <td>N</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id1217141</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-06-30 23:59:47</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.997437</td>\n",
              "      <td>40.737583</td>\n",
              "      <td>-73.986160</td>\n",
              "      <td>40.729523</td>\n",
              "      <td>N</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id2150126</td>\n",
              "      <td>2</td>\n",
              "      <td>2016-06-30 23:59:41</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.956070</td>\n",
              "      <td>40.771900</td>\n",
              "      <td>-73.986427</td>\n",
              "      <td>40.730469</td>\n",
              "      <td>N</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id1598245</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-06-30 23:59:33</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.970215</td>\n",
              "      <td>40.761475</td>\n",
              "      <td>-73.961510</td>\n",
              "      <td>40.755890</td>\n",
              "      <td>N</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          id  vendor_id  ... dropoff_latitude store_and_fwd_flag\n",
              "0  id3004672          1  ...        40.756680                  N\n",
              "1  id3505355          1  ...        40.655403                  N\n",
              "2  id1217141          1  ...        40.729523                  N\n",
              "3  id2150126          2  ...        40.730469                  N\n",
              "4  id1598245          1  ...        40.755890                  N\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0Agw6ANeqxKL",
        "outputId": "add6d96e-417a-45b0-8452-c01bdac872fa",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(train.columns)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Index(['id', 'vendor_id', 'pickup_datetime', 'dropoff_datetime',\n",
            "       'passenger_count', 'pickup_longitude', 'pickup_latitude',\n",
            "       'dropoff_longitude', 'dropoff_latitude', 'store_and_fwd_flag',\n",
            "       'trip_duration'],\n",
            "      dtype='object')\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "d8f646f582c395c5226449b0be71fe0a26f39120",
        "_cell_guid": "8561657e-e994-4cd7-be1d-ac674557ddb0",
        "id": "LjcHX47LkEt0",
        "outputId": "42bf24ef-1deb-470b-b31d-d8c1ced19c32",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "#Checking the dtypes and missing values(if any)\n",
        "print(train.info())\n",
        "\n",
        "#Optimizing dtypes for the reduction of memory\n",
        "train.passenger_count=train.passenger_count.astype(np.int8)\n",
        "train.vendor_id=train.vendor_id.astype(np.int8)\n",
        "train.trip_duration=train.trip_duration.astype(np.int32)\n",
        "for c in [c for c in train.columns if c.endswith('tude')]:\n",
        "    train.loc[:,c]=train[c].astype(np.float32)\n",
        "    \n",
        "#Checking memory usage \n",
        "print('Memory usage,Mb: {:.2f}\\n'.format(train.memory_usage().sum()/2**20)) #Nearly 50% memory has been reduced."
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 1458644 entries, 0 to 1458643\n",
            "Data columns (total 11 columns):\n",
            " #   Column              Non-Null Count    Dtype         \n",
            "---  ------              --------------    -----         \n",
            " 0   id                  1458644 non-null  object        \n",
            " 1   vendor_id           1458644 non-null  int64         \n",
            " 2   pickup_datetime     1458644 non-null  datetime64[ns]\n",
            " 3   dropoff_datetime    1458644 non-null  datetime64[ns]\n",
            " 4   passenger_count     1458644 non-null  int64         \n",
            " 5   pickup_longitude    1458644 non-null  float64       \n",
            " 6   pickup_latitude     1458644 non-null  float64       \n",
            " 7   dropoff_longitude   1458644 non-null  float64       \n",
            " 8   dropoff_latitude    1458644 non-null  float64       \n",
            " 9   store_and_fwd_flag  1458644 non-null  object        \n",
            " 10  trip_duration       1458644 non-null  int64         \n",
            "dtypes: datetime64[ns](2), float64(4), int64(3), object(2)\n",
            "memory usage: 122.4+ MB\n",
            "None\n",
            "Memory usage,Mb: 75.12\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "0e7d2dcf8edbf3e1178dc454794b1936f3c09beb",
        "_cell_guid": "3723cfe2-c9a1-4731-8d71-7e5ef48dcc3f",
        "id": "zXT1MZ5okEt5"
      },
      "source": [
        "\n",
        "\n",
        "No null entries .\n",
        "After reducing their dtypes, memory usage has reduced by 50%."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "9dc134631da7191226e629a8c35280c4cd4ff9d8",
        "_cell_guid": "caccc4ff-2788-4bd7-9db0-432af070c3e3",
        "id": "W1Ge3HtVkEt5",
        "outputId": "4f69d5ea-8f33-4fc2-93f5-07fe2c667624",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 314
        }
      },
      "source": [
        "#Checking the range and statistical distribution of the variables.\n",
        "train.describe().apply(lambda s: s.apply(lambda x: format(x, 'g')))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>vendor_id</th>\n",
              "      <th>passenger_count</th>\n",
              "      <th>pickup_longitude</th>\n",
              "      <th>pickup_latitude</th>\n",
              "      <th>dropoff_longitude</th>\n",
              "      <th>dropoff_latitude</th>\n",
              "      <th>trip_duration</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1.45864e+06</td>\n",
              "      <td>1.45864e+06</td>\n",
              "      <td>1.45864e+06</td>\n",
              "      <td>1.45864e+06</td>\n",
              "      <td>1.45864e+06</td>\n",
              "      <td>1.45864e+06</td>\n",
              "      <td>1.45864e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1.53495</td>\n",
              "      <td>1.66453</td>\n",
              "      <td>-72.7866</td>\n",
              "      <td>40.2487</td>\n",
              "      <td>-72.7863</td>\n",
              "      <td>40.2489</td>\n",
              "      <td>959.492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.498777</td>\n",
              "      <td>1.31424</td>\n",
              "      <td>1.18915</td>\n",
              "      <td>0.503276</td>\n",
              "      <td>1.18926</td>\n",
              "      <td>0.504102</td>\n",
              "      <td>5237.43</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>-121.933</td>\n",
              "      <td>34.3597</td>\n",
              "      <td>-121.933</td>\n",
              "      <td>32.1811</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.9919</td>\n",
              "      <td>40.7373</td>\n",
              "      <td>-73.9913</td>\n",
              "      <td>40.7359</td>\n",
              "      <td>397</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.9817</td>\n",
              "      <td>40.7541</td>\n",
              "      <td>-73.9798</td>\n",
              "      <td>40.7545</td>\n",
              "      <td>662</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>-73.9673</td>\n",
              "      <td>40.7684</td>\n",
              "      <td>-73.963</td>\n",
              "      <td>40.7698</td>\n",
              "      <td>1075</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2</td>\n",
              "      <td>9</td>\n",
              "      <td>-61.3355</td>\n",
              "      <td>51.8811</td>\n",
              "      <td>-61.3355</td>\n",
              "      <td>43.921</td>\n",
              "      <td>3.52628e+06</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         vendor_id passenger_count  ... dropoff_latitude trip_duration\n",
              "count  1.45864e+06     1.45864e+06  ...      1.45864e+06   1.45864e+06\n",
              "mean       1.53495         1.66453  ...          40.2489       959.492\n",
              "std       0.498777         1.31424  ...         0.504102       5237.43\n",
              "min              1               0  ...          32.1811             1\n",
              "25%              1               1  ...          40.7359           397\n",
              "50%              2               1  ...          40.7545           662\n",
              "75%              2               2  ...          40.7698          1075\n",
              "max              2               9  ...           43.921   3.52628e+06\n",
              "\n",
              "[8 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "3fbfd934660460beb4ab1f1ec53fbd1bbe94c8cc",
        "_cell_guid": "b554abf2-1254-4a8f-9dd5-0e8085b336bb",
        "id": "-uWn5jVxkEt9"
      },
      "source": [
        "Staring with the coordinates . **NYC coodinates : 40.730610, -73.935242**\n",
        "There are huge outliers in the coordinates.\n",
        "Even the trip duration range is **1sec to 3526282sec**. Needless to say, any trip cannot last for a sec or apprx 980 hrs."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "059da1ff7280c7197601675a9afe9acab190c165",
        "_cell_guid": "52801864-ce51-4ae4-b520-27fa59e5ae33",
        "id": "wmqsd8nCkEt-",
        "outputId": "a5fc5d5f-da68-4eab-db59-81120f39f26b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 294
        }
      },
      "source": [
        "test.describe().apply(lambda s: s.apply(lambda x: format(x, 'g')))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>vendor_id</th>\n",
              "      <th>pickup_longitude</th>\n",
              "      <th>pickup_latitude</th>\n",
              "      <th>dropoff_longitude</th>\n",
              "      <th>dropoff_latitude</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>625134</td>\n",
              "      <td>625134</td>\n",
              "      <td>625134</td>\n",
              "      <td>625134</td>\n",
              "      <td>625134</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1.53488</td>\n",
              "      <td>-73.9736</td>\n",
              "      <td>40.7509</td>\n",
              "      <td>-73.9735</td>\n",
              "      <td>40.7518</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.498782</td>\n",
              "      <td>0.073389</td>\n",
              "      <td>0.0298478</td>\n",
              "      <td>0.0725649</td>\n",
              "      <td>0.0358239</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1</td>\n",
              "      <td>-121.933</td>\n",
              "      <td>37.3896</td>\n",
              "      <td>-121.933</td>\n",
              "      <td>36.6013</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1</td>\n",
              "      <td>-73.9919</td>\n",
              "      <td>40.7374</td>\n",
              "      <td>-73.9913</td>\n",
              "      <td>40.736</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2</td>\n",
              "      <td>-73.9817</td>\n",
              "      <td>40.7541</td>\n",
              "      <td>-73.9798</td>\n",
              "      <td>40.7545</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2</td>\n",
              "      <td>-73.9674</td>\n",
              "      <td>40.7684</td>\n",
              "      <td>-73.963</td>\n",
              "      <td>40.7699</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2</td>\n",
              "      <td>-69.2489</td>\n",
              "      <td>42.8149</td>\n",
              "      <td>-67.4968</td>\n",
              "      <td>48.8576</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      vendor_id pickup_longitude  ... dropoff_longitude dropoff_latitude\n",
              "count    625134           625134  ...            625134           625134\n",
              "mean    1.53488         -73.9736  ...          -73.9735          40.7518\n",
              "std    0.498782         0.073389  ...         0.0725649        0.0358239\n",
              "min           1         -121.933  ...          -121.933          36.6013\n",
              "25%           1         -73.9919  ...          -73.9913           40.736\n",
              "50%           2         -73.9817  ...          -73.9798          40.7545\n",
              "75%           2         -73.9674  ...           -73.963          40.7699\n",
              "max           2         -69.2489  ...          -67.4968          48.8576\n",
              "\n",
              "[8 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "aa5d5ad12947a55eacae9940df5fad41ee4a3c9b",
        "_cell_guid": "c429d94d-85e9-4a49-9072-d8c52b6d997c",
        "id": "Z5NqlLWrkEuC"
      },
      "source": [
        "Same with the test dataset as some of the trips were outstation ones. \n",
        "We need to clean this dataset as well."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "c7528d7032f117139848d461212791b4fc38efb7",
        "_cell_guid": "b3ee6e64-f0a3-4cad-a1d5-98831c87b96a",
        "id": "Xb2Ak47QkEuC"
      },
      "source": [
        "#**2. Data Cleaning**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "ddd139b53872ff26c5d1187a8f4776ac963d058a",
        "_cell_guid": "c8826d79-9d59-4edc-b762-4fc41c6e033b",
        "id": "GCHaO3bHkEuD"
      },
      "source": [
        "First, we will corect the coordinates range to work with. \n",
        "Range of *latitude coordinates* : **40.6 to 40.9**\n",
        "Range of *longitude coordinates* : **-74.25 to -73.7**\n",
        "\n",
        "After cross checking with the google maps and finding the location of the extreme coordinates range, it is highly unlikely that any trip would last for more than 120 min or less than 5min.\n",
        "Trip duration range : **5min to 120 min**\n",
        "\n",
        "For the coordinates filtering, we will be filtering using the same coordinates range on the train and test datset.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "4887c63a2be1377ad0b9b17181d3aebb18c9730a",
        "_cell_guid": "9c9c2dfc-418e-4a57-adeb-fd91118c0fef",
        "id": "k_LSg-9nkEuE",
        "outputId": "5c35e40c-3699-4027-c84d-6b660d8f12a0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Setting Coordinates range \n",
        "lat_min=40.6\n",
        "lat_max=40.9\n",
        "long_min=-74.25\n",
        "long_max=-73.7\n",
        "\n",
        "#Defining coordinates range\n",
        "def lat_range(lati):\n",
        "    return lati>=lat_min and lati<=lat_max\n",
        "def long_range(longi):\n",
        "    return longi>=long_min and longi<=long_max\n",
        "\n",
        "#Fixing the coordinates range\n",
        "train=train[(train['pickup_latitude'].apply(lat_range)) & (train['pickup_longitude'].apply(long_range))]\n",
        "train=train[(train['dropoff_latitude'].apply(lat_range)) & (train['dropoff_longitude'].apply(long_range))]\n",
        "\n",
        "test=test[(train['pickup_latitude'].apply(lat_range)) & (test['pickup_longitude'].apply(long_range))]\n",
        "test=test[(test['dropoff_latitude'].apply(lat_range)) & (test['dropoff_longitude'].apply(long_range))]\n",
        "\n",
        "#Correcting the trip range as we are concerend with only the trips within NYC.\n",
        "train=train[(train.trip_duration>300)&(train.trip_duration<3600)]\n",
        "\n",
        "print(train.shape[0])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:17: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "1222126\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "c38c6e4cdd9b0d45a0c7a69e5eaabbf8df1f3b51",
        "_cell_guid": "5c8cf6cd-db20-482c-8c16-9a37683a9ee6",
        "id": "nkBHj6fZkEuH",
        "outputId": "4ece6051-6223-4bb7-f151-ef8c26818dbf",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "#Checking the range\n",
        "print('Latitude Range:{} to {}'.format(max(train.pickup_latitude.min(),train.dropoff_latitude.min()),max(train.pickup_latitude.max(),train.dropoff_latitude.max())))\n",
        "print('Longitude Range:{} to {}'.format(max(train.pickup_longitude.min(),train.dropoff_longitude.min()),max(train.pickup_longitude.max(),train.dropoff_longitude.max())))\n",
        "print('Trip duration in sec range:{} to {}'.format(train.trip_duration.min(),train.trip_duration.max()))\n",
        "print('Datetime range:{} to {}'.format(train.pickup_datetime.min(),train.dropoff_datetime.max()))\n",
        "print('Passenger range: {} to {}'.format(train.passenger_count.min(),train.passenger_count.max()))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Latitude Range:40.600677490234375 to 40.89995574951172\n",
            "Longitude Range:-74.22979736328125 to -73.70030212402344\n",
            "Trip duration in sec range:301 to 3599\n",
            "Datetime range:2016-01-01 00:00:17 to 2016-07-01 00:48:20\n",
            "Passenger range: 0 to 9\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "d0bd08085047dc86fd56ae8326dbd3cb1973489e",
        "_cell_guid": "5a698cf3-1b39-4bd6-92d7-a9727477610d",
        "id": "q8J4yqhWkEuL"
      },
      "source": [
        "As any trip would be counted if passenger were to be sitting in a car. Hence, we will find out the empty trips and would drop those entries without any passenger."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "bca4e841eabd69f285335019eb52c2969c69f5c1",
        "_cell_guid": "12fa6b12-f0de-41da-b743-364f79a568c9",
        "id": "yyKyKcuDkEuL",
        "outputId": "7e8c01b8-664f-4a8b-f3ac-2372c045c9ea",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "train=train[train.passenger_count>0]\n",
        "print('Passenger range: {} to {}'.format(train.passenger_count.min(),train.passenger_count.max()))\n",
        "print(train.shape[0])\n",
        "# In total 12 entries were without any passenger."
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Passenger range: 1 to 9\n",
            "1222114\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "ea6a26e3389d785986b4026c2b1b6341872e3ec9",
        "collapsed": true,
        "_cell_guid": "aaff01ca-de0f-4e51-bf17-0cf1f33fb0c9",
        "id": "APlaE5YXkEuP"
      },
      "source": [
        "#**3.Visualization Analysis**\n",
        "\n",
        "\n",
        "\n",
        "As visualization gives the meaningful insights to explore the data.\n",
        "\n",
        "We will be using **histogram** to understand the distribution of the dataset.\n",
        "\n",
        "**Barplot** to count the no of entries using different analysing methods.\n",
        "\n",
        "**Lineplot** to compare.\n",
        "\n",
        "**Heatmap** to extract insights using relative density.\n",
        "\n",
        "**Scatter plot** for mapping the coordinates on the NYC map to extract pick up and drop off locations."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "3aaee7f66068d9e0ca481aff43f7388ffc104f83",
        "_cell_guid": "69564629-b414-40be-b20e-4a4dd536e42f",
        "id": "wP9lb8J-kEuP"
      },
      "source": [
        "For the analysis at different level, we are grouping the pickup and datetime at hourly, daily and monthly basis."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "0f2a53bfabd3c784f6efabf79128cff1c31a3108",
        "_cell_guid": "43723082-46c7-4b02-8f41-320a0782340a",
        "id": "mZHiyIVCkEuQ",
        "outputId": "e24f74d0-e77d-4349-e319-c17829d19092",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "#Naming week of a day and month of a year\n",
        "dow_names=['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']\n",
        "mm_names=['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December']\n",
        "\n",
        "#Grouping month wise\n",
        "train['mm_pickup']=train.pickup_datetime.dt.month.astype(np.int8)\n",
        "train['mm_dropoff']=train.dropoff_datetime.dt.month.astype(np.int8)\n",
        "\n",
        "test['mm_pickup']=test.pickup_datetime.dt.month.astype(np.int8)\n",
        "\n",
        "#Grouping day wise\n",
        "train['dow_pickup']=train.pickup_datetime.dt.weekday.astype(np.int8)\n",
        "train['dow_dropoff']=train.dropoff_datetime.dt.weekday.astype(np.int8)\n",
        "\n",
        "test['dow_pickup']=test.pickup_datetime.dt.weekday.astype(np.int8)\n",
        "\n",
        "#Grouping day of year wise\n",
        "train['yday']=train.pickup_datetime.dt.dayofyear.astype(np.int8)\n",
        "test['yday']=test.pickup_datetime.dt.dayofyear.astype(np.int8)\n",
        "\n",
        "#Grouping hour wise\n",
        "train['hh_pickup']=train.pickup_datetime.dt.hour.astype(np.int8)\n",
        "train['hh_dropoff']=train.dropoff_datetime.dt.hour.astype(np.int8)\n",
        "\n",
        "test['hh_pickup']=test.pickup_datetime.dt.hour.astype(np.int8)\n",
        "\n",
        "#Plotting pickup wise\n",
        "#Monthly\n",
        "plt.figure(figsize=(12,2))\n",
        "month_wise=train.groupby('mm_pickup').agg({'id':'count'}).reset_index()\n",
        "sns.barplot(x='mm_pickup',y='id',data=month_wise)\n",
        "plt.xlabel('Month wise pick up')\n",
        "plt.ylabel('no of counts')\n",
        "plt.xticks(range(0,7),mm_names[:6])\n",
        "plt.title('Monthly pick up')\n",
        "pass\n",
        "\n",
        "#Day of a week\n",
        "plt.figure(figsize=(12,2))\n",
        "day_wise=train.groupby('dow_pickup').agg({'id':'count'}).reset_index()\n",
        "sns.barplot(x='dow_pickup',y='id',data=day_wise)\n",
        "plt.xlabel('day wise pick up')\n",
        "plt.ylabel('no of counts')\n",
        "plt.xticks(range(0,7),dow_names)\n",
        "plt.title('Daily pickup')\n",
        "pass\n",
        "\n",
        "#Hourly\n",
        "plt.figure(figsize=(12,2))\n",
        "hour_wise=train.groupby('hh_pickup').agg({'id':'count'}).reset_index()\n",
        "sns.barplot(x='hh_pickup',y='id',data=hour_wise)\n",
        "plt.xlabel('hourly wise pick up 0-23')\n",
        "plt.ylabel('no of counts')\n",
        "plt.title('Hourly pick up')\n",
        "pass\n",
        "\n",
        "\n",
        "#Hourly dropoff\n",
        "plt.figure(figsize=(12,2))\n",
        "hhdrop_wise=train.groupby('hh_dropoff').agg({'id':'count'}).reset_index()\n",
        "sns.barplot(x='hh_dropoff',y='id',data=hhdrop_wise)\n",
        "plt.xlabel('hourly wise dropoff 0-23')\n",
        "plt.ylabel('no of counts')\n",
        "plt.title('Hourly dropoff')\n",
        "pass\n",
        "\n",
        "#Daily dropoff\n",
        "plt.figure(figsize=(12,10))\n",
        "yday_wise=train.groupby('yday').agg({'id':'count'}).reset_index()\n",
        "yday_wise.plot(kind='line')\n",
        "plt.xlabel('Daily pickups')\n",
        "plt.ylabel('no of counts')\n",
        "plt.title('Pickups on daily basis')\n",
        "pass"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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wiYiIiIjDs2sJxsLCQu69997rStAB+vbtyyuvvFKhfODAgcTGxhIbG2tL0LOzs9m6dSvvvfcer776KkuXLsVisWCxWFi6dCmvvPIKcXFxpKenk52dDcAnn3zCwIEDWbBgAY0bN7atRLNx40YaN27MggULGDhwICtWrLiu+EVERERE6pJdSXr//v3ZtGnTdTfSsWNHjEajXXV37txJ7969cXV1JSAggObNm3P48GEOHz5M8+bNadasGS4uLvTu3ZudO3ditVrZt28fPXv2BC5/Idi5cycAu3btom/fvgD07NmTf/3rX1it1ut+HyIiIiIidcGu6S6HDh3iH//4B3/7299o2rRpuX2vv/76dTe+YcMG0tLSaNOmDSNHjsRoNGI2m2nXrp2tjslkwmw2A+Dr62sr9/X15dChQ5w/fx5PT0+cnZ0r1DebzbZjnJ2d8fT05Pz587YpNiIiIiIijsiuJL1///7079+/Rhu+7777iI6OBi7ffLp8+XImTpxYo238FikpKaSkpAAQExODn5/fNY85VdtBNSD2fN5SP2q+b3Tl1BRdN46rpvvGXKNna9h03Tgu9U15diXpV6aM1KSrR+QHDBjA3Llzgcsj4WfOnLHtM5vNmEwmgHLlZ86cwWQy4eXlRVFREWVlZTg7O5erf+Vcvr6+lJWVUVRUVOVTUqOiooiKirJt5+Xl1dyblWvS5+241DeOS33juGq6b+yamyp20XXjuBpq3wQGBlZableSfuVGzMpc7wh7fn4+Pj4+AOzYsYOWLVsCEB4eTnx8PA899BD5+fmcOnWK4OBgrFYrp06dIjc3F5PJxNatW5k8eTIGg4FOnTqxfft27r77blJTUwkPDwege/fupKamEhISwvbt2+nUqRMGg+G64hURERERqSt2Jenffvttue2zZ8+Sk5PD7bffbleSPn/+fPbv38/58+eZMGECw4YNY9++fRw/fhyDwYC/vz/jx48HoGXLlvTq1Yvnn38eJycnxo4di5PT5TGEMWPG8Pbbb2OxWOjXr58tsX/iiSeYP38+q1at4rbbbrPF1L9/fxYuXMizzz6L0Wjkueees/+TERERERGpJ3Yl6TNnzqxQtnHjRn755Re7GqksOa4uuR8yZAhDhgypUH7HHXfYlmq8WrNmzZgzZ06Fcjc3N55//nm7YhQRERERcRTXPc2tb9++1U6DERERERGR62PXSLrFYim3XVJSQlpaGo0bN66VoEREREREGjK7kvThw4dXKDOZTDz99NM1HpCIiIiISENnV5K+cOHCctvu7u56IJCIiIiISC2xa066v78//v7+GAwG8vPzKSkpqe24REREREQaLLtG0vPz85k/fz5ZWVl4eXlx/vx5QkJC+POf/2x7cJCIiIiIiNQMu0bSExMTad26NcnJySxevJjk5GSCgoJITEys7fhERERERBocu5L0H3/8kZEjR+Lh4QGAh4cHTz75JFlZWbUanIiIiIhIQ2RXkt64cWOys7PLlZ08eRJPT89aCUpEREREpCGza076oEGDePPNN+nfvz/+/v6cPn2a1NRUHn300dqOT0RERESkwbErSY+KiqJ58+Zs2bKFEydO4OPjw+TJk+nSpUttxyciIiIi0uDYlaQDdO7cmc6dO9dmLCIiIiIigp1z0t99910OHDhQruzAgQPMmzevVoISEREREWnI7ErS9+/fT/v27cuVhYSEsG/fvloJSkRERESkIbMrSXd1daW4uLhcWXFxMc7OzrUSlIiIiIhIQ2ZXkt6tWzcWL15MUVERAEVFRSxdupTQ0NBaDU5EREREpCGy68bRkSNHsmDBAsaMGYPRaKSwsJDQ0FCeffZZuxpZtGgRu3fvxtvb2zaPvbCwkLi4OE6fPo2/vz9TpkzBaDRitVpJTk4mIyMDd3d3Jk6cSJs2bQBITU1l7dq1AAwZMoS+ffsCcPToURISEigpKSEsLIzRo0djMBiqbENERERExJHZlaQbjUamT5/O2bNnycvLw8/Pj6ZNm9rdSN++fbn//vtJSEiwla1bt44uXbowePBg1q1bx7p163jyySfJyMggJyeH+Ph4Dh06xJIlS5g9ezaFhYWsWbOGmJgYAF5++WXCw8MxGo0kJiby9NNP065dO+bMmUNmZiZhYWFVtiEiIiIi4sjsmu5yRdOmTQkODv5NCTpAx44dK4xg79y5k8jISAAiIyPZuXMnALt27SIiIgKDwUBISAgXLlwgPz+fzMxMunbtitFoxGg00rVrVzIzM8nPz+fixYuEhIRgMBiIiIiwnauqNkREREREHJnd66TXtIKCAnx8fIDLyX9BQQEAZrMZPz8/Wz1fX1/MZjNmsxlfX19buclkqrT8Sv3q2qhMSkoKKSkpAMTExJSLoSqn7H2zck32fN5SP2q+b3Tl1BRdN46rpvvGXKNna9h03Tgu9U159ZakX81gMGAwGOq1jaioKKKiomzbeXl5tRqPlKfP23GpbxyX+sZx1XTf/KafvaVaum4cV0Ptm8DAwErLq7zuv/rqK9vrnJycGg/I29ub/Px8APLz82nSpAlweYT86k46c+YMJpMJk8nEmTNnbOVms7nS8iv1q2tDRERERMSRVZmkr1y50vb6pZdeqvGGw8PD2bx5MwCbN2+mR48etvK0tDSsVitZWVl4enri4+NDaGgoe/bsobCwkMLCQvbs2UNoaCg+Pj40atSIrKwsrFYraWlphIeHV9uGiIiIiIgjq3K6S7NmzVi+fDktWrSgtLSUjRs3Vlqvf//+12xk/vz57N+/n/PnzzNhwgSGDRvG4MGDiYuLY+PGjbblEQHCwsLYvXs3kydPxs3NjYkTJwKXV5gZOnQo06dPByA6Otp2M+q4ceNYtGgRJSUlhIaGEhYWBlBlGyIiIiIijqzKJP25555j/fr1pKenU1ZWxrfffltpPXuS9Oeee67S8hkzZlQoMxgMjBs3rsq2Kmuvbdu2tvXXr+bl5VVpGyIiIiIijqzKJD0wMJAJEyYA8MYbbyjZFRERERGpI3at7jJjxgzKysr48ccfbUsehoSE4OzsXNvxiYiIiIg0OHYl6SdPniQmJoaSkhJ8fX05c+YMrq6uvPTSS7Ro0aK2YxQRERERaVDsStITExOJiori4Ycftq01vn79epYuXcrMmTNrNUARERERkYbGrucjHD9+nIceeqjcw4AGDhzI8ePHaysuEREREZEGy64k3WQysX///nJlBw4cwMfHp1aCEhERERFpyOya7jJ8+HDmzp1L9+7d8fPzIy8vj927d/Pss8/WdnwiIiIiIg2OXUl6eHg4c+fOZdu2beTn59OyZUuGDRtGYGBgbccnIiIiItLg2JWkw+V104cOHVqbsYiIiIiICHbOSRcRERERkbqjJF1ERERExMEoSRcRERERcTB2z0kHyMvLw2w2YzKZ8PPzq62YREREREQaNLuS9Pz8fObPn09WVhZeXl6cP3+ekJAQ/vznP2MymWo7RhERERGRBsWu6S6JiYm0bt2a5ORkFi9eTHJyMkFBQSQmJtZ2fCIiIiIiDY5dI+k//vgjzz//PC4ul6t7eHjw5JNPMmHChBsOYNKkSXh4eODk5ISzszMxMTEUFhYSFxfH6dOn8ff3Z8qUKRiNRqxWK8nJyWRkZODu7s7EiRNp06YNAKmpqaxduxaAIUOG0LdvXwCOHj1KQkICJSUlhIWFMXr0aAwGww3HLSIiIiJSW+waSW/cuDHZ2dnlyk6ePImnp2eNBDFz5kxiY2OJiYkBYN26dXTp0oX4+Hi6dOnCunXrAMjIyCAnJ4f4+HjGjx/PkiVLACgsLGTNmjXMnj2b2bNns2bNGgoLC4HLvwI8/fTTxMfHk5OTQ2ZmZo3ELCIiIiJSW+xK0gcNGsSbb77JihUr+Oc//8mKFSt46623eOSRR2olqJ07dxIZGQlAZGQkO3fuBGDXrl1ERERgMBgICQnhwoUL5Ofnk5mZSdeuXTEajRiNRrp27UpmZib5+flcvHiRkJAQDAYDERERtnOJiIiIiDgqu6a7REVF0bx5c7Zs2cKJEyfw8fFh8uTJdOnSpUaCePvttwG49957iYqKoqCgAB8fHwCaNm1KQUEBAGazudyqMr6+vpjNZsxmM76+vrZyk8lUafmV+iIiIiIijszuJRg7d+5M586dazyAN998E5PJREFBAW+99RaBgYHl9hsMhjqZQ56SkkJKSgoAMTExdi0xeaq2g2pAtKSn46r5vtGVU1N03Tiumu4bDS/VHF03jkt9U55dSXppaSmpqakcP36c4uLicvueeeaZGwrgyhKO3t7e9OjRg8OHD+Pt7U1+fj4+Pj7k5+fTpEkTW928vDzbsWfOnMFkMmEymdi/f7+t3Gw207FjR0wmE2fOnKlQvzJRUVFERUXZtq9uR2qfPm/Hpb5xXOobx1XTfaMnD9YcXTeOq6H2zX8OUF9h13W/cOFCvvzySzw8PGjWrFm5fzeiuLiYixcv2l7v3buXVq1aER4ezubNmwHYvHkzPXr0ACA8PJy0tDSsVitZWVl4enri4+NDaGgoe/bsobCwkMLCQvbs2UNoaCg+Pj40atSIrKwsrFYraWlphIeH31DMIiIiIiK1za6R9D179rBw4UIaN25co40XFBTw7rvvAlBWVkafPn0IDQ2lbdu2xMXFsXHjRtsSjABhYWHs3r2byZMn4+bmxsSJEwEwGo0MHTqU6dOnAxAdHY3RaARg3LhxLFq0iJKSEkJDQwkLC6vR9yAiIiIiUtPsStL9/Py4dOlSjTferFkzYmNjK5R7eXkxY8aMCuUGg4Fx48ZVeq7+/fvTv3//CuVt27Zl3rx5Nx6siIiIiEgdsStJj4iIIDY2lgceeICmTZuW21cbN5OKiIiIiDRkdiXpX331FQArV64sV24wGFi4cGHNRyUiIiIi0oDZlaQnJCTUdhwiIiIiIvJ/tKqTiIiIiIiDUZIuIiIiIuJglKSLiIiIiDgYJekiIiIiIg5GSbqIiIiIiINRki4iIiIi4mCUpIuIiIiIOBgl6SIiIiIiDkZJuoiIiIiIg1GSLiIiIiLiYJSki4iIiIg4GCXpIiIiIiIOxqW+A6gLmZmZJCcnY7FYGDBgAIMHD67vkEREREREqnTTj6RbLBaWLl3KK6+8QlxcHOnp6WRnZ9d3WCIiIiIiVbrpk/TDhw/TvHlzmjVrhouLC71792bnzp31HZaIiIiISJVu+iTdbDbj6+tr2/b19cVsNtdjRCIiIiIi1TNYrVZrfQdRm7Zv305mZiYTJkwAIC0tjUOHDjF27Nhy9VJSUkhJSQEgJiamzuMUEREREbniph9JN5lMnDlzxrZ95swZTCZThXpRUVHExMTcdAn6yy+/XN8hSBXUN45LfePY1D+OS33juNQ3jquqvrnpk/S2bdty6tQpcnNzKS0tZevWrYSHh9d3WCIiIiIiVbrpl2B0dnZmzJgxvP3221gsFvr160fLli3rOywRERERkSrd9Ek6wB133MEdd9xR32HUi6ioqPoOQaqgvnFc6hvHpv5xXOobx6W+cVxV9c1Nf+OoiIiIiMjvzU0/J11ERERE5PdGSboDGzFiRH2HIP/n0Ucf5cUXX7T9y83NrbLurFmzOHLkSB1GJ1UZNmwY8fHxtu2ysjLGjh1bY6s46RqtWTt27GDYsGH88ssvv/nYDz74wPY06UmTJnHu3LmaDq9Bq+1rSa6f/g7dvBrEnHSxX1lZGc7OzvUdhsNxc3MjNja2xs5XE5+zxWLByUnfs6vj7u7Ozz//TElJCW5ubuzdu7fSJViro2ui7qSnp3P77beTnp7OsGHD7D7OYrHYnoUhtaMmriUR+W2UpDu44uJi3nnnHS5cuEBpaSmPPfYYPXr0IDc3lzlz5tC+fXuysrIwmUxMmzYNNzc3Zs2axYgRI2jbti3nzp1j+vTpJCQkkJuby8KFC/n3v/8NwJgxY2jfvj379u3js88+o3Hjxpw8eZLevXtjNBoZOHAgACtXrsTb25sHH3ywPj8Kh3P06FE++ugjiouLadKkCRMnTsTHxwe4/NCsDz74AIvFwp/+9CeCg4NZvXo1v/76K7m5ufj6+hIaGsqRI0dsD9aKiYnh4YcfplOnTiQmJnLkyBFKSsUYoHMAAA+CSURBVEro2bOnLWGZNGkSvXr14ocffuCuu+7iu+++Y+7cuQCcOnWK+fPn27blsrCwMHbv3k3Pnj1JT0/n7rvv5uDBgwAcPnyY5ORkLl26hJubGxMnTiQwMJDU1FS+++47iouLsVgsTJ8+naSkJI4cOYLBYCA6OpqePXsCl6+P3bt34+bmxosvvkjTpk3r8+3+bhUXF3Pw4EFmzpzJ3LlzGTZsGPv27WP16tV4eHiQk5NDp06dGDduHE5OTowYMYJ7772XH374gbFjx7Jq1Srb3z2pHddzLc2cOZPRo0cTFBQEwGuvvcbYsWNt21Iz9u3bx+eff25bb3vp0qW0bduWvn37MmnSJCIjI/n+++8pLS3l+eef59Zbb6W4uJikpCR+/vlnysrK+OMf/0iPHj3q+Z3I1TQM5+BcXV154YUXmDt3LjNnzmT58uVcudf31KlT3H///bz33nt4enqyffv2as/l7e3N//t//4+5c+fy3HPPkZycbNt37NgxRo8ezV/+8hf69etHWloacHmEauvWrdxzzz219yZ/B0pKSmxTXWJjYyktLSUpKYmpU6cyd+5c+vXrx8qVK231//3vfxMbG8vYsWN5//33beXZ2dm89tprPPfcc9W2N3z4cGJiYnj33XfZv38/P/30k22fl5cXc+fOZciQIXh6enL8+HEANm3aRN++fWv0fd8M7r77btLT0ykpKeGnn36iXbt2tn2BgYG88cYbvPPOOwwbNoxPP/3Utu/YsWNMnTqV119/nTVr1uDp6cm8efN499136dy5M3C5n9u1a0dsbCwdOnTgm2++qfP3d7PYuXMnoaGhBAYG4uXlxdGjR4HLyd+YMWOIi4vj119/ZceOHcDlzz44OJjY2Fhuv/32+gy9wbiea6lfv36kpqYCcPLkSS5duqQEvR5c+X/jvvvu4/PPPwdg7dq1dO7cmTlz5jBz5kw++eQTiouL6zlSuZpG0h2c1Wpl5cqVHDhwAIPBgNlspqCgAICAgADbH7s2bdpw+vTpas9VVlbG0qVLOX78OE5OTpw6dcq2Lzg4mICAANt5jUYjx44do6CggKCgILy8vGrnDf5O/Od0lxMnTvDzzz/z5ptvApe/zFwZRQfo06cPAB07dqSoqIgLFy4AEB4ejpub2zXb27p1K9988w1lZWXk5+eTnZ1N69atAejdu7etXv/+/dm0aRNPPfUU27ZtY/bs2Tf+Zm8yrVu35vTp06SnpxMWFlZuX1FREQkJCeTk5ACXr5ErunbtitFoBOCHH34o98XqSrmLiwvdu3cHLl+De/furdX3cjNLT0+3/VrXu3dvtmzZQvfu3QkODqZZs2YAtpHbnj174uTkZPs1Q+rG9VxLvXr14n/+53948sknNZBQj+666y7g8t+pK1909+7dy/fff29L2ktKSsjLy6NFixb1FqeUpyTdwW3ZsoVz584RExODi4sLkyZNoqSkBLg8yn6Fk5OTrdzZ2dk22n7p0iVbnS+++AJvb29iY2OxWq088cQTtn3u7u7l2h0wYACpqamcPXuWfv361dr7+z1r0aIFb7/9tl11DQYDUP5zdnJy4uoVUK/0VW5uLp9//jlz5szBaDSSkJBQrh+vPsddd93FmjVr6Ny5M7fddluD/zJVlfDwcD7++GNmzZrF+fPnbeWfffYZnTp1st0M/Prrr9v2/ec1URlnZ2db3zo5OZVL8sV+hYWF/Otf/+LEiRMYDAYsFgtAtc+3cHV11T0Z9eC3Xkvu7u507dqVXbt2sW3bNt1oWkuu/n8fyv/fD5cHFKD83ymr1crUqVMJDAysu0DlN9FfOAdXVFSEt7c3Li4u/Otf/7rmaDmAv7+/7afiq6fAFBUV4ePjg5OTE2lpabb/CCtz5513kpmZyZEjRwgNDb3xN3KTCQwM5Ny5c2RlZQFQWlrKzz//bNu/detWAA4ePIinpyeenp4VzhEQEMDx48exWCzk5eVx+PBh4HI/eXh44OnpydmzZ8nMzKwyDjc3N7p168aSJUv0Zaoa/fr1Izo6mlatWpUrLyoqst38duUn+cp07dqVDRs22LYLCwtrJc6Gavv27URERLBo0SISEhJ4//33CQgI4ODBgxw+fJjc3FwsFgvbtm3T1JZ6dj3X0oABA0hOTqZt27a2X6GkZvn5+ZGdnc2lS5e4cOECP/zwwzWP6datG//4xz9syf2xY8dqO0z5jTSS7qDKyspwdXWlT58+zJ07l6lTp9K2bVtuvfXWax778MMPExcXR0pKSrmRqP/6r/9i3rx5pKWl0a1bt2pHCl1cXOjUqRONGzfWaFUlXFxcmDp1KsnJyRQVFVFWVsaDDz5Iy5YtgcvJ87Rp0ygrK+NPf/pTpedo3749AQEBtpt4brvtNgCCgoIICgpiypQp+Pr60r59+2pj6dOnDzt27KBbt241+yZvIr6+vpXe+PzII4+QkJDA2rVrqx21HTp0KEuWLGHq1Kk4OTkRHR1t+/lYblx6ejqPPPJIubK77rqLr7/+muDgYJYuXWq7cfTOO++spygFru9aatOmDY0aNdJAQi24kiv4+fnRq1cvpk6dSkBAgO3/k+pER0ezbNkyXnjhBaxWKwEBAbYbT8Ux6ImjDur48eN8+OGHzJkzp17at1gsvPTSSzz//PPccsst9RKD2Gf9+vUUFRXx2GOP1XcoIjXqP1eskN8ns9nM66+/TlxcnAZ9alh95wpSuzSS7oD++c9/8o9//INRo0bVS/vZ2dnExMRw5513KkF3cLGxsfz666/MmDGjvkMREalg8+bNrFq1ipEjRypBr2H1nStI7dNIuoiIiIiIg9HXWhERERERB6MkXURERETEwShJFxERERFxMErSRURuYsOGDbM9BbKmLF68mDVr1tToOa9lxIgR/Prrr9XWyc3NZdiwYXqolIjcFJSki4jUgUmTJjF8+HDOnTtXrnzatGkMGzaM3NzcG25j1qxZfPPNNzd8nmsZP3480dHRtd7O1T7++GOaNWtWp22KiNQnJekiInUkICCA9PR02/aJEyf497//XY8RiYiIo9I66SIidSQiIoK0tDQeeOAB4PLj0yMjI1m1apWtTlFREUlJSWRkZODu7s6AAQP4wx/+gJOTE6mpqXzzzTe0a9eOTZs24enpybhx4wgLC2PlypUcOHCAQ4cOsWzZMvr27cvYsWMB2Lt3L7Nnz+bcuXP06dOHsWPHYjAYysVWUlLC6NGjef/992nSpAlr165l9erVJCUl4enpyapVqyguLmbUqFEkJCTg6+vLY489xrlz51i0aBEHDx7EYDDQsmVLZs2ahZOTE2azmaSkJA4cOICHhwcDBw6s9GmVAAkJCbi6uvLrr79y6NAhbrvtNp555hn8/f2By9N24uPjad68OSUlJaxatYrt27dz4cIFWrVqxWuvvVbhnNu3b+fjjz/mpZdeqvAY+yuf5Ztvvmkru7qNa8UjIlLbNJIuIlJH2rVrR1FREdnZ2VgsFrZu3co999xTrk5SUhJFRUUsXLiQWbNmkZaWRmpqqm3/4cOHCQwMZOnSpTzyyCN88MEHWK1Whg8fTocOHRgzZgwff/yxLUEH2L17N3PmzOHdd99l27Zt7Nmzp0Jsbm5uBAcHs3//fgD279+Pv78/P/74IwAHDhygY8eOFY774osvMJlMLFmyhMTERIYPH47BYMBisTB37lyCgoL48MMPmTFjBn//+9/JzMys8vPZsmULQ4cOZenSpQQFBREfH19pveXLl3P06FHeeustkpOTefLJJyt86di0aRMrVqzgtddeq5Cg28veeEREaoOSdBGROnRlNH3v3r3ceuutmEwm2z6LxUJ6ejqPP/44jRo1IiAggIceeoi0tDRbHT8/P6KionByciIyMpL8/HwKCgqqbXPw4ME0btwYPz8/OnXqxPHjxyut16FDB/bv309ZWRk//fQTDzzwAPv376ekpITDhw/ToUOHCsc4Oztz9uxZ8vLycHFxoUOHDhgMBo4cOcK5c+eIjo7GxcWFZs2aMWDAALZu3VplnHfccQcdO3bE1dWV4cOHk5WVRV5eXrk6FouFTZs2MWrUKEwmE05OTrRv3x5XV1dbnS+//JL169cza9YsmjdvXu1nUx174hERqS2a7iIiUociIiKYOXMmubm5REZGltt37tw5ysrK8PPzs5X5+/tjNptt202bNrW9dnd3B6C4uLjaNv/zmKrqd+zYkeXLl3Ps2DFatWpF165def/99zl06BDNmzfHy8urwjGDBg3ir3/9K2+99RYAUVFRDB48mNOnT5Ofn1/ukeUWi6XSRP8KX19f22sPDw+MRiP5+fnlPo/z589z6dKlapPvzz//nKFDh5Y73/WwJx4RkdqiJF1EpA75+/sTEBBARkYGEyZMKLevSZMmODs7k5eXR4sWLQDIy8srN9penf+c8vFbtW/fnpMnT7Jjxw46duxIixYtyMvLIyMjo9KpLgCNGjVi5MiRjBw5khMnTvDGG2/Qtm1b/Pz8CAgI+E1TRM6cOWN7XVxcTGFhIT4+PuXqeHl54erqSk5ODkFBQZWe59VXX2X27Nk0bdqUnj17VlrH3d2dkpIS2/bZs2evKx4Rkdqi6S4iInVswoQJzJgxAw8Pj3LlTk5O9OrVi5UrV3Lx4kVOnz7NF198UWHeelW8vb2vuZZ4ddzd3WnTpg0bNmywJeXt27fn66+/rjJJ//7778nJycFqteLp6YmTkxMGg4Hg4GAaNWrEunXrKCkpwWKxcOLECQ4fPlxl+xkZGRw8eJDS0lJWrVpFSEhIhVFrJycn+vXrx/LlyzGbzVgsFrKysrh06ZKtTsuWLXnllVdYunQpu3btqrSt1q1b8/PPP3P8+HFKSkpYvXr1dcUjIlJbNJIuIlLHqpuqMWbMGJKSknjmmWdwc3NjwIAB9OvXz67zPvjggyQkJPD1119zzz33MGbMmN8cW8eOHTl27BjBwcG27e3bt1c5TeXUqVMkJSVx7tw5GjduzH333Ufnzp0BeOmll1i+fDmTJk2itLSUwMBAHn300Srbvvvuu/nrX/9KVlYWbdq04dlnn6203siRI/n000+ZPn06xcXFBAUF8eqrr5arExQUxMsvv0xMTAzOzs6EhYWV2x8YGEh0dDRvvvkmbm5uDB8+nJSUlOuKR0SkNhisVqu1voMQEZGG7eplHR2Bo8UjIg2PpruIiIiIiDgYJekiIiIiIg5G011ERERERByMRtJFRERERByMknQREREREQejJF1ERERExMEoSRcRERERcTBK0kVEREREHIySdBERERERB/P/AVF9jsMEmGqZAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x144 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x144 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x144 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x144 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x720 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "3c0b876b932cbd2777b1bf08092f17067e307562",
        "_cell_guid": "d592ec92-391a-4744-abac-aec158bd2fb7",
        "id": "9CNCD2C9kEuW"
      },
      "source": [
        "In the starting 2 months, trips were slightly on a lower side(may be due to extreme cold weather). \n",
        "\n",
        "\n",
        "It also can be seen from the 1st graph that trips started decreasing after the month of March.\n",
        "\n",
        "\n",
        "Maximum daily pickups usually noticed on Thursday, Friday and Saturday.\n",
        "\n",
        "\n",
        "In the early morning time, as usual less traffic.\n",
        "Max rush was at 6 to 7pm followed by 8 to 10pm.\n",
        "\n",
        "\n",
        "From the last graph(line), there was a sudden dip in trips in the middle of March. \n",
        "\n",
        "We will be using weather data to check for the further insights on a sudden dip in trips."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "12a6241e2d30226748736269b715896fcfd2ac30",
        "_cell_guid": "a12ee12e-7f1b-403a-a561-d83a7ab492d1",
        "id": "D_4GoJJfkEuX",
        "outputId": "04a45c19-1308-492c-a7d8-4ee470dc6e74",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        }
      },
      "source": [
        "#Checking the pickups on a daily basis comparing train and test dataset\n",
        "fig, ax= plt.subplots(nrows=2,ncols=1,figsize=(12,7))\n",
        "plt.subplot(211)\n",
        "trips_train=train.groupby('mm_pickup').agg({'id':'count'})\n",
        "plt.plot(trips_train)\n",
        "plt.title('Monthly pick ups of a train dataset')\n",
        "plt.xlabel('Month of a year')\n",
        "plt.ylabel('No of trips')\n",
        "pass\n",
        "\n",
        "plt.subplot(212)\n",
        "trips_test=test.groupby('mm_pickup').agg({'id':'count'})\n",
        "plt.plot(trips_test)\n",
        "plt.title('Monthly pick ups of a test dataset')\n",
        "plt.xlabel('Month of a year')\n",
        "plt.ylabel('No of trips')\n",
        "pass\n",
        "\n",
        "fig.tight_layout()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "1bfd8ca653c6724c60490214e8f182b2093c1ef2",
        "_cell_guid": "ab35c251-f228-437e-a0e1-b1e80d1c4743",
        "id": "RQ99-kW8kEua"
      },
      "source": [
        "Same type of trip distribution in train and test dataset except in the 4th month where a lil bit dip is seen in the month of April"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "38e316c85bacb01d60489fbce8efc3de65cfa817",
        "_cell_guid": "f0f7d10e-fe74-4fb0-9daa-fd51c3eb07ba",
        "id": "q0wvpioOkEub",
        "outputId": "59cab470-b76e-404e-fa52-063c4b3b3406",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 365
        }
      },
      "source": [
        "#heatmap hour vs day wise\n",
        "plt.figure(figsize=(12,2))\n",
        "plot1=pd.crosstab(train.dow_pickup,train.hh_pickup,values=train.vendor_id,aggfunc='count',normalize='index')\n",
        "sns.heatmap(plot1)\n",
        "plt.title('Pickup heatmap, Day-of-Week vs. Day Hour')\n",
        "plt.ylabel('Weekday')\n",
        "plt.xlabel('Day Hour, 0-23')\n",
        "plt.yticks(range(0,7),dow_names,rotation='horizontal') \n",
        "pass\n",
        "\n",
        "#heatmap hour vs month wise\n",
        "plt.figure(figsize=(12,2))\n",
        "plot2=pd.crosstab(train.mm_pickup,train.hh_pickup,values=train.vendor_id,aggfunc='count',normalize='index')\n",
        "sns.heatmap(plot2)\n",
        "plt.title('Pickup heatmap, Month of a year vs. Day Hour')\n",
        "plt.ylabel('Month')\n",
        "plt.xlabel('Day Hour, 0-23')\n",
        "plt.yticks(range(0,7),mm_names,rotation='horizontal')\n",
        "pass"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x144 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x144 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "0f53bd3855a466e44a2964c4e8924aa9aed84957",
        "_cell_guid": "796e7e0d-2900-4caf-9fe1-a8261f47e5a5",
        "id": "fCCgdzxLkEue"
      },
      "source": [
        "From the 1st heatmap,it can be seen  that max rush noticed on ending days of a week at time around 6 pm to 10 pm.\n",
        "\n",
        "Same pattern though traffic in the month of May and June is greater as compared to other months in the same time frame."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "3426ae66c4febb9699deffb0163dbaf81948e032",
        "_cell_guid": "50c72075-e538-4fa8-bca5-11a61248ccaf",
        "id": "Gg1Ep6DBkEuf"
      },
      "source": [
        "*Trip Duration Analysis*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "835bc88c9484fa6cde4f47c50ada64afe70a31bf",
        "_cell_guid": "13fc9541-2395-44d9-80bf-054a0abb041f",
        "id": "_ctfIvb-kEuf",
        "outputId": "1c9bcac0-9c08-4ca5-ec81-6ceabe052b46",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 445
        }
      },
      "source": [
        "#Plotting Histogram \n",
        "plt.figure(figsize=(10,7))\n",
        "plt.hist(train.trip_duration/60,bins=100,color='darkred')\n",
        "plt.title('Trip duration(in min) distribution')\n",
        "pass"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ZsxUVFSVJysrK0o4dOyRJkyZNUnx8vCTp888/V3p6uqqrqxUTE6Pp06fLsizvPDEAAEAr0ezvmly6dKm6dOniPs7IyNDQoUM1ceJEZWRkKCMjQ4mJicrLy9Pp06e1du1aHTt2TK+99ppWrFihyspKbd++XcnJyZKkpKQkxcbGyuFwaOPGjZo1a5YGDBigl19+Wfn5+YqJiWn5pwUAAGhFrntqMjs7W2PHjpUkjR07VtnZ2ZKknJwcjRkzRpZlaeDAgTp79qzKysqUn5+vYcOGyeFwyOFwaNiwYcrPz1dZWZmqqqo0cOBAWZalMWPGuK8FAADQnjV7RGz58uWSpAceeEAJCQkqLy9XaGioJKlr164qLy+XJLlcLoWHh7tfFxYWJpfLJZfLpbCwMHe70+lssL3+/IZkZmYqMzNTkpScnOxxH/xNQEAAtfEh6u171Ny3qLdvUW/fMl3vZgWxF198UU6nU+Xl5XrppZfUs2dPj59bluWTNV0JCQlKSEhwH5eUlHj9nm1ReHg4tfEh6u171Ny3qLdvUW/f8lW9L89O9Zo1Nel0OiVJISEhGjlypI4fP66QkBCVlZVJksrKytzrx5xOp8cDlZaWyul0yul0qrS01N3ucrkabK8/HwAAoL1rMoidP39eVVVV7n8/dOiQ+vTpo9jYWO3atUuStGvXLo0cOVKSFBsbq927d8u2bRUUFCgoKEihoaGKjo7WwYMHVVlZqcrKSh08eFDR0dEKDQ1Vp06dVFBQINu2tXv3bsXGxnrxkVvetsjIK/4BAABoSpNTk+Xl5Vq5cqUkqba2Vvfcc4+io6PVr18/paSkaOfOne7tKyQpJiZGubm5mjdvnjp06KDZs2dLkhwOhyZPnqxFixZJkqZMmSKHwyFJmjlzptavX6/q6mpFR0fziUkAAHBTsGzbtk134nqdOnXK5/e8kdGuqSdPtmBPGsf6At+i3r5HzX2LevsW9fatNrFGDAAAAC2PIAYAAGAIQQwAAMCQZm/oihvX0PoyX60bAwAArQ8jYgAAAIYQxAAAAAwhiAEAABhCEAMAADCEIAYAAGAIQQwAAMAQtq+4Cr68GwAAeBNBzDD2FgMA4ObF1CQAAIAhBDEAAABDCGIAAACGEMQAAAAMIYgBAAAYQhADAAAwhCAGAABgCEEMAADAEIIYAACAIeys3wqx2z4AADcHRsQAAAAMIYgBAAAYQhADAAAwhCAGAABgCEEMAADAEIIYAACAIQQxAAAAQwhiAAAAhrChaxvR0CavEhu9AgDQljEiBgAAYAhBDAAAwBCCGAAAgCEEMQAAAEMIYgAAAIYQxAAAAAwhiAEAABhCEAMAADCEIAYAAGAIQQwAAMAQghgAAIAhfNdkG9fQd1DOu3DBQE8AAMC1YkQMAADAEIIYAACAIQQxAAAAQwhiAAAAhhDEAAAADCGIAQAAGEIQAwAAMIQgBgAAYAhBDAAAwBCCGAAAgCEEMQAAAEP4rsl2aG3Hjle0TT150kBPAADA1TAiBgAAYAhBDAAAwBCCGAAAgCEEMQAAAEMIYgAAAIYQxAAAAAwhiAEAABhCEAMAADCEIAYAAGBIs3fWr6urU1JSkpxOp5KSklRcXKzU1FRVVFQoKipKc+fOVUBAgC5evKh169bp888/V+fOnTV//nxFRERIkt59913t3LlTfn5+mj59uqKjoyVJ+fn52rx5s+rq6jRu3DhNnDjRO08LAADQijR7ROwPf/iDIiMj3cdbt27VhAkTlJaWpuDgYO3cuVOStHPnTgUHBystLU0TJkzQG2+8IUkqLCzUvn37tHr1aj3//PPatGmT6urqVFdXp02bNmnx4sVKSUnR3r17VVhY2MKPCQAA0Po0K4iVlpYqNzdX48aNkyTZtq3Dhw9r9OjRkqT4+HhlZ2dLknJychQfHy9JGj16tD755BPZtq3s7GzFxcXplltuUUREhHr06KHjx4/r+PHj6tGjh7p3766AgADFxcW5rwUAANCeNWtqcsuWLUpMTFRVVZUkqaKiQkFBQfL395ckOZ1OuVwuSZLL5VJYWJgkyd/fX0FBQaqoqJDL5dKAAQPc1/z2a+rPr//3Y8eONdiPzMxMZWZmSpKSk5MVHh5+TQ97M6NW3hMQEEB9fYya+xb19i3q7Vum691kEDtw4IBCQkIUFRWlw4cP+6JPjUpISFBCQoL7uKSkxGBv2pa1HTte0Tb15EkDPWl/wsPDeS/6GDX3LertW9Tbt3xV7549ezbY3mQQO3r0qHJycpSXl6fq6mpVVVVpy5YtOnfunGpra+Xv7y+XyyWn0ynp0khXaWmpwsLCVFtbq3Pnzqlz587u9nrffs2320tLS93tAAAA7VmTa8SmTp2qDRs2KD09XfPnz9eQIUM0b948DR48WPv375ckZWVlKTY2VpI0YsQIZWVlSZL279+vwYMHy7IsxcbGat++fbp48aKKi4tVVFSk/v37q1+/fioqKlJxcbFqamq0b98+97UAAADas2ZvX3G5xx9/XKmpqXrzzTfVt29f3X///ZKk+++/X+vWrdPcuXPlcDg0f/58SVLv3r1111136ZlnnpGfn59mzJghP79LOfDJJ5/U8uXLVVdXp/vuu0+9e/dugUcDAABo3Szbtm3Tnbhep06d8ur1t31ru472iDViLYP1HL5HzX2LevsW9fYt02vE2FkfAADAEIIYAACAIQQxAAAAQwhiAAAAhhDEAAAADCGIAQAAGEIQAwAAMOS6N3RF29fQPmnsLQYAgO8wIgYAAGAIQQwAAMAQghgAAIAhBDEAAABDCGIAAACGEMQAAAAMIYgBAAAYQhADAAAwhCAGAABgCDvrwwO77QMA4DuMiAEAABhCEAMAADCEIAYAAGAIQQwAAMAQghgAAIAhBDEAAABDCGIAAACGEMQAAAAMIYgBAAAYQhADAAAwhCAGAABgCEEMAADAEIIYAACAIQGmO4DWb1tk5BVtU0+eNNATAADaF0bEAAAADCGIAQAAGEIQAwAAMIQgBgAAYAhBDAAAwBCCGAAAgCEEMQAAAEMIYgAAAIYQxAAAAAwhiAEAABhCEAMAADCEIAYAAGAIQQwAAMAQghgAAIAhBDEAAABDAkx3AG3TtsjIK9qmnjxpoCcAALRdjIgBAAAYQhADAAAwhCAGAABgCEEMAADAEIIYAACAIQQxAAAAQwhiAAAAhhDEAAAADGFDV7QYNnkFAODaMCIGAABgCEEMAADAEIIYAACAIQQxAAAAQwhiAAAAhhDEAAAADCGIAQAAGNLkPmLV1dVaunSpampqVFtbq9GjR+vhhx9WcXGxUlNTVVFRoaioKM2dO1cBAQG6ePGi1q1bp88//1ydO3fW/PnzFRERIUl69913tXPnTvn5+Wn69OmKjo6WJOXn52vz5s2qq6vTuHHjNHHiRO8+NQAAQCvQ5IjYLbfcoqVLl+rVV1/VK6+8ovz8fBUUFGjr1q2aMGGC0tLSFBwcrJ07d0qSdu7cqeDgYKWlpWnChAl64403JEmFhYXat2+fVq9ereeff16bNm1SXV2d6urqtGnTJi1evFgpKSnau3evCgsLvfvUAAAArUCTQcyyLAUGBkqSamtrVVtbK8uydPjwYY0ePVqSFB8fr+zsbElSTk6O4uPjJUmjR4/WJ598Itu2lZ2drbi4ON1yyy2KiIhQjx49dPz4cR0/flw9evRQ9+7dFRAQoLi4OPe1AAAA2rNmfcVRXV2dFi5cqNOnT+vBBx9U9+7dFRQUJH9/f0mS0+mUy+WSJLlcLoWFhUmS/P39FRQUpIqKCrlcLg0YMMB9zW+/pv78+n8/duxYg/3IzMxUZmamJCk5OVnh4eHX+rzwsYa+9mjehQsGeuI9AQEBvBd9jJr7FvX2LertW6br3awg5ufnp1dffVVnz57VypUrderUKW/3q0EJCQlKSEhwH5eUlBjpB25Me/vvFh4e3u6eqbWj5r5FvX2LevuWr+rds2fPBtuv6VOTwcHBGjx4sAoKCnTu3DnV1tZKujQK5nQ6JV0a6SotLZV0aSrz3Llz6ty5s0f7t19zeXtpaan7WgAAAO1Zk0Hsm2++0dmzZyVd+gTloUOHFBkZqcGDB2v//v2SpKysLMXGxkqSRowYoaysLEnS/v37NXjwYFmWpdjYWO3bt08XL15UcXGxioqK1L9/f/Xr109FRUUqLi5WTU2N9u3b574WAABAe9bk1GRZWZnS09NVV1cn27Z11113acSIEerVq5dSU1P15ptvqm/fvrr//vslSffff7/WrVunuXPnyuFwaP78+ZKk3r1766677tIzzzwjPz8/zZgxQ35+l3Lgk08+qeXLl6uurk733Xefevfu7cVHBgAAaB0s27Zt0524Xt5eq9bQQnPcuKknT5ruQotiPYfvUXPfot6+Rb19q02tEQMAAEDLIYgBAAAYQhADAAAwhCAGAABgCEEMAADAkGbtrA+0pIY+jdrePkkJAEBzMCIGAABgCEEMAADAEIIYAACAIQQxAAAAQwhiAAAAhhDEAAAADCGIAQAAGEIQAwAAMIQgBgAAYAhBDAAAwBCCGAAAgCF81yRaBb5/EgBwM2JEDAAAwBCCGAAAgCEEMQAAAEMIYgAAAIYQxAAAAAwhiAEAABhCEAMAADCEIAYAAGAIQQwAAMAQdtZHq8Vu+wCA9o4RMQAAAEMIYgAAAIYQxAAAAAwhiAEAABhCEAMAADCEIAYAAGAIQQwAAMAQghgAAIAhbOiKNoVNXgEA7QkjYgAAAIYQxAAAAAwhiAEAABhCEAMAADCEIAYAAGAIQQwAAMAQghgAAIAhBDEAAABDCGIAAACGEMQAAAAMIYgBAAAYQhADAAAwhC/9RpvX0BeBS3wZOACg9WNEDAAAwBCCGAAAgCEEMQAAAEMIYgAAAIYQxAAAAAwhiAEAABhCEAMAADCEfcTQbjW0vxh7iwEAWhNGxAAAAAwhiAEAABhCEAMAADCEIAYAAGAIQQwAAMAQghgAAIAhTW5fUVJSovT0dP31r3+VZVlKSEjQ+PHjVVlZqZSUFJ05c0bdunXTggUL5HA4ZNu2Nm/erLy8PHXs2FGzZ89WVFSUJCkrK0s7duyQJE2aNEnx8fGSpM8//1zp6emqrq5WTEyMpk+fLsuyvPfUAAAArUCTI2L+/v564oknlJKSouXLl+uPf/yjCgsLlZGRoaFDh2rt2rUaOnSoMjIyJEl5eXk6ffq01q5dq6eeekqvvfaaJKmyslLbt2/XihUrtGLFCm3fvl2VlZWSpI0bN2rWrFlau3atTp8+rfz8fC8+MgAAQOvQZBALDQ11j2h16tRJkZGRcrlcys7O1tixYyVJY8eOVXZ2tiQpJydHY8aMkWVZGjhwoM6ePauysjLl5+dr2LBhcjgccjgcGjZsmPLz81VWVqaqqioNHDhQlmVpzJgx7msBAAC0Z9e0s35xcbG++OIL9e/fX+Xl5QoNDZUkde3aVeXl5ZIkl8ul8PBw92vCwsLkcrnkcrkUFhbmbnc6nQ2215/fkMzMTGVmZkqSkpOTPe4DNEdDu+3Pu3Dhhq4ZEBDAe9HHqLlvUW/fot6+ZbrezQ5i58+f16pVqzRt2jQFBQV5/MyyLJ+s6UpISFBCQoL7uKSkxOv3RPt3o++j8PBw3os+Rs19i3r7FvX2LV/Vu2fPng22N+tTkzU1NVq1apXuvfdejRo1SpIUEhKisrIySVJZWZm6dOki6dJI17cfqLS0VE6nU06nU6Wlpe52l8vVYHv9+QAAAO1dk0HMtm1t2LBBkZGReuihh9ztsbGx2rVrlyRp165dGjlypLt99+7dsm1bBQUFCgoKUmhoqKKjo3Xw4EFVVlaqsrJSBw8eVHR0tEJDQ9WpUycVFBTItm3t3r1bsbGxXnpcAACA1qPJqcmjR49q9+7d6tOnj5577jlJ0mOPPaaJEycqJSVFO3fudG9fIUkxMTHKzc3VvHnz1KFDB82ePVuS5HA4NHnyZC1atEiSNGXKFDkcDknSzJkztX79elVXVys6OloxMTFeeVgAAIDWxLJt2zbdiet16tQpr16/oYXdaH+mnjx5Q69nPYfvUXPfot6+Rb19q02sEQMAAEDLI4gBAAAYck37iAHtUUNT0Dc6XWuz+qEAAAzmSURBVAkAQHMwIgYAAGAIQQwAAMAQghgAAIAhBDEAAABDWKwPNIAF/AAAX2BEDAAAwBCCGAAAgCEEMQAAAEMIYgAAAIYQxAAAAAwhiAEAABhCEAMAADCEIAYAAGAIG7oCzcQmrwCAlsaIGAAAgCEEMQAAAEMIYgAAAIYQxAAAAAwhiAEAABhCEAMAADCE7SuAG8CWFgCAG8GIGAAAgCEEMQAAAEMIYgAAAIYQxAAAAAwhiAEAABhCEAMAADCE7SuAFsaWFgCA5mJEDAAAwBCCGAAAgCEEMQAAAEMIYgAAAIYQxAAAAAzhU5OAD/BJSgBAQxgRAwAAMIQgBgAAYAhBDAAAwBCCGAAAgCEEMQAAAEMIYgAAAIawfQVgCFtaAAAYEQMAADCEIAYAAGAIQQwAAMAQghgAAIAhLNYHWhEW8APAzYURMQAAAEMIYgAAAIYQxAAAAAwhiAEAABjCYn2glWMBPwC0X4yIAQAAGEIQAwAAMIQgBgAAYAhrxIA2iHVjANA+MCIGAABgCEEMAADAEIIYAACAIQQxAAAAQwhiAAAAhvCpSaCd4JOUAND2NBnE1q9fr9zcXIWEhGjVqlWSpMrKSqWkpOjMmTPq1q2bFixYIIfDIdu2tXnzZuXl5aljx46aPXu2oqKiJElZWVnasWOHJGnSpEmKj4+XJH3++edKT09XdXW1YmJiNH36dFmW5aXHBQAAaD2anJqMj4/X4sWLPdoyMjI0dOhQrV27VkOHDlVGRoYkKS8vT6dPn9batWv11FNP6bXXXpN0Kbht375dK1as0IoVK7R9+3ZVVlZKkjZu3KhZs2Zp7dq1On36tPLz81v6GQEAAFqlJoPYoEGD5HA4PNqys7M1duxYSdLYsWOVnZ0tScrJydGYMWNkWZYGDhyos2fPqqysTPn5+Ro2bJgcDoccDoeGDRum/Px8lZWVqaqqSgMHDpRlWRozZoz7WgAAAO3dda0RKy8vV2hoqCSpa9euKi8vlyS5XC6Fh4e7zwsLC5PL5ZLL5VJYWJi73el0Nthefz6AltHQujGJtWMA0Frc8GJ9y7J8tqYrMzNTmZmZkqTk5GSP0Aeg+dr6n52AgIA2/wxtCfX2LertW6brfV1BLCQkRGVlZQoNDVVZWZm6dOki6dJIV0lJifu80tJSOZ1OOZ1OHTlyxN3ucrk0aNAgOZ1OlZaWXnF+YxISEpSQkOA+/va9ADRfW/+zEx4e3uafoS2h3r5FvX3LV/Xu2bNng+3XtY9YbGysdu3aJUnatWuXRo4c6W7fvXu3bNtWQUGBgoKCFBoaqujoaB08eFCVlZWqrKzUwYMHFR0drdDQUHXq1EkFBQWybVu7d+9WbGzsdT4iAABA29LkiFhqaqqOHDmiiooK/fjHP9bDDz+siRMnKiUlRTt37nRvXyFJMTExys3N1bx589ShQwfNnj1bkuRwODR58mQtWrRIkjRlyhT3BwBmzpyp9evXq7q6WtHR0YqJifHWswL4f+w5BgCtg2Xbtm26E9fr1KlTXr1+YwudgfaoLQUxpm58i3r7FvX2rTY5NQkAAIAbRxADAAAwhO+aBCCJdWMAYAIjYgAAAIYQxAAAAAwhiAEAABjCGjEAjWLdGAB4FyNiAAAAhhDEAAAADCGIAQAAGMIaMQDXhHVjANByGBEDAAAwhCAGAABgCFOTAG4Y05UAcH0YEQMAADCEIAYAAGAIQQwAAMAQghgAAIAhLNYH4BUs4AeAphHEAPgM4QwAPDE1CQAAYAhBDAAAwBCmJgEYxXQlgJsZI2IAAACGEMQAAAAMYWoSQKvDdCWAmwUjYgAAAIYwIgagTWCUDEB7xIgYAACAIYyIAWizGCUD0NYxIgYAAGAII2IA2hVGyQC0JYyIAQAAGEIQAwAAMISpSQDtXkPTlRJTlgDMY0QMAADAEIIYAACAIUxNArhpNTZleTmmMAF4CyNiAAAAhjAiBgBNYG8yAN7CiBgAAIAhjIgBwHVglAxASyCIAUALIZwBuFYEMQDwIsIZgKthjRgAAIAhjIgBgI8xSgagHkEMAFoBwhlwcyKIAUArRTgD2j/WiAEAABjCiBgAtCGMkgHtC0EMANo4vrwcaLsIYgBwk2A0DWh9CGIAcBNrbDSNgAb4BkEMAHAFpjsB3yCIAQCuG9OdwI0hiAEAWhSjaUDzEcQAAEYQ2ACCGACglWP6E+0ZQQwA0OY0dzStIYQ4tCYEMQDATYUpUbQmBDEAABpwI6NuEkEOzUMQAwDAC240yF2OYNc+EcQAAGgDWBfXPhHEAABo51p6dK4xBL5rRxADAAAtwleB73INBcC2su1Jqwli+fn52rx5s+rq6jRu3DhNnDjRdJcAAEAb0NwA2NB58y5caOnuXBM/o3f/f3V1ddq0aZMWL16slJQU7d27V4WFhaa7BQAA4FWtIogdP35cPXr0UPfu3RUQEKC4uDhlZ2eb7hYAAIBXtYqpSZfLpbCwMPdxWFiYjh07dsV5mZmZyszMlCQlJyerZ8+eXu3Xs7bt1esDAADzvJ0nrqZVjIg1V0JCgpKTk5WcnGy6K61aUlKS6S7cVKi371Fz36LevkW9fct0vVtFEHM6nSotLXUfl5aWyul0GuwRAACA97WKINavXz8VFRWpuLhYNTU12rdvn2JjY013CwAAwKv8ly1btsx0J/z8/NSjRw+lpaXpv/7rv3Tvvfdq9OjRprvVpkVFRZnuwk2FevseNfct6u1b1Nu3TNbbsm1WpAMAAJjQKqYmAQAAbkYEMQAAAENaxT5iuH7r169Xbm6uQkJCtGrVKklSZWWlUlJSdObMGXXr1k0LFiyQw+Ew3NP2oaSkROnp6frrX/8qy7KUkJCg8ePHU3Mvqa6u1tKlS1VTU6Pa2lqNHj1aDz/8sIqLi5WamqqKigpFRUVp7ty5Cgjg11lLqaurU1JSkpxOp5KSkqi3l82ZM0eBgYHy8/OTv7+/kpOT+Z3iRWfPntWGDRv01VdfybIs/eQnP1HPnj2N1Zs1Ym3ckSNHFBgYqPT0dHcQ27p1qxwOhyZOnKiMjAxVVlYqMTHRcE/bh7KyMpWVlSkqKkpVVVVKSkrSc889p6ysLGruBbZt68KFCwoMDFRNTY2WLFmiadOm6f3339eoUaN099136ze/+Y1uv/12ffe73zXd3Xbj/fff12effeZ+j69evZp6e9GcOXP08ssvq0uXLu42fo97z7p16/R3f/d3GjdunGpqanThwgW9++67xurN1GQbN2jQoCtSe3Z2tsaOHStJGjt2LF8X1YJCQ0Pdn67p1KmTIiMj5XK5qLmXWJalwMBASVJtba1qa2tlWZYOHz7s/mR1fHw89W5BpaWlys3N1bhx4yRdCsPU2/f4neId586d01/+8hfdf//9kqSAgAAFBwcbrTdjy+1QeXm5QkNDJUldu3ZVeXm54R61T8XFxfriiy/Uv39/au5FdXV1WrhwoU6fPq0HH3xQ3bt3V1BQkPz9/SVd2hDa5XIZ7mX7sWXLFiUmJqqqqkqSVFFRQb19YPny5ZKkBx54QAkJCfxO8ZLi4mJ16dJF69ev14kTJxQVFaVp06YZrTdBrJ2zLEuWZZnuRrtz/vx5rVq1StOmTVNQUJDHz6h5y/Lz89Orr76qs2fPauXKlTp16pTpLrVbBw4cUEhIiKKionT48GHT3blpvPjii3I6nSovL9dLL710xfce8jul5dTW1uqLL77Qk08+qQEDBmjz5s3KyMjwOMfX9SaItUMhISEqKytTaGioysrKPNYd4MbV1NRo1apVuvfeezVq1ChJ1NwXgoODNXjwYBUUFOjcuXOqra2Vv7+/XC4XX4nWQo4ePaqcnBzl5eWpurpaVVVV2rJlC/X2svp6hoSEaOTIkTp+/Di/U7wkLCxMYWFhGjBggCRp9OjRysjIMFpv1oi1Q7Gxsdq1a5ckadeuXRo5cqThHrUftm1rw4YNioyM1EMPPeRup+be8c033+js2bOSLn2C8tChQ4qMjNTgwYO1f/9+SVJWVhZfidZCpk6dqg0bNig9PV3z58/XkCFDNG/ePOrtRefPn3dPA58/f16HDh1Snz59+J3iJV27dlVYWJh7ZP3jjz9Wr169jNabT022campqTpy5IgqKioUEhKihx9+WCNHjlRKSopKSkr42HML+/TTT7VkyRL16dPHPXT92GOPacCAAdTcC06cOKH09HTV1dXJtm3dddddmjJlir7++mulpqaqsrJSffv21dy5c3XLLbeY7m67cvjwYf3+979XUlIS9fair7/+WitXrpR0adrsnnvu0aRJk1RRUcHvFC/58ssvtWHDBtXU1CgiIkKzZ8+WbdvG6k0QAwAAMISpSQAAAEMIYgAAAIYQxAAAAAwhiAEAABhCEAMAADCEIAYAAGAIQQwAAMCQ/wN8P3OtgOMPEwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "b0897ff02bd85578c79135dd9494c5ea33b4abb3",
        "_cell_guid": "0f59e946-840f-4937-aca8-cd09484134b0",
        "id": "H52Py-jnkEuj"
      },
      "source": [
        "Most of the trips last for less than 10-20 minutes and barely few could cross a span of 50-60 min.\n",
        "\n",
        "\n",
        "People travel shorter distances in short time duration"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "5fc7340b3e989347e116165e1fc447f7b7357dba",
        "_cell_guid": "e6955d27-2e53-44b5-9e7d-87173f360f4c",
        "id": "sB49SZ_skEun"
      },
      "source": [
        "No of trips that lasted for the max duration was noticed on Thursday,Friday and Saturday betwen 8 AM to 5 PM and if we go by Month vs Hour distribution then in the starting months of 2016 larger trip duration lasted during 2 to 5 PM."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "c6031a54b283043377ae314453308a48c6a28f9c",
        "_cell_guid": "0de2327c-234f-4a70-91cf-197098874ce1",
        "id": "PkLT5MdpkEuo"
      },
      "source": [
        "\n",
        "Analyzing trips with respect to **Vendor**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "c4c97827e09dde84131eaaf2e79eab1d8408eb33",
        "_cell_guid": "03d1bc04-ab08-4207-88f9-d3725c44a236",
        "id": "KX04SlAKkEup",
        "outputId": "a21755b7-b809-4a96-faef-80f64550f0ad",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 799
        }
      },
      "source": [
        "#No of trips acc to passenger count\n",
        "plt.figure(figsize=(12,4))\n",
        "table=pd.crosstab(index=train.passenger_count ,columns=train.vendor_id ,values=train.trip_duration/60, aggfunc='mean')\n",
        "plt.plot(table)\n",
        "plt.legend(['Vendor 1','Vendor 2'])\n",
        "plt.xlabel('No of passenger')\n",
        "plt.ylabel('Trip duration')\n",
        "plt.title('Trip duration dist acc to passenger count')\n",
        "pass\n",
        "\n",
        "plt.subplots(nrows=1,ncols=2,figsize=(12,8))\n",
        "\n",
        "#No of trips on the basis of Month wrt Vendor using vendor id\n",
        "plt.subplot(121)\n",
        "data = pd.crosstab(index=train.mm_pickup,columns=train.vendor_id,values=train.id,aggfunc='count')\n",
        "plt.title('Trip distribution as per both the vendors')\n",
        "plt.xlabel('Monthly pickup')\n",
        "plt.ylabel('No of trips')\n",
        "plt.xticks(range(1,7),mm_names)\n",
        "plt.plot(data)\n",
        "plt.legend(['Vendor 1','Vendor 2'])\n",
        "pass\n",
        "\n",
        "#No of trips on the basis of Month wrt Vendor\n",
        "plt.subplot(122)\n",
        "data1 = pd.crosstab(index=train.hh_pickup,columns=train.vendor_id,values=train.id,aggfunc='count')\n",
        "plt.title('Trip distribution as per both the vendors')\n",
        "plt.xlabel('Hourly pickup')\n",
        "plt.ylabel('No of trips')\n",
        "plt.plot(data1)\n",
        "plt.legend(['Vendor 1','Vendor 2'])\n",
        "pass"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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lJYXvv/+e559//oqg53IPPPAA+/fv54UXXuCWW26xzejR0PNe6tFHH+XChQvMnDmTo0ePsmnTJp5//vlq+9Tmfl8r/99++y0nT57k8OHDfPbZZwQHB2M0GmudRtH4pN7+hdTbUm9fTurtxq23JUi3oz//+c9s3LiRPn368PLLL/Paa69x66231rh///79+eCDD1izZg29e/dm3rx5LFy48JrX8PHxYeXKlYwcOZLu3buzYMECli9fbqtspkyZwh133MGECRPw9/fntddeq3M+nnzySVJTU4mOjubJJ5/kiSee4Omnn7a9P3fuXCZMmMCdd97JsGHD8PLy4o477qh2jt/97nf4+fnRp08f/P39r9rSpNFo+OKLL7jhhhuYMGECAwYM4Pz583z33XfV+o7Vx8KFCwkJCWHUqFGMHj2aoKCgaotxuLu7c+LECe666y66du3KbbfdxpAhQ6766O1S7du3Z+bMmdx+++3ceOONuLm58dlnn9kewY0aNYr4+HgOHTrEsGHDiIyMZPbs2RiNxnrPtzpv3jyWL19OZGQk7733HqtXr6Zfv34AuLq6smHDBlxcXBg+fDgjRozA3d2ddevW2VpiBgwYwNNPP81vf/tbAgICeOKJJ+qVjotef/119u3bR2hoaJ1aPAIDA9m1axd+fn5MnTqVbt26ce+995Kammqb37omkZGRREVFcfDgQR544IFGO++lgoKC+Oqrr9izZw9RUVE8/fTTLFiwoNo+tbnfNVFKMWvWLHr16sXw4cMpLCxk7dq1jbpgiag7qbd/IfW21NuXk3q7cettjbq805loFhqNhvfee4/77rvP3kkRTeTFF19k9erV1eZWFUK0XFJvt35SbwtHIi3pQgghhBBCOBgJ0oUQQgghhHAw0t1FCCGEEEIIByMt6UIIIYQQQjgYCdKFEEIIIYRwMBKkCyGEEEII4WD09k6Ao7p8pbXa8PPzq9Ok/y1Ja84btO78Sd5arvrkr0OHDk2UGscmdfb1SX5bv7aW59aS35rqbWlJF0IIIYQQwsFIkC6EEEIIIYSDkSBdCCGEEEIIByN90oUQdqOUoqSkBKvVikajqfPxGRkZlJaWNkHKHENN+VNKodVqMRgM9bpvbUFtylZrLz+Xq21+pXwJ4RgkSBdC2E1JSQlOTk7o9fWrivR6PTqdrpFT5Tiulb+KigpKSkpwdXVt5lS1DLUpW629/FyuLvmV8iWE/Ul3FyGE3Vit1noH6G2dXq/HarXaOxkOS8pWw0j5EsL+JEgXQtiNPEpvGLl/NZN703ByD4WwLwnShRBt1u23386WLVuqbVuxYgXPPPNMg88dExOD2Wyu9/ErV64kJiaGoKCgBp1H2Iejl62hQ4dK2RLCwUmQLoRos6ZMmUJcXFy1bXFxcUyZMqVZ06GUuqJrwYABA/jkk0/o2LFjs6ZFNA5HL1tr1qyRsiWEg5MgXQjRZk2YMIFNmzZRVlYGwJkzZ8jIyCAmJoatW7cyceJExo4dy8yZMyksLASqWjHnz5/P2LFjGT16NElJSQCYzWbuvvtuRo0axe9//3uUUrbrvP3228TGxhIbG8uKFSts1xo2bBhPPfUUsbGxV6yY2atXLzp16tQct0E0AUcvW8HBwc1xG4QQDSCjaoQQDsG6ZgXqTHLdjtFoqgUsl9MEh6G96zc1vu/j40NUVBSbN29m7NixxMXFMXHiRHJycnjjjTf46KOPcHNzY+nSpSxfvpzZs2cD4Ovry/r161m1ahVvvfUW8+fPZ+HChQwcOJDZs2ezceNGPvzwQwAOHTrExx9/zNdff41SiltuuYXBgwfj5eVFcnIyixYton///nXKt6ibmsrW9crPtUjZEkI0NWlJF0K0aZd2S7jYHWHfvn0kJiYyefJkbrrpJj755BPOnj1rO2b8+PEAREZGcubMGQB2797N1KlTARgzZgze3t4A7Nmzh3HjxuHm5oa7uzvjx4/nhx9+AKBjx44SRLViUraEEA0hLelCCIdwrVbJmuj1eioqKhp03bFjx/Liiy/y008/UVxcTGRkJBs2bGD48OEsW7bsqse4uLgAoNPpqKysrPe13dzc6n2sqL2aylZjlJ9rkbIlhGgIaUkXQrRp7u7uDBkyhDlz5tgG9fXv35+EhASSk6u6SBQVFXHy5MlrnmfQoEF8/vnnAMTHx5ObmwtU9TNev349xcXFFBUVsW7dOmJiYpowR8JRSNkSQjREs7SkL1u2jP379+Pl5cXrr78OwK5du/jkk09IS0vj5ZdfpnPnzgBkZmYye/ZsOnToAEBERAQzZ84E4NSpUyxdupSysjL69u3L9OnT0Wg0FBQUsHDhQi5cuIC/vz+zZ8/Gw8MDpRQrV67kwIEDuLi48NhjjxEeHt4cWRZCtCBTpkzh4Ycf5p///CcAJpOJhQsX8vjjj9sG/v3hD3+w1VNXM3v2bB5//HFGjRpFdHQ0QUFBAPTu3Zs77riDCRMmAHD33XfTq1cvW1eGmrz77rv885//JDMzkzFjxhAbG8v8+fMbI7uiGTlq2Vq2bBkXLlyQsiWEA9Oo+o6aqYMjR45gMBhYunSpLUg/e/YsWq2W5cuXc//991cL0l999VXbfpd69tlnmT59OhEREbzyyiuMHz+evn37snr1ajw8PJgyZQpffPEFBQUF3Hfffezfv59169bx7LPPcuLECVatWsXLL79cqzRfPhq+Nvz8/MjKyqrzcS1Ba84btO78OXLeioqKGvRYvqm7K9jb9fJ3tft3sYGjrbm8zq5N2Wrt5edydc1vQ/8+7c2R676m0tby3FryW1O93SzdXXr06IGHh0e1bR07dqzTl0lOTg7FxcV07doVjUbD8OHDSUhIACAhIYERI0YAMGLECNv2vXv3Mnz4cDQaDV27dqWwsJCcnJxGypVoLaxN/ztVCCGEaFOaoQ241XPIgaOZmZn84Q9/wNXVlbvuuovu3btjNpsxmUy2fUwmk22ltLy8PHx8fADw9vYmLy8PqJpb1s/P74pjLu57qY0bN7Jx40YA5s2bV+242tLr9fU6riVorXlLzSlixpofGRJq5pGhIbT3NNg7SY3OkT+7jIwM9PqGVUMNPd7RXSt/Li4uDvvZCiHartIKK49+dYru/q48OqAdHi46eyepRXK4bzcfHx+WLVuG0Wjk1KlT/OMf/7hq15eaaDQaNBpNna87ZswYxowZY3tdn8cnreWxy9W01rz9+4fzlFVY2X4qm61JWUzu7sttPX1xc2o9FYojf3alpaXodPW/1629u8L18ldaWnrFZ9tWu7sIIRzHWUsZ2UUVfJ+az9ELxcwa3J7Idu72TlaL43Czuzg5OWE0GgEIDw8nMDCQ9PR0fH19yc7Otu2XnZ2Nr68vAF5eXrZuLDk5OXh6egJVi0Jc+gV26TFC5JVUsDk5j9HhXqx5oD9DOxn57+FsHvvyFBtP5lJplUd1QgghRF2lWaoGRT89uD0uOi1/3nSGlfszKa+02jllLYvDBekWiwWrtepDzMjIID09ncDAQHx8fHB1dSUxMRGlFNu2bSM6OhqA6Ohotm7dCsDWrVsZMGCAbfu2bdtQSpGYmIibm9tVu7qItmntiVzKKhWTbvAhwOjC7KEd+MfYEAI8nFm8+zy/X5fCzxlF9k6mEEII0aKkWUrRamBYiJGFvwplbIQ3Xxw183/rUzmdW2rv5LUYzdLdZdGiRRw5coT8/HweeeQRpk2bhoeHB//617+wWCzMmzeP0NBQnn/+eY4cOcLHH3+MTqdDq9Xym9/8xjbodMaMGSxbtoyysjKioqLo27cvUDXF1cKFC4mPj7dNwQjQt29f9u/fz1NPPYWzszOPPfZYc2RXtABllVa+TcwhuoM7Hb1cbNu7+rny6s2d2J6az38OZPL8xtMMDvbgwb4BtDc62zHFQgghRMuQZikjwN0JJ50WJ+DRge3o38GdJbvP87t1KTzY158JXX3q1T25LWmWKRhbIpmCsbrWlrfvknJZ8sN5XhodTGQ796vmr7TCStwxM58ezqbCChO7+XBHLxPuzi2rv7ojf3b2noLx9ttv54knnmDkyJG2bStWrODkyZPMmzev3ueFqoVm1q5dW+8udk888QSHDh1Cr9cTFRXFq6++ipOTU7V9ZArGXzjaFIyOWLYu5veJJ57gxx9/xMnJqcayBTIFY0vkKHme9W0yvq56/jwquNr23OIK3tydzr5zhfRt785Tg9vj61r/9mJHyW9D2XUKRiEciVKKuGNmwnxc6B1Y8xeQi17LtF5+LJsYzohQT744aubRL0+x7kSO9FdvJaZMmUJcXFy1bXFxcbbVIZuLUsrWze+iW2+9lR07drBp0yZKSkr44IMPmjVNomEcvWxt27ZNypZoElalOGcpo4PnlU+fvV31/GlkR347IJDDmUU89U0yu8/k2yGVLYME6aLNOZBeyJm8Mibf4FurR20mNyeeGtye+eNCCfJ05p97Mpi9NoWD6YXNkFrRlCZMmMCmTZtsKz+eOXOGjIwMYmJi2Lp1KxMnTmTs2LHMnDmTwsKqzzsmJob58+czduxYRo8eTVJSElA15evdd9/NqFGj+P3vf19tjuC3336b2NhYYmNjWbFihe1aw4YN46mnniI2NvaKluDRo0fbZquKiooiPT29OW6JaCRStkRblV1UQWmlIqiGLqIajYZfdfVhwfhQAtz1vLItjSW70ykul0Gll3O4KRiFaGpxR834uuq5McSzTsd1MRl4+aZO7DqTz6oDF3gh/gwDgjyY3i+AoKu0GIi6eWdvBsk5JXU6RqPRXHPBjDAfAzOiA2t838fHh6ioKDZv3szYsWOJi4tj4sSJ5OTk8MYbb/DRRx/h5ubG0qVLWb58uW28i6+vL+vXr2fVqlW89dZbzJ8/n4ULFzJw4EBmz57Nxo0b+fDDDwE4dOgQH3/8MV9//TVKKW655RYGDx6Ml5cXycnJLFq0iP79+9eYxvLycj799FP++te/1uneiF/UVLauV36uRcqWEFd3cWaX630vBnu58OrNoXx46AKfHTHzc2YRfxoZLN+nl5CWdNGmpOSUcPB8ERO6+eCkq/uAFY1Gw5BOniy5JYwHo/z5OaOIJ78+xTv7MigorWyCFIumdmm3hIvdEfbt20diYiKTJ0/mpptu4pNPPuHs2bO2Y8aPHw9AZGQkZ86cAWD37t1MnToVqFp3wdvbG4A9e/Ywbtw43NzccHd3Z/z48fzwww9A1crL1wqiAJ577jliYmKIiYlp3IyLJidlS7RFtQ3SAZx0Gh7oG8DfxnQit7iST35u+f3LG5O0pIs2Je5YDi46DWO7eDfoPM46LVN7mogN9+KDQ1l8czyHLafyuDvSn7ER3ui1MmK9rq7VKlmTxhj4N3bsWF588UV++ukniouLiYyMZMOGDQwfPpxly5Zd9RgXl6oZgXQ6HZWV9f9xdr1BefPnzyc7O5t33nmn3tcQNZetpl4My5HL1oIFC6RsiSaRll+GQa+t04DQXoFuDA0x8n1qPo9WWHHRSxsySEu6aEPMxRVsS8ljTGcvjI20RLG3q57HYtqxYHwoYT4Glu/N4Olvktl/rqBRzi+anru7O0OGDGHOnDm2QX39+/cnISGB5ORkoGqWi5MnT17zPIMGDeLzzz8HID4+ntzcXKCqn/H69espLi6mqKiIdevW1arl8oMPPmDz5s0sXboUrVaq6pbIkcvWli1bpGyJJpFmKaOjp3Odp1ccEepJSYWVPWfl+/Mi+esUbcbaxBwqrTDxhsZfdTbMx8BfRwfz3IggKpXiL5vP8pf4M5zOk0UbWoIpU6Zw5MgRWyBlMplYuHAhjz/+OGPGjGHSpEnXDaRmz57NDz/8wKhRo1i7di1BQUEA9O7dmzvuuIMJEyZwyy23cPfdd9OrV6/rpumZZ57hwoULTJo0iZtuuomFCxc2PKOi2Tlq2crKypKyJZrEOUtpvfqV9wp0w+SqZ2uKpQlS1TLJPOk1kHnSq2vpeSutsPLwFyfp4e/KcyM6XvF+Y+avvFLxbWIOH/2URXGFlXER3tzd2w9Pg316lznyZ2fvedId3fXyJ/Ok/8LR5kl3RHXNr8yT3vLYO8+lFVamfZTIPZF+3Nnbr87Hr9yfyVfHzKy6LWTlv98AACAASURBVALPWjzxtnd+G4vMky7atPhTeeSXVjKle+O3ol/OSadhcndf3poUztgu3qw7kcsjX50i7qiZ8kr5TSyEEKJ1Opdf+0GjVzMi1JNKBTtSpTUdJEgXbYBVKb48lkOEyUB3f9dmu66nQc8jA9vxxq/CiDC58q/9mTz1zSn2nM2v97RvQgghhKOqy8wuVxPm40KwlzPbpMsLIEG6aAP2phVwLr+MSbVcvKixdfJ24cVRHfnTyI5oNRr+vjWNP8efIaWOc4ILIYQQjuxikN6hhoWMrkej0TAi1JMjF4rJLChvzKS1SBKki1Yv7lgO/m56hnYy2i0NGo2G6CAP3pgQxm+iAzhlLmH22hSW/XCe3JK20yf2cvJEoWHk/tVM7k3DyT0UdZVmKcPfTd+gKRSHh1YtNCit6RKki1bupLmEnzOKuOUGH3QOMHe5Xqvhlm6+vDWpMxO6+rDxZC6PfnmKz45kU17Z9pZE1mq1bWrgXmOqqKiQ6fOuQcpWw0j5EvWRZilr8IqhgR7OdPd3ZWtKXpv/oSiLGYlWLe6oGVe9lps6N2zxosZmdNExIzqQcV29WbU/k38fuMD6E7k81DeAQcEedumWYw8Gg4GSkhJKS0vrlWcXFxdKS1vvNJc15U8phVarxWAw2CFVYLVaeeaZZ/D19eWZZ54hMzOTRYsWkZ+fT3h4OE8++SR6vZ7y8nKWLFnCqVOnMBqNzJo1i4CAAAA+//xz4uPj0Wq1TJ8+naioKAAOHjzIypUrsVqtjB492jZ1YV3Vpmy19vJzudrm197lS7RMSinSLGXEhns2+FwjQj15KyGDlNxSwnzabjmUIF20WllF5XyfamFCNx/cnRtn8aLG1tHThT+ODOZgeiH/2pfJvO1p9Apw5df9A+ns2/orJo1Gg6tr/Qfztpbpt2riqPn79ttvCQoKori4GIDVq1czYcIEhg4dyvLly4mPj+fmm28mPj4ed3d3Fi9ezI4dO3j//feZPXs2Z8+eZefOnSxYsICcnBxeeukl3njjDQDeffdd/vjHP2IymXj22WeJjo6mY8crp029ntqULUe9v02lreVXNK+ckkqKK6wEebo0+FxDOxlZsTeDrcmWNh2ky7Ms0Wp9czwHBdzSzcfeSbmuqPbuLPxVKI8MCOR0Xhm/W5vCm7vSMRfL43rhWLKzs9m/fz+jR48GqlrPDh8+zKBBgwAYOXIkCQkJAOzdu5eRI0cCVatm/vzzzyilSEhIYMiQITg5OREQEEC7du1ISkoiKSmJdu3aERgYiF6vZ8iQIbZzCSEcW5ql6ilNQ7u7QNXsaP06uLMt1YK1DXd5kSBdtErF5VbWJ+UyONhIoEfDK4zmoNNqGN/Vh39OCmdyd1+2puTx6Jcn+eTnLEor2l5/deGYVq1axX333WfrQpKfn4+bmxs6XdXTKl9fX8xmMwBmsxmTyQSATqfDzc2N/Pz8atsvPeby7SaTyXYuIYRjO5vXsOkXLzc81IvsogoOZxY1yvlaIunuIlqlTadyKSyzMrkZFi9qbB7OOqb3C2BchDerDmSy+scs1p/I5cG+AdwYYmwz/dWF49m3bx9eXl6Eh4dz+PBhu6Zl48aNbNy4EYB58+bh51f31Q31en29jmupJL+tnz3zbD5swaDX0q1TO7SN8D31Ky8flu3J4If0Mkb1DLnqPq39M5YgXbQ6lVbFV8dyuMHPlW5+zbd4UWNrb3Tm2eEdOXS+kH/tz2T+jnN8fdyVh/sH0LUF50u0XMePH2fv3r0cOHCAsrIyiouLWbVqFUVFRVRWVqLT6TCbzfj6Vv049vX1JTs7G5PJRGVlJUVFRRiNRtv2iy495tLt2dnZtu2XGzNmDGPGjLG9rk9f67bWR1vy2/rZM88nM/Nob3TCfMnfcEPFdHQn/sQFHuzthZPuys4freUz7tChw1W3S3cX0ersOVvA+YJyJnd3/L7otRHZzp3Xx4XyREw7zheU8X/rU1m48xxZRbLQg2he99xzD2+99RZLly5l1qxZ9OrVi6eeeoqePXuye/duALZs2UJ0dDQA/fv3Z8uWLQDs3r2bnj17Vq0ZEB3Nzp07KS8vJzMzk/T0dLp06ULnzp1JT08nMzOTiooKdu7caTuXEMKxNcb0i5cbEepJYZmVvecKG/W8LYW0pItWJ+6YmUAPJ2I62m/xosam02q4qYs3Q0OM/PfnbL48lsPO0/nc1sPErT18G7RwhBANde+997Jo0SLWrFlDWFgYsbGxAMTGxrJkyRKefPJJPDw8mDVrFgDBwcEMHjyYOXPmoNVqefjhh21zcv/617/m73//O1arlVGjRhEcHGy3fAkhaqe80kpmYTkjwho+/eKl+rRzx8ugY2uyhcHBrec7vbYkSBetyvGsYo5eKGZG/wCHWLyosbk56XigbwBjI7z594ELfPhTFhuScnmgrz/DQz0bpR+gELXRs2dPevbsCUBgYCCvvPLKFfs4OzszZ86cqx4/depUpk6desX2fv360a9fv8ZNrBCiSaXnl2NVEGRs3JZ0nVbDsBBP1p/IpbCs0mGnU24q0vwmWpW4o2bcnbSM7uxl76Q0qUAPZ/4wLIiXb+qEt6uehTvT+cP6VI5eaLuj4IUQQthHmuXizC4NnyP9ciNCPSm3KnadyW/0czs6CdJFq5FRUMauM/mMjfDGzalt/NruGeDG/HEhPD24PdlFFTyz4TTzv08js0D6qwshhGgevwTpjT/lcYTJQHujE1uTLY1+bkcnQbpoNb4+noMGmNACFi9qTFqNhthwL/45KZw7e5v44WwBj399itUHL1BcLvOrCyGEaFpp+aWYXPW4OjV+WKnRaBgR6slPGUVkt7EJEyRIF61CYVkl3yXlcWOIJ35uTvZOjl0Y9FruifRn2cRwBgUb+eRwNo9+eZI1+9PIlZVLhRBCNJGzeY0/s8ulRoR6oYDtqW2rNV0GjopWYePJPIorrEy6oeUtXtTY/N2d+N3QDtzSzYeV+zNZvD0ZraZqlPzIME9iOhqbpLVDCCFE26OUIi2/jOEhjTuzy6U6eDoTYTKwNdnClO6m6x/QSkiQLlq8qsWLzPQKcKWLyWDv5DiMbn6uzLs5hHyNG18cSGVbSh4Ld6bjojtPTLCREaGeRLV3R98KZ8ERQgjRPPJKKyksszZpSzpUDSB9Z18mZ/JKCfZq/AGqjkiCdNHi7Tydz4WiCmYOCLR3UhxSmMmN+6P8ubePH0cvFLM12cKO0xa2pVjwctFxY4iREWFedDUZ0MgUjkIIIeqgKQeNXurGEE/+tT+TrckW7ovyb9JrOQoJ0kWLppQi7piZDkYnooM87J0ch6bVaOgZ4EbPADd+Ex3A/nOFbEmxsCEpj28Sc2lvdGJEqCcjQr3o0MSVrRBCiNahuYJ0H1c9kYFubEu1cG8fvzbRqCRBumjRjl4o5kR2CY8MCJSFfOrASaclJthITLCRwrJKdp3JZ2uyhY9+ymbNT9lEmAyMDPPkxhBPvA1STQghhLi6NEsZTlpNs0zaMCLMizd2pXMsq5ju/m5Nfj17k29f0aLFHTNjdNYSG966Fy9qSu7OOsZ09mZMZ2+yisrZnmJha4qFFXszeXdfJn3buzMi1JOYYCMGvQw4FUII8Ys0SxkdjM7Nssr3oGAP/rlHw9ZkS52CdKUUSeYSgjydW9Q6KhKkixYrPb+MH84UcHtPEy4SPDYKPzcnbu1h4tYeJlJzS9manMe2FAsLdqZj0J9nUEcjI8I86dPOvVkqZCGEEI4tzVJGiHfzDOR0c9IxIMiDHafzmRF9/XFoFwrL2Xwqj02n8jhfUE6vAFf+OrpTi/n+kiBdtFhfHTOj02r4VRtbvKi5hHi78EDfAO6L8udoZjFbUyx8f9rClhQLXgYdw0I8GRnmSRdfGXAqhBBtUXml4nxBGUM7GZvtmiPCPNlxOp+D6YWMC7hyAGlZpZXdZwrYdDKXH88XoYDIQDdiOnoQdyyH93+8wAN9A5otvQ0hQbpokQpKK9l4Mo/hoZ74ukoxbkpajYaegW70DKwacLr3XCFbky2sO5HL18dz6GB0YkSYFyNCPWlvlAGnQgjRVmQUlGFVTT9o9FL92ntgdNayNdnCuD5V2y52Z9l0Mo9tqRYKy6wEuOu5s7eJ2HAvAj2q0ldSofj0iJkb/F0Z2LH5fljUl0Q3okVal5RLaaVi8g3Sit6cnHRaBgcbGRxspKCskl2n89mSYuHDQ1l8eCiLbn4GRoR6cWOIES8ZcCqEEK1ac83sciknnYYhnTzZkpxHWl4J646a2XQyj9S8Upx1GgYHGxnd2YvegW5XTCgxIzqAE9nFLNqVzsLxLrbg3VHJt6hoccorFd8cz6FPOzdCfWTxInvxcNZxUxdvburizYXCqgGnW1IsLN+bwbv7MqoGnIZ5EdPRQ8YMCCFEK2SPIB2qurysT8pl2qq9AESYDDw6MJAbQzzxcK55YKizTsvcYUHMWZvCq9vTmHdzCM46x/1+kiBdtDg7TlswF1fw5KB29k6K+B9/dyem9jQxtaeJlJwStv5vhpi9O85h0GsZFOzByDAvIgPdWsyAHSGEENeWll+Gt0GH+zUC46bQ3d+VMZ298PfyYEh7ZzrVYeBqO6MzTw9pz8tb03hnbyaPxThuLCFBumhRlFJ8cdRMsJczfdu72zs54ipCfQyE+hi4P8qfw5lFbE22sPN0PluSLXgbdAwL9WREqAw4FUKIli7NUtbsrehQNVbqyUHt8fPzIysrq87Hx3Q0MrWHL58dMdPd35VRDjqNswTpokX5KaOI5JxSHo9pJwGeg9NqNPQOdKd3oDszBwSyL62QLSl5rE3M5atjOQR5OjMy1JPhoZ60kwGnQgjR4qRZyhgU3DJX+76vjz/Hs4r5557zhPsamm0aybqQIF20KF8eM+PlomNkmKe9kyLqwFmnZXAnI4M7GSkorWTnmXy2Jufx/qEs3j+UxQ1+rowM82RoJyOeMuBUCCEcXn5pJZbSSru0pDcGnVbD728MYva3yby6PY3540IcbqEjx+0tL8RlzuaVkpBWyK+6+jj0QA9xbR4uOm7u4s3fbwrhnSmduT/Kn6LySt5KyOChz5L425azbE+xUFphtXdShRBC1MA2aNToeC3QteXrquf3N3YgPb+MJbvPo5Syd5KqkSYr0WJ8eSwHJ62GcV297Z0U0Uj83Z24vaeJ23r4kpJbytZkC9tSLCSkFeCq1zK4kwcjQqum0pIBp0II4TjOWkoB6OjVMlvSL+od6M69ffx57+AFeiTmcEs3X3snyUaCdNEiWEoq2Jycx6hwT7ylO0Sro9FoCPMxEHbpgNOUqgGn8acs+LjqGR5iZESYF+E+LjIeQQgh7CzNUoZeCwHuTvZOSoNN7eHLsQvFrNyfSYTJlW5+rvZOEiDdXUQLsfZELmWViok3OM4vXNE0dFoNke3ceXJQe1ZN7cIfhnWgq8nAN4k5zFmbwhNfJ/PJz1lkFJTZO6lCCNFmpVnKaOfh3Cqecmo1GmYNbo+vqxOvbU/DUlJh7yQBEqSLFqCs0so3iTn07+BOJ6+W2/dN1J2LXsvQTp48N6Ijq6ZG8OjAQDxddKz+MYuZcaf4fdxhyiul77oQQjQ3e02/2FQ8XHTMHRZEbkklC3amU2m1f/90CdKFw9uWYiGvpJLJ3aUVvS0zuugYF+HDKzeHsHxyOHf0NLErJYe4Yzn2TpoQQrQplVbF+YLWFaQDdDEZ+E10AAfSC/nkcLa9kyNBunBsSim+PJpDqLcLkYFu9k6OcBCBHs7cF+XPsHBfPv4pi6yicnsnSQgh2ozMwnIqrLS6IB1gbBdvRoZ6suZQFofOF9o1LRKkC4d28HwRqXmlTO7uK4MFxRWeGh6OAv61L9PeSRFCiDbDNv1iKwzSNRoNj8a0w8ug47ukPLumRYJ04dC+OGrGx1XPsBBZvEhcqYOXgdt6mNhxOp8f7dziIYQQbcUvQXrrHCdm0Gu5wd+VE+Ziu6ZDgnThsFJzSzmYXsiErt446aQVXVzdrT18CfRwYnlCBuWV9h/oI4QQrV2apQyjiw5PF8daobMxRfi6kp5fTkFppd3SIEG6cFhfHjPjrNMwNsLH3kkRDsxFr2VG/wDOWsr4+rjZ3skRQohW76yllI6tsKvLpbqYDAAkmUvslgYJ0oVDyimuYEuyhdHhXq36l7poHAM7Gonu4M6an7LJlkGkQgjRpFrb9ItXczFIP5Ftvy4vEqQLh/RtYg6VVsUkWbxI1NKM6EAqrIpVBy7YOylCCNFqFZZVkltSSZCxdQfpHs46OhidOJEtLelC2JRWWFl7IpeBHT3o0Mp/qYvG097ozNQevmxLsfBzRpG9kyOEEK1Sa57Z5XJdTK4kSZAuxC82J+eRX1rJZGlFF3V0e08TAe56lidkUOEAq8UJIURr05aC9AiTgeziCszFFXa5vgTpwqFYleLLYzl09jXQI8DV3skRLYyLXsuv+weSmlfKt4myEqkQQjS2NEsZWk3VonKtXYSvffulS5AuHMr+c4WkWcqYIosXiXoa1NGDvu3d+fBQFjl2av0QQojWKi2/jHYeTm1iauRwXwNaDXbr8iJBunAoXxw1Y3LTM6ST0d5JES2URqPhN9GBlFVa+fcBWYlUCCEaU1uY2eUiF72WTl4udhs8KkG6cBinzCX8lFHELd180Gtb/y900XSCPJ2ZfIMvm5MtHM2UQaRCCNEYKq2Kc5ayVrvS6NV0MRlIyi5GqeYf5yRBunAYccfMGPRabu7ibe+kiFZgWm8/TG563t6bQaUMIhVCiAbLKiqn3KraTEs6QFeTK/llVs4XNP8aHBKkC4eQXVTO9hQLN3X2wsNZFi8SDWfQa3m4XwDJOaWsO5Fr7+QIIUSL15ZmdrkowraoUfN3eZEgXTiEb47noICJN/jYOymiFRnSyUhkOzfe//ECuSUyiFQIIRqiLQbpnbxdcNZpSLLDDC/65rjIsmXL2L9/P15eXrz++usA7Nq1i08++YS0tDRefvllOnfubNv/888/Jz4+Hq1Wy/Tp04mKigLg4MGDrFy5EqvVyujRo5kyZQoAmZmZLFq0iPz8fMLDw3nyySfR6/WUl5ezZMkSTp06hdFoZNasWQQEBDRHlkUdFJdbWZeUy6BgY5uY0kk0H41Gw8zoQJ7+Jpn3Dl7gyUHt7Z0kIYRosdIsZbg7a/FyaTtPvPVaDWE+9hk82iwt6SNHjuS5556rti04OJjf//73dO/evdr2s2fPsnPnThYsWMDzzz/Pu+++i9VqxWq18u677/Lcc8+xcOFCduzYwdmzZwFYvXo1EyZMYPHixbi7uxMfHw9AfHw87u7uLF68mAkTJvD+++83R3ZFHcWfyqOwzCqLF4kmEezlwqQbfNl4Mo/jWfaZ61YIIVqDNEsZQUbnNjdFcheTK6dySpp9fFOzBOk9evTAw8Oj2raOHTvSoUOHK/ZNSEhgyJAhODk5ERAQQLt27UhKSiIpKYl27doRGBiIXq9nyJAhJCQkoJTi8OHDDBo0CKj6QZCQkADA3r17GTlyJACDBg3i559/tsvoXFGzSqviy2NmuvkZuMFfFi8STWNabxO+rnreTjgvg0iFEKKe2tL0i5eK8DVQUqE4+7/uPs3F4fqkm81mTCaT7bWvry9ms/mK7SaTCbPZTH5+Pm5ubuh0umr7X34unU6Hm5sb+fn5zZgbcT170go4X1DO5O7Sii6ajpuTjun9AjhpLmVDkgwiFUKIuiout5JdXNE2g3STfVYebZY+6S3Bxo0b2bhxIwDz5s3Dz8+vzufQ6/X1Oq4laKq8fbv5HO09XZgQFWbXudHls2uZ6pK3W00m4lMKeP9QNhP7huLt6tTEqWs4R/zsysrKeOGFF6ioqKCyspJBgwYxbdo0li5dypEjR3BzcwPg8ccfJzQ0FKUUK1eu5MCBA7i4uPDYY48RHh4OwJYtW/jss88AmDp1qu3J56lTp1i6dCllZWX07duX6dOnt7nH60I4mnP5bW/Q6EUdPJ1xc9KSlF3CmM7X37+xOFyQ7uvrS3Z2tu212WzG17eqlfXS7dnZ2fj6+mI0GikqKqKyshKdTldt/4vnMplMVFZWUlRUhNF49ZUsx4wZw5gxY2yvs7Ky6px2Pz+/eh3XEjRF3hKzijl0zsLD/QPINWdf/4AmJJ9dy1TXvE2PMjHrWwtvxh/nsZh2TZiyxlGfz+5q3Qgbk5OTEy+88AIGg4GKigr+/Oc/2wb333///bauhxcdOHCA8+fP8+abb3LixAneeecdXn75ZQoKCvjvf//LvHnzAHjmmWeIjo7Gw8ODFStW8Nvf/paIiAheeeUVDh48SN++fZs0X0KIazubVwrQ4IWMVEkx5Johz4zKNVf9P9cMBXlobpqMplMzRsG1pNVo6OxraPbBow4XpEdHR/Pmm29yyy23kJOTQ3p6Ol26dEEpRXp6OpmZmfj6+rJz506eeuopNBoNPXv2ZPfu3QwdOpQtW7YQHR0NQP/+/dmyZQtdu3Zl9+7d9OzZU1pjHEjcMTNuTlrGdPayd1JEGxHi7cIt3Xz46lgON3XxIsIk4yDqSqPRYDBUPfqtrKyksrLymvXq3r17GT58OBqNhq5du1JYWEhOTg6HDx8mMjLSNl4pMjKSgwcP0rNnT4qLi+natSsAw4cPJyEhQYJ0IewsLb8MDdDeWLunkNbdW+BM8i/BeN7/gvGSq3QZcXYBayXKkodu9l8aNd2NJcJk4MtjZsorrTjpmqe3eLME6YsWLeLIkSPk5+fzyCOPMG3aNDw8PPjXv/6FxWJh3rx5hIaG8vzzzxMcHMzgwYOZM2cOWq2Whx9+GK226mb8+te/5u9//ztWq5VRo0YRHBwMwL333suiRYtYs2YNYWFhxMbGAhAbG8uSJUt48skn8fDwYNasWc2RXVELmQXl7Dydz6QbfHFzajtTOQn7u6u3H9tSLLydkMFrY0PQyg/3OrNarcydO5fz588zduxYIiIi2LBhAx9++CH//e9/6dWrF/feey9OTk6YzeZqXXYujieq6/gjIYR9pVnKCPRwwrkWAaoyX0C9uwD0TuBjAi9fNB3DoFd/8Pateu3lA96mqtcGV9S3n6C+WI1KO40mqFMz5KhuupgMVFghJbe02Rp4miVIryk4Hjhw4FW3T506lalTp16xvV+/fvTr1++K7YGBgbzyyitXbHd2dmbOnDl1TK1oDt8k5gBwSzdZvEg0L3dnHQ/1DWDRrnQ2nszj5i7e9k5Si6PVavnHP/5BYWEh8+fP5/Tp09xzzz14e3tTUVHB22+/TVxcHLfffnuTpUHGEdWd5Lf1a8o8ZxSdIdTkUavzlyQdJg/w/fsynLr2rNX5rbfew4VvP8Zl53d4Pjq3Vsc052cc4+wB28+RXqJncDNd0+G6u4jWr6i8kg1JudzYyRN/d8cfvCdan5FhnmxIyuU/By8wONiIsQ0tzNGY3N3d6dmzJwcPHmTSpElAVZ/1UaNG8dVXXwFVLeSX9qu/OJ7I19eXI0eO2LabzWZ69Ohxxbiki/tfTsYR1Z3kt/VrqjxbleK0uYgbTM61Or/15wOg1ZLr4Y2mDunRxIykePNaSsffgcbD87r7N+dnrFMKLxcdB05nMTyocWOXmsYSOdwUjKL1+y4pj6JyK5O6Syu6sA+NRsPMAYEUllXy/o8X7J2cFsVisVBYWAhUzfRy6NAhgoKCyMmpejqmlCIhIcHWHTE6Oppt27ahlCIxMRE3Nzd8fHyIiorixx9/pKCggIKCAn788UeioqLw8fHB1dWVxMRElFJs27bNNs5ICGEf2UUVlFYqgoy1m9lFpZ6E9sFonOs2yFQzehKUl6G2rqtPMpuURqOhi8nQrNMwSku6aFaVVsXXx8308HeVQXvCrsJ8DIzv6sPaxBxu7uJNuK/B3klqEXJycli6dClWqxWlFIMHD6Z///785S9/wWKxABASEsLMmTMB6Nu3L/v37+epp57C2dmZxx57DAAPDw9uu+02nn32WQBuv/122yDSGTNmsGzZMsrKyoiKipJBo0LY2encqpldOnlfP+hWSkFqEpredf9xrQnqBD2iUFu+RY29FY3esZ62dzW5sv9cIUXllc0ynk6CdNGsdp3JJ7Owghn9A+2dFCG4J9KP71MsvJWQwbybO8kg0loICQnhtddeu2L7Cy+8cNX9NRoNM2bMuOp7sbGxtoH+l+rcuTOvv/56wxIqhGg0qf+bfrGTVy1axnPNkJ8H9ZxKUTtmEtY3/4ratxNNzIh6naOpdDEZUMApcym9At2a/HrS3UU0G6UUXxw1097oRHSQh72TIwQezjoe6OvP8axiNp/Ks3dyhBDCIZ3JK8XHVV+78TunTwKgCannfOc9+0G7INR3cVWt8g6kuVcelSBdNJtjWcWcyC5hYjdfdHZcXVSIS8WGe9HNz8C/D1ygoKzS3skRQgiHczq3jBCv2vZHTwKNFoLD6nUtjVaLZvRESE2Ck8fqdY6m4mXQE+Cub7ZFjSRIF80m7qgZD2cto2XxIuFAtBoNvx3QDktpJR8ealszQQghxPVYleJMXinBteiPDqBOn4J2QWhc6j/ORzM4FtzcsW6Mq/c5mkoXkytJZgnSRSuSnl/G7jMFjIvwwaCXYiccS2dfA+MivPk2MYeUnOZd9lkIIRxZZkE5pZWqdv3RoWrQaH27uvyPxsWAZthY2L8blZ3ZoHM1tghfAxkF5VhKKpr8WhItiWbx9fEcdFr4VVdZOEY4pnv7+OPurOPthAyH6wcphBD2cnHQaEhtZnbJy6kaONrAIB1AEzsBNKDiv2nwuRpTl//1S2+O1nQJ0kWTKyitZOPJXIaFeGJyc6zplIS4yOii44Eof45cKGZrisXeyRFCCIdwJrcMgODa9Em/OGi0njO7XErj64+m/1DU9g2okuabm/x6upgMaKBZ+qVLkC6a3IakXEoqFJNuuHLVJUMXswAAIABJREFUQCEcyZjOXkSYDKzan0lRuQwiFUKI1LxS/N30tZoXXKVWBel0Cm+Ua2tGT4TiQtTOTY1yvsbg5qQjyNNZgnTR8pVXKr4+nkNkoJssFiMcXtUg0kByS2QQqRBCQNX0i7VZxAj+F6QHBqExNM4c4prON0BYV9Smr1BWa6OcszF0MRlIyi5u8q6REqSLJrXjtIXs4gomd5dWdNEyRJhcuamLF18fz7GtsieEEG1RpVVxNq+s9oNGT59s8KDRy2lumgyZ6fDTvkY9b0NEmAzklFSSXdy0g0clSBdNRinFl8fMdPR0pl8Hd3snR4hau7+PP25OWt7eK4NIhRBtV3pBGeVWVauWdJVvAfOFeq80WhNN38Hg44d105eNet6GiDC5Ak3fL12CdNFkfs4s4qS5lMndfWW5ddGieBr03NfHn58zitiemm/v5AghhF3Ub9Bo4/RHv0ij16MZNQGO/og6m9Ko566vMB8XdBpIkiBdtFRxR3PwdNExItTT3kkRos5u7uJNZ18XVsogUiFEM7MqxZHMIiqt9n2Sl5pXigYIrkV3F5WaVPWfRu7uAqAZfjM4O6M2OkZrurNOS4i3C4nZTTvrjATpokmkWcpISCtgfFdvXGTxItEC6bQaZka3w1xcwcc/Zds7OUKINkIpxfKEDJ797rTdB7Cfzi0l0MOpVosQqtMnwb8dGjePRk+Hxt2IZnAs6oetKEtuo5+/PiJMrpzMLsHahF0iJXoSTeLLY2actBp+FeFj76QIUW83+LsyOtyLL4+ZOZsng0iFEE1LKcW7+zJZeyKXAHc9nx3JtusA9tN1mNmF1JONMj96TTSjJ0FFOWrbuia7Rl1EmAwUlltJzy9vsmtIkC4anaWkgvhTeYwI88TbVW/v5AjRIA/09ceg17JcBpEKIZqQUopVBy7w1fEcJnbz4fVxobg561j6w/kmba2tSXml4pyldjO7qMICyMpokq4uF2nad4Re/VFb1qLKmy4wrq2I/608eqIJu7xIkC4a3bqkXMoqFZNl8SLRCngb9NzTx48fzxex84wMIhVCwIXCct7ac57URmrlVkqx+scsvjhqZnyENw/3D8DToOfX/QI4llXMhqTm7+KRnl9GpYJOdRk02oRBOoB2zCT+n707j4+6Ohc//jkzk32yr5CFEMIatoSgLJW9yBVr+VlrF2tblKpXS116VVzq0l4VtQqC2EWR1qu3blexLrggBSyIguwghDVhScgy2ZeZzMz5/TEkgmSZJDOZTPK8Xy9fhm++8/0+3wROnpx5znOoLEdv/cyr93FHamQQgUbl1cWjkqQLj2p0OPngYDk5/cLcf4tMiB7uPwZHkx4VxItfFdNg7zkbagghul9JbSP3ry1gzaEKfrvmOO8fLO/yu2yv7SnjzX1lzM6M5IbxiaizHdGmD4xgdGIoL+0oodzLPbm/rekXELfaLxY07TTq3SSdEWOhXyr603/6/J1No0ExKCbYq20YJUkXHrXxeBXlDQ7ZvEj0KkaDayfS0jo7b+yVRaRC9FVNCXqV1cHvpqUwOimUv247wyMbTlLZ0Lkk+o29pfxjTykzMiL5z4uSzmtZrJTipouSsDk0L3x1xlOP4ZaCSisGBckRbsyk5x+B2ASU2bvd3JRSqFlXQMFROLTPq/dyR2ZsMEfLG7zWhUeSdOExWmveOVDOgKggxiR5ZktgIXqKEQmhTBsYweqvyzhVZfN1OEKIblZa902C/tCMVHKTzfxuWgoLxiWwo7COW98/xo7C2g5d8+39Zby8q5Qp6RH8+uKkFvcUSY4I5IcjY/l3fjVfnarx1OO0q6DSSr/wQAKNbnR2yT8CHu6P3ho1YRqYw3G20o5Ra42uLEcfOYDzy404P3gD5/+swLH8D+idX3g0lsExwdgcmgIvNRaQVX3CY3YV1ZFfYeU3E5Ka36oTojf5ZXYCX56s4YVtZ3hgeor8PReijyita+S+TwqobHDw8MxUhsa5dpxUSvG9YTGMSgzlj5tO89C6E3x/WDTXjo0noJ3k9t0DFv62o4TJaeHcNrEfRkPr48mVI2LZeLyKP28tYnlihlstEbuqoMLGgKj2Z9F1XS0Un0ZNmuH1mABUYBBqyhz0mjepX/suzqLTUFaMLi12LV4tK4bGb02khEeCwYhz3+MYbnsINWy0R2I5d+fRgdHBHrnmuSRJFx7zztcWooKNTJHNi0QvFR1i4iej41j5VTFfnKxhQmq4r0MSQnhZ2dkZ9G8n6OdKjw7mqTnprNpezDsHytl9po7fTu7f6iZAa/LKeeGrYiakmrljcv82E3SAAKPilouTmnunz89J8MiztcbmcFJUY+OSdDfGuBPHALzafvHb1LTL0B+/TdWKx1wHQs0Qlwj9U1Gjc12lN7GJrmOx8ajgEHRtDc4nFuF87lEMdy1GpaR3OY5+4QGEBRo4XNbA7MwuX+4CkqQLjyiosLK9sJZrRse1O3sghD+7bEg0nxyuYOVXZ8juFyabdQnRi5XVNXLf2gIq6l0lLi0l6E2CTAZuuiiJ7P5hLN9SxB1rjnP9uAQuzYw67123jw9X8OetZxifHMZ/TU7G1E6C3mREQiizM137NkxNjyAjxvMzt01OVtpwatxrv9i802j3lLsAqOhYDA8sIyrcTIUhABUa1v5rwswYbn0Q52N34nzmYQz3PIGKie9aHEqRGRPstTaM8tNFeMQ7BywEGhVzBkf5OhQhvMpkUNw4PoniWjtv7pNFpEL0Vk0z6OX1Dh6ckcKw+NYT9HNdnBLOM5elMzw+hD99eYbHNp6iyuoAYN3RSp77ooicfmHcfUkyAcaOlcz9YmwC4UFGnvuyyGuLFYHmGmu3urQVHIGoWFRE925eqPqlEJCe6VaC3vyamHgMtz4I1nqczzyMrut6jf/g2BDyK6zYHJ7v/CVJuuiyino7G45VMSMjkohgeXNG9H4jE0OZMiCCt/dbKKyWRaRC9DauBP0ElnoHD81IYXh8x5ohxIYG8NCMVObnxPPV6Rpuff8Yr+wqYfmWQkYnhbJoSnKn3nU2BxlZMC6RQ2UNrDlU3uHXu6ugworJAP3D3ahJzz/i1U2MPE2lDMRw871w5jTOFY+iv12/3kGZscE4NBwr9/ziUUnSRZd9cKicRqfme8O697doIXzplznxGA2Kld3cFk0I4V2WevvZBN3OQ9M7nqA3MSjFvOGxPHFpOiEBBl7fW8aIhFDum5rSpTK5SwaEk90vjP/ZWUppnXd23iyotNE/PLDdUhzdUA9nTnVrPbonqGGjUfNvhby96BeXop2dnwX35s6jkqSLLrHanazJq2B8spmUCNm8SPQdsaEB/HhULFtP1bL1ZPe1RRNCeI8rQS/AUt/Ig9NTGJ7Q9XbCg2KCefo/0rl1Yj/u72KCDq466P+8KBGn1jy/zTuTBAWVVvdKXU4cA61RA7ywatLLDBdPRV01H73t3+g3VnX6OrEhJqKDjRwq9fymRpKkiy7ZcLyKKquD7w+XWXTR91w+NIaUiEBe+OqMV+oRhRDdp7zezu/WFlBW18iD01MZ4YEEvUmwycCMjEhCAjyTdiWaA/nxqDi2nKjhixPVHrlmkwa7kzM1je4tGm3aabQbF416kpo9DzXze+i17+D85J3OXUMpMmNDOGSRJF30IE6teedrCxnRQYz04GAmhL8IMCpuGJ9IUU0jb+23+DocIUQnVVkd3L+2gNK6Rh7wcILuLd8fHkN6VBB/2XaGukaHx657oiOLRvMPQ2Q0KirWY/fvTkop1NXXQc4k9OsrcW79rFPXGRIbzKkqG7U2z30fQJJ00QXbT9dyssrG94fHyKYuos8akxTG5LRw/m9fGWdqZBGpEP5o1fZiCqttPDAtlSw/SNDB1Wnq5ouTsNTZeWVXqceuW1BxNkl3ayb9KPhZPfq3KYMRw4I7YPAI9ItL0Af3dPgamWfr0o94eDZdknTRae8csBAbYmJymmxeJPq2+TkJKGDlV8W+DkUI0UF7ztSy7mgl84bHkJXoHwl6k6FxIcwZHMX7B8s9tnCxoNJGgEGRZA5o8zxttcLpEyg/6uzSGhUQiOGW+yC+n6vjy6n8Dr0+85ydRz1JknTRKUctDewuqmPu0OgO93kVoreJDwvg6lFxfHGyhu2nZRGpEP6i0eHkT1+eIdEcwI9Gxfk6nE65dmw8USEmVnxRhN0DvdMLKqykRAa2uwsqJ4+BdvpdZ5fWqLBwDLc+BIFBrh7qFvffnYgIMtI/PJDKBrtHY5IkXXTKPw9YCDYpLs2UzYuEAPj+sGj6hwfw121naJRFpEL4hbf2WzhVZeOm8Yl+u3twWKCRX+UmcKzcytqDJV2+XkGl1f1SF/CrHuntUbFnNzuqr8W5rGObHT17+UCuG5fo0Xj882+k8KmyukY+y69i5qAozEFGX4cjRI8QYDTwq9xECqsbWf21LCIVoqc7XWXjjb1lTE4LJ6e/2dfhdMmk1HDiQk2sO9S12vRam4PSOrv7i0bNERDtn+9AtEalnt3sqOgk+t1X3X5du+88dIIk6aLDPsirwOGE7w2VtotCnCunv5kJqWZe31tGSa13NhkRQnSd1po/bS0iwKhYkOvZ2U9fUEoxMS2cLwvKu9Tp5USla/F7WqQbO40WHIG0Qb2ycYQaPgZGZKP3fOXTOCRJFx3SYHfy4aFyJqSa6efGdsFC9DXX57h+4L+4XRaRCtFTbThexe6iOn42Jp6YEJOvw/GIyanhNDp0lzZXKzjbfnFAOzPputEGpwt6xaLR1qgRY+HMKXSp73aVliRddMi6o5XU2Jx8f1iMr0MRokdKMAfww6xYNhdUs7Ow1tfhCCG+pcbq4MXtxQyODWbO4N6zrmpofAixYYF83oXNjQoqrAQZFfFhbXd24VQ+OBy9O0nPygZA79/psxgkSRduczg1/zxgYXBsMMPiQ3wdjhA91rwRMSSZmxaRdr3bghDCc17aWUK11cHNFyV5pY7YVwxKMS0zlq9O11Lf2LnF6wWVVtKigjC0U8Ki88/uNNpLOru0KCkFouPQ+3f4LARJ0oXbtp2qobC6kXmyeZEQbQo8u4j0VJWNdw/IIlIheoqvS+r46HAF3xsaTUZMsK/D8bhpmbHYHLrTrWALKqykutHZhYIjEGqGOP+v52+NUspV8vL1LrTTszuJukuSdOG2dw5YSAgzMTE13NehCNHj5SabGZ9s5rW9pZTWySJSIbrK1sXWpnan5k9fnCEu1MRPRsd7KKqeZUz/SCKDjGwq6HjJS5XVQXmDw71Fo/lHYEDvXDR6nqxsqKuF44d9cntJ0oVbvj5Tzb7iei4fGtOr3h4UwpsWjEvA4YS/ySJSITqtrK6RJz47xY9ey+PvO4qx2juXrL/ztYX8Sis3jE8kJKB3pj9Gg2JCajhfna7p8NfpRIWbi0btjXDqOCoto9Nx+gs1bAwo5bOSl975t1R43GvbTxNiMvDdzEhfhyKE30gKD+QHWTF8ll/N7iJZRCpERzicmncPWLjl3WN8ebKG7H5hvLXfwm0fHGNfcV2HrnWmxsare0q5OMXMxSm9+93gSWnhNNg1Ozq4cL2ps0u75S6nC8BuhwGZnQ3Rb6jwCEgbhN7nm8WjkqSLdpXUNrLuUAmzMyMJDZDNi4ToiCtHxJIQ5lpE6oktu4XoCw6V1XPnR8d54atihseHsPzygTwwPZXfz0zFoeHeTwr4y9Yit3qCa635y9YzGJTiV72gJ3p7RiaGEh5oYHMHS14KKq2EBhiIC227JWXTolHVmxeNnkNlZcPRA+j6jv1i6AmSpIs2VVkdPL3pNACXD5W2i0J0VJDJwIJxCZyotPH+wXJfhyNEj1Zjc/DnL4u488N8LPUO7vpOfx6YntK8L8eYpDCWzR3I94ZGsyavgt+8d6zdRZKbT1Tz1elafjo6rv3Wgr2AyaC4ODWcradqaOxAHX/TotF268wLjkBIKMQndTFS/6BGZIPTCQd3d/u9JUkXrTpdZePuj46TV9bAA5cOJcHc+wc3IbzhohQz4/qH8Y/dpVjq7b4OR4geR2vNxuNV3PLuUT46XMHlQ6N57nsDmTwg4oKkMdhkYEFuIo/NTiPIZODhf53kmc9PU229cFa91ubg+W3FDIwO4vI+tEv2pNRw6hqd7Cpyb/ZXa01+pY0BUW4uGk3NQBn6SAo5aCgEBfuk5KWPfIVFR+07U8ddHx2nxubkv2emMmto71wJL0R3UGffZm90av4ui0iFOM/pKhsPrjvBU5tOEx8WwB/npLMgN7Hd8srh8aEsuSydH2bFsv5YFb9+7yiff6vE45VdJVTU27nl4t7VE709o5PCCAswuN3lpbLBQbXVQVo79eja4YCTx3v1JkbfpkwBMHSUTxaP9o69cIVH/etoJc9+UUiiOZDfTfvmbUYhROf1Cw/k/w2P4Y19ZcweHEVWQqivQ+oUm83Ggw8+iN1ux+FwMGHCBK6++mqKi4tZunQp1dXVZGRksHDhQkwmE42NjTz77LMcPXqU8PBwbrvtNhISEgB4++23WbduHQaDgfnz5zN27FgAdu7cyapVq3A6ncycOZN58+b58pGFl9gcTv5vXxlv7rMQZFTcOD6RSzOjOpRMBxoN/GxsPJPSwlm2pZDFn51iUlo4N+YmUlJUzQd5FVw2JIrBsX1rA74Ao2J8ipkvT1ZjdyZhaudr6vai0cIT0Gjr3ZsYtUCNyEbv3oouKUJ1Y5mPzKSLZlprXtlVwtLPCxkeH8oTswdIgi6EB/1wZCzxoSb+svUMDj9dRBoQEMCDDz7Ik08+yRNPPMHOnTvJy8vj5ZdfZu7cuSxfvpywsDDWrVsHwLp16wgLC2P58uXMnTuXV155BYCTJ0+yefNmnn76ae677z5WrlyJ0+nE6XSycuVK7r33XpYsWcKmTZs4efKkLx9ZeEFJbSO/ef8Yr+4pY1JaOCu+l8FlQ6I7PdudERPMH+ekc+2YeL48WcOv3zvKQx8eJCrExDVj+uY7wZPSwqmxOdlzpv2Sl6Ykvd32i02LRvtAZ5dzqSzXBILe370lL5KkC8A1o/H0pkJe31vGrEGRPDg9FXOQdHIRwpOCTAauG5dAfoWVD/L8cxGpUorgYNdOjQ6HA4fDgVKKffv2MWHCBACmTZvG1q1bAdi2bRvTpk0DYMKECezduxetNVu3bmXSpEkEBASQkJBAUlIShw8f5vDhwyQlJZGYmIjJZGLSpEnN1xK9x6aCKgqrG3lwegq/ndyf6JCuv7FvMiiuGhnLM5elkxwRxMnKBn6Vm0BYYN/8WZbdL4xgk4HNBVXtnltQYSM80EBUcDtfq4IjEBQMif08FKWfSEyGmPhuL3mRchdBZYOdRzec4kBpPdeOjecHI2J6/y5iQvjIxNRwxiaF8r+7S7lkQARRHkhOupvT6eTuu++mqKiISy+9lMTEREJDQzEaXT/gY2JisFgsAFgsFmJjYwEwGo2EhoZSXV2NxWJh8ODBzdc89zVN5zd9fOjQoe56NNFN8itsRAcbyelv9vi1UyKDePS7adgCzIQ4/HN/Aq01HD/kWqBp6twYEWg0MD45jC9O1HDTeN3muxQFlVbSotrv7KLzD59dNNq3fvFRSqGystHbNqEdDpSxe57f/346CI86WWnlD+tPYqm3c9d3+jN5QISvQxKiV1NK8avxidz6/jH+vrOYWyf293VIHWYwGHjyySepra3lj3/8I6dPn+72GNauXcvatWsBWLx4MXFxcR2+hslk6tTr/FVPet7TNScZFB/u1XhMJhN2u//VomutqV65hPr33yRw7EVE3vkIhtAwt1777e/xpVnwWf4BTloDGJca1er9TlQe4rtD49v8fmiHg+KTxwmZ9T0iesjfo+78O91w8RQqP/uYyPJiAoeN6pZ7SpLeh+0uqmXxZ6cwGRT/PSuNoXH+N5gJ4Y9SIoK4YlgMb+23MDsziuHx/rmINCwsjKysLPLy8qirq8PhcGA0GrFYLMTEuPZViImJoaysjNjYWBwOB3V1dYSHhzcfb3Lua849XlZW1nz8XLNmzWLWrFnNfy4tLe1w/HFxcZ16nb/qKc/rcGqOltUyZ3CUV+PpKc/bEdrpRP/vn9EbPoRRudj2fEXJ3TdguPUBVFRsu6//9jMPCXcSZFSs2XOSASEtt38tq2ukxuYgIVi3+fXSpwvA2kBDQjK2HvJ17c7vsU4ZCEpRsXk9hjjPlvv079/yZI3UpPdRa49U8NC6E8SEmHjy0gGSoAvRza4eGUdsqIm/+tki0qqqKmprXSUENpuN3bt3k5ycTFZWFlu2bAFg/fr15ObmAjBu3DjWr18PwJYtW8jKykIpRW5uLps3b6axsZHi4mIKCwvJzMxk0KBBFBYWUlxcjN1uZ/Pmzc3XEr1DcW0jNodud5FiX6OdDvRLz6I3fIia8wMMC3+HYeEDUFKE87E70acKOnzNIJOBnP5mtpyoxqlbHmfyK1yLRtttv1jQtGi0b3V2aaLCwiF9cLfWpctMeh/j1JqXd5bwf/stjE0K5a5LkvvsohohfCkkwMB1OQk8+e/TfHS4gsuG+MdGK+Xl5axYsQKn04nWmokTJzJu3DhSUlJYunQpr776KgMHDmTGjBkAzJgxg2effZaFCxdiNpu57bbbAEhNTWXixInccccdGAwGrr/+egxnN0e57rrreOSRR3A6nUyfPp3U1FSfPa/wPHeTwr5EOx3oVcvQW/6FuvxHqCt+6qoPz8rGcNdjOJf9Hufjd2O4+R7UsNEduvaktHA+P1HNgZJ6RrTQ+vVEpQ2AtMh2urnlH4HAQEhK6dD9exM1Yix6zZvouhpUqOfXU3ybJOl9iNXuZOnnhWwuqObSzChuGJ/Ybu9UIYT3TE4L56PEUF7eVcLktHAig3v+kDxgwACeeOKJC44nJiby2GOPXXA8MDCQO+64o8VrXXnllVx55ZUXHM/JySEnJ6frwYoeqaDCzZ7cfYS229EvLkFv/Qz1/Z9iuPzH531epWVguOdJnMsexrn0IdQvf4NhwjS3r5+bHEaAQbG5oLrFJL2g0kpUsJGIdsYfXXAEUgZ226LJnkiNyEa//zoc2AM5E71+Pyl36SMq6u3ct7aAzwuqmZ8Tz39eJAm6EL7WtIi0odHJSztLfB2OEN0iv9JKojmAkABJQbS9Eefzf3Ql6Ff+4oIEvYmKjcdw92LIHI5e+TTOD95wdYBxQ2iAkez+YWxupeQlv8LafqmL0wkFR/tsqUuzjKEQFNJtJS/yL6QPKKiwcudHxymosLJoSjLzhsdKi0Uheoi0yCC+NyyGtUcqySut93U4QnhdgRtJYV+gGxtx/vlx2L4ZdfX1GP7jB22er0LNGG59CHXxVPTb/4N++U9oh8Ote01KDaeszs6hsobzjju15kSljbT21gcUnoCGehgwuO3zejllMsGwUd22qZEk6b3cjsJa7v44n0aH5tHvDmBCarivQxJCfMuPRsUSHeLfO5EK4Y5Gh+ZUla3PLxrVjTaczz0Ku75E/fRGDN/9vluvUwEBqOtuR/3HVeiNH+Jc8Qi6of1f7senmDEZYHNB9XnHS2obabA7259JP7DHdf+hI92KszdTWdlQUoQuLvT6vSRJ78U+PFTO7/91goSwAJ6ck05mbLCvQxJCtCA0wMj87HgOWxpYe6TS1+EI4TWnq204tBuLFHsxbbXifPa/Yd921LW3YJg+t0OvVwYDhit/jvrZzbB3O84/3oeubHsHY3OgkTFJYWwuqD6vTKZ50WhU298PfXA3xCag4hI7FGtvpEZkA3RLyYsk6b2Qw6lZtb2YP315hux+YTw2O434sABfhyWEaMOU9AiyEkL4n53FVFndewtbCH/T1Nmlr86k64Z6nMt/D1/vQv3iNximXNrpaxmmzsHw6/ug8ISrRWPhyTbPn5QWTnFtI0fLrc3H8t1YxKudTji4F9VNG/j0eAn9IDYBvc/7JS+SpPcyDXYnj392itVfW5g7JIr7pqYQGtB3V2IL4S+UUtyQm0hto5OXZRGp6KUKKqwYFSRH9L0kXTfU4XzmYcjbh7rudgyTZ3b5mmr0eAx3Pgo2K87Fd2E/ld/quRelhGNQ55e8FFRaiQ0xYW6rFfPJY1BXAx1s/dhbKaVcJS8Hd6PtLW8Q5Snd0u/rueeeY/v27URGRvLUU08BUFNTw5IlSygpKSE+Pp7bb78ds9nMvn37eOKJJ0hISADg4osv5qqrrgJg586drFq1CqfTycyZM5k3bx4AxcXFLF26lOrqajIyMli4cCEmk4nGxkaeffZZjh49Snh4OLfddlvzdXujsrpGHtlwimPlDSwYl8D3hl24S58QoudKjw5m7pBo3jtYzuzMKHrIzttCeEx+pZX+EYEEGPtO8wKtNRw9iPO1FyD/MOpX/4Vh/Hc8dn2VPtjVovH+m2j41xqYc1WL50UEGRmdGMrmgip+NiYOpRQnKq3tLhr9ph5dkvQmakQ2euNHcDwPMkd47T7dMpM+bdo07r333vOOrV69mlGjRrFs2TJGjRrF6tWrmz83fPhwnnzySZ588snmBN3pdLJy5UruvfdelixZwqZNmzh50vXWzssvv8zcuXNZvnw5YWFhrFu3DoB169YRFhbG8uXLmTt3Lq+88kp3PK5PHCtv4M6P8jlVZeXeKSmSoAvhp34yOo7IYCN/2VrU6g6BQvirvtTZRVeU4VzzJs4Hbsa5+C44XYDhxrs9mqA3UfFJMGgY1h1ftHnexLRwTlc3kl9hxeE829mlnfUB+sBuSOiPio71ZMj+bdhoUAavl7x0S5I+YsQIzObzd2baunUrU6dOBWDq1Kls3bq1zWscPnyYpKQkEhMTMZlMTJo0ia1bt6K1Zt++fUyYMAFw/ULQdK1t27Yxbdo0ACZMmMDevXvd7ivqT7adqmHRxwWg4bHvDmB8ivd3wRJCeEdYoJFfZCeQV9bAmq+LfR2OEB7TYHdSVNPYq+uLZssuAAAgAElEQVTRdWMjetu/cTzzMM67rke/9RKYI1G/WIjhj39DeXEDHJWVg/3owTYXkU5oKnk5UU1xbSM2h25zJl07HHBon9Sjf4sKM0PGEK8vHvXZ9naVlZVER7u2wY6KiqKy8puOBnl5edx5551ER0dz7bXXkpqaisViITb2m9/iYmNjOXToENXV1YSGhmI8uwNWTEwMFosF4LzXGI1GQkNDqa6uJiIiorse0+veP1jOC1+dIT0qiPunpRAbKgtEhfB30wZGUFFv5zsDY2islW4vonc4UelapNhuT24/o7WGgiPoTWvRX2x01W9Hx6H+4weoSTNRif27JQ41ahx69cvofTtQk2a0eE5UiIkRCaFsLqgmI9rV8a3NdzYKjrj6o0s9+gXUiLHo915H19a4knYv6BF7UCulmjfXGThwIM899xzBwcFs376dJ598kmXLlnk9hrVr17J27VoAFi9eTFwnikFNJlOnXtcZDqdm+WdHeWPnGb6TEcODlw4ltK2FH13Unc/mC735+eTZ/NMNU+MxmUzYQ+QXb9E7NHd26SXlLrq6Er1lPXrTWjiVD6YAVPYE1ORZMHw0ytDNTRtSBmKIikHv/QpaSdLBtbHRX7edaV5A2mZnF+mP3io1Ihv97qtwYDeMm+SVe/gsSY+MjKS8vJzo6GjKy8ubZ7dDQ0Obz8nJyWHlypVUVVURExNDWVlZ8+fKysqIiYkhPDycuro6HA4HRqMRi8VCTIyrHrvpNbGxsTgcDurq6ggPb3kzn1mzZjFr1qzmP5eWlnb4meLi4jr1uo6qa3Tw1L9Ps+10LVcMi+aX2fHUVZVT58V7dtez+Upvfj55Nv/Vmefr3797Zu2E6KiCCiuBRkWi2f9/8dR5+3AueQDsjZA+GHXNTajxU7w2o+oOZTAQkD2Bhi8/Qzsdrf6SMCHVzF+3neGz/CoSwgIICWi98lkf2A39UlER0d4K238NHAIhoej9O1BeStJ91oIxNzeXDRs2ALBhwwbGjx8PQEVFRXPd+OHDh3E6nYSHhzNo0CAKCwspLi7GbrezefNmcnNzUUqRlZXFli1bAFi/fj25ubkAjBs3jvXr1wOwZcsWsrKymmfs/VVpXSP3flLA9sJabhqfyPXjEjEa/PuZhBBC9H75lTZSIwP9/meWtlpx/n0ZRMVgeGg5xvuewjDtMp8m6E2Csi+G2mo4dqjVc2JDAxgeH4KznU2ltL0RDu9HSalLi5TRCMNGo/ft8Np6x26ZSV+6dCn79++nurqam266iauvvpp58+axZMkS1q1b19yCEVzJ9Mcff4zRaCQwMJDbbrsNpRRGo5HrrruORx55BKfTyfTp00lNTQXgmmuuYenSpbz66qsMHDiQGTNcb/PMmDGDZ599loULF2I2m7ntttu643G95oilgf9ef5L6Rie/m5ZCTn/fDwhCCCGEOwoqrIxJCm3/xB5O//N/obgQwx1/QCUP8HU45wkcc9HZriPbUYOGtXrepLRwvi6pb3t9wPFDYLPKotE2qBHZ6B1b4MxpSEr2+PW7JUlvLTl+4IEHLjg2Z84c5syZ0+L5OTk55OTkXHA8MTGRxx577ILjgYGB3HHHHR2Mtmf64kQ1T206TUSQkcWz00g/u+BDCCGE6OmqrQ4s9Xa/XzSqj+WhP3kHdcls1PAxvg7nAoaISBg4GL13O1zx01bPm5QWziu7SslKaP2XJn1gDygFQ6QevTUqKxsNrpIXLyTpsuNoD6e15p2vLTy28RRpUUE8OSddEnQhhBB+peDsotF0P07SdWMjzr8tg8ho1FXzfR1Oq9TIcXD8ELq6qtVz4kIDeOWHg8lNbv0deX1gNySno8y9pyOep6n4JIhPQu/3Tr90SdJ7MIdT85etZ3hxezETUsN5ZFYa0SE9oiGPEEII4bb8XtB+UX/whmtDomtvRoWG+TqcVqmROaB1uz28TW2sDdCNNjhyQOrR3aCysuHAHlcNv4dJkt5D1TU6+MP6k6w5VMGVI2K465L+BJnk2yWEEML/FFRYCQswEOunE036xDH0mjdQE6ahRo/3dThtG5AJ5gjYu73z1zh6EOyNUo/uBjUiG6z1rq+Zh0nW1wMV1zSy6KMCdhfVcsvFSfwiOwGDn3elEUII0XflV1hJiwryyw5r2uFwlbmEmlE/WuDrcNqlDAbXgsZ929FOZ6euoQ/sBmWAwVkejq4XGjoKDAb0Ps+XvEiS3sMcKqvnzo+OU1rXyAPTU5mdGeXrkIQQQohO01pTUGlte2fLHkx//DYUHMFwzU3+U589KgeqK+HE0U69XB/YAwMG9eiynp5ChYZBxtB2y4s6Q5L0HmRzQRX3flJAoNHA4ksHMLaf/OMQQgjh3yz1dmpsTgb4YT26LjqJ/uc/IGciatxkX4fjNjUiGwC956sOv1ZbrXAsDzVUSl3cpUZkQ/5hdE3ri3U7Q5L0HkBrzVv7ynj8s9MMjA7iyTkD/HbGQQghhDhXQaUNgLSo1jfO6Ym082yZS2AQhp/e5OtwOkRFRMGATPS+TtSlH9kPDrvUo3eAGjHWtVj3690eva4k6T5md2pWfFHE33eW8J0B4fxhZhpRwf65sEYIIYT4tqb2i/42+aT/9YGrw8mPFqAio30dToepkTlw5CC6tqZDr9MHdoPRCJkjvBRZL5Q+GELDwMMlL5Kk+1CNzcHD/zrBJ0cq+WFWLL+dLB1chBBC9C75FVaigo1E+tEElC4pQr/1Eowch5o43dfhdIoaOQ60E77u2IJGfWAPpA9GBYd4KbLeRxmNGG64C3X5jzx6XckIfeRMjY27P8pnf3Edt07sx8/GxksHFyGEEL1OfoXVr+rRtdY4/2cFGAyunuj++rN54BAIDUPvdb8uXdfXQf5h1FDpj95RKisbFZvg0WtKku4DB0rqufPDfCoa7Dw0I5UZGZG+DkkIIYTwOGdTZxd/StL//Ql8vQt11XxUTLyvw+k0ZTS6WjHu3YHW2r0XHdoHTqfUo/cQkqR3s8+OV3H/2gJCAgw8fukARiVKBxchhBC905maRmwOzQA/qUfX5WXoN16EoaNQl8z2dThdNzIHKi1w8rhbp+uDe8BkgkHDvBuXcIv/FIj5Oa01b+wr45VdpYyID+GeKclE+FF9nhBCCNFRzYtG/WAmXWuN8+XnwGHH8PNfowz+P4+psnLQgN67HZU6sN3z9YE9kDEMFdjzv199gf//DfQDjQ7Nsi2FvLKrlKnpEfx+Zqok6EIIIXq9/EpXkp4a2fPbL+ovN8Lurah516IS+vk6HI9QUTGQMtCtunRdWwMnjkp/9B5EMkUvq7Y6WLzxJHuL6/nJqDh+NCrWfxehCCGEEB1QUGElISyA0ACjr0Npk64qR7/6V8gYipp5ua/D8Sg1Kgf98Wp0fR0qJLT1E/P2gtZSj96DyEy6FxVW27jro+McKG3g9kn9+PHoOEnQhRBC9BkFFTYG9PBNjLTTgfP5p8BqxfDL36AMPfsXio5SWePA4YCvd7V5nj64BwIDYeDQbopMtEeSdC/ZV1zHnR8ep9rm5A8zU5k2UDq4CCGE6DsaHZqTVdYev4mR/uc/4MBu1DX/ieqX6utwPG/QMAgOaXf3UX1gNwwajgoI6KbARHuk3MUL1h+rZPmWIhLCAnhgegr9wnv2LIIQQgjhaYXVNhy6Zy8a1Xu+Qr//OmryLAyTZ/o6HK9QJhMMH4Pe+xVa6xbf0dfVlXAqHzX+Eh9EKFrjVpL+73//m/T0dFJSUjh9+jR/+ctfMBgMLFiwgOTkZG/H6De01vxjdwmv7iljZGIoiy5JJjyod71tJoTwbzKei+5y/GxnF09sZKSdTmi0oYKCu3yt5muWleBc+TSkpKN+eqPHrtsTqZHj0Du2QOEJ6J924QkH97jOGyabGPUkbpW7vPbaa5jNZgBeeuklBg0axPDhw3nhhRe8Gpw/sTmcPPxRHq/uKWNGRiQPTU+VBF0I0ePIeC66S0GFFYOClIiOvZustUYXF+Lc+hnON1bh+ON9OG/9ieu/zz72SGza3ojzL4+72i3etKjXtxxUI3MAWu3yog/ugaAQGJDZnWGJdrg1k15VVUVUVBQ2m42DBw/y29/+FqPRyPXXX+/t+PxCo0Pz4Kcn2F9Sz8/GxHFVlnRwEUL0TDKei+5SUGmlf3ggAcbW5wO11mApgeOH0fmH0McPQ/5hqKt1nWAKgNSBqInT0UWn0C89i7O+FsPs/9el2PSbf4Njea4EPbF/l67lD1RMPPRPQ+/dDi187fSBPTB4hKs0RvQYbn03IiIiKCoqoqCggEGDBhEQEIDVavV2bH4jwKgYkxTGj3LTGBsjybkQoueS8Vx0l/wKK4NiWi5P0aVncP7vX+D4IaiudB00GiF5ACr3OzAgE5WeCf3TUCbXQkZtb0S/8DT6jVU4a2tR867p1ISY3vZv9KfvomZdgRo3qbOP53fUyBz0uvfQDfWo4JDm47qiDIpOor4zy4fRiZa4laT/4Ac/4O6778ZgMHD77bcDsGfPHgYMGODV4PzJj0fHERcXR2lpqa9DEUKIVsl4LrpDg93JmZpGpme03NlMf7EB9mxDTZoJ6YNR6Zmu2vCA1ktjlCkAbvgveDkM/cHrUF8DP76hQzuD6qJTOP++3NUP/Qe/6Ohj+TU1chz649VwcC+MGd98XB/c6/q81KP3OG4l6dOmTWPixIkABAW56rYGDx7Mbbfd5r3IhBBCeJyM56I7nKi0ooEBrbRf1McPQUJ/DPNv7dB1lcEI194CIaGuhLO+Dn55K8rY/howbbXi/PNiMJkw3HhX8wx9n5E5AoKC0Xu/Qp2TpHNwD4SGQepA38UmWuR28ZHdbmf79u2Ul5cTHR1NdnZ28+IjIYQQ/kPGc+FtBWc7u7TUflFrDcfyUMPHdOraSim4aj6EmtGrX0Y31GO44c42Z+EB9D/+DKcLMPzmQVeNdh+jAgJg2OgLWjHqA7thcFav28SpN3DrPaK9e/dyyy23sGbNGg4fPsyHH37Ir3/9a/bs2ePt+IQQQniQjOeiOxRU2ggwKJLMLcxWW0qhshwGDun09ZVSGOZe7WqduPMLnMt+j26oa/V8578/QW/6FDX36uZOJ32RysqB0jNw5jTgakNJSZGUuvRQbs2kr1y5khtuuIFJk75ZYPH555+zcuVKli5d6rXghBBCeJaM56I75FdYSY0MxGhoYWHnsYMAKA9sP2+YPhdncCj6b8/gfPoBDLc+iAoLP+8cfeIY+n//AsPHoL734y7f05+pkTloQO/bjkpKRh/c7To+bJRvAxMtcmsmvby8nAkTJpx37KKLLqKiosIrQQkhhPAOGc9FdyiosLa606g+lgcmE6Ske+RehonTMfznIjhxFOeT96IrLN/cq67WVYceZsaw4Ld9vqRDxSdBYvI3/dIP7AFzOPSXheM9kVtJ+pQpU/jwww/PO/bxxx8zZcoUrwQlhBDCO2Q8F95WY3VQVm9vdadRfTQPUjNcNdIeosZOwPCbB6H0DM4nFqFLitBauzq5lJ7BcMNdqIgoj93Pn6mROXBwL9pmdc2kDx3VoQ45ovu4Ve5y7NgxPvnkE/75z38SExODxWKhsrKSwYMH8+CDDzaf9/DDD3stUCGEEF0n47nwtvxK16LRljq7aIcDCg6jLrnU4/dVw8dguOMPOJ95GOfji6iZ8l3Yvhl11XzU4BEev5+/UiNz0J++i960FiylqDlX+Tok0Qq3kvSZM2cyc+ZMb8cihBDCy7o6npeWlrJixQoqKipQSjFr1iwuu+wyXn/9dT799FMiIiIA+MlPfkJOjmuB3ttvv826deswGAzMnz+fsWPHArBz505WrVqF0+lk5syZzJs3D4Di4mKWLl1KdXU1GRkZLFy4EJPshOg32urswql8sNm6tGi0LSpjKIY7H8W59EHq3n0Nxk5AzZ7nlXv5rSEjISAQ/e6rgNSj92Ru90kXQgjh/7o6nhuNRq699loyMjKor69n0aJFjB7t6gwxd+5crrjiivPOP3nyJJs3b+bpp5+mvLycP/zhDzzzzDOAaxHr/fffT2xsLPfccw+5ubmkpKTw8ssvM3fuXCZPnsxf//pX1q1bx+zZs7sUt+g++RVWQgMMxIVemGLoY3kAKC8l6QAqJR3DXYsJ3vYZDdMu69SupL2ZCgyCoSNh73aIjIakFF+HJFrRapK+cePG5hrFdevWtXqBGTNmeD4qIYQQHuPJ8Tw6Opro6GgAQkJCSE5OxmKxtHr+1q1bmTRpEgEBASQkJJCUlMThw4cBSEpKIjExEYBJkyaxdetWkpOT2bdvH7fe6trkZtq0abzxxhuSpPuRgkoraZFBLSfHxw6COQLik7wag0roR/jPb8Yqu4C3SI0ch967HTV0lPwS04O1mqRv2rSpeVD/7LPPWr2AJOlCCNGzeWs8Ly4u5tixY2RmZnLgwAE++ugjNm7cSEZGBj//+c8xm81YLBYGDx7c/JqmOniA2NjY5uOxsbEcOnSI6upqQkNDMZ7dQfLc80XPp7WmoMLKpLSIlj9/NA8GDpHE0MfUqFz0Gy/CyHG+DkW0odUk/Z577gFc/+Buuukm4uLimgdNIYQQ/sMb43lDQwNPPfUUv/zlLwkNDWX27NlcdZVrAdprr73GSy+9xM0339zl2Fuzdu1a1q5dC8DixYuJi4vr8DVMJlOnXuevuuN5S2ttVNucDE+OueBezrpaSopOEjZ1NuZu+Lr3te8vdOCZ4+Jw/PlNDLEJfv0LU2//Hrdbk66U4r/+67/4+9//3h3xCCGE8BJPjed2u52nnnqKSy65hIsvvhiAqKhv2tvNnDmTxx9/HHDNhJeVlTV/zmKxEBMTA3De8bKyMmJiYggPD6eurg6Hw4HRaDzv/HPNmjWLWbNmNf+5tBNlDXFxcZ16nb/qjufdWVgLQKyp8YJ76a93gdbUJ6bQ0A1f9772/YWOPrMRzvk36I96y/e4f//+LR53qzFmeno6hYWFHg1ICCFE9+vqeK615s9//jPJyclcfvnlzcfLy8ubP/7yyy9JTU0FIDc3l82bN9PY2EhxcTGFhYVkZmYyaNAgCgsLKS4uxm63s3nzZnJzc1FKkZWVxZYtWwBYv349ubm5nY5XdK/8s51dWuqR3rRo1FudXYTobdzq7pKVlcWjjz7K1KlTL3hbQWrShRDCf3R1PD948CAbN24kLS2NO++8E3C1W9y0aRPHjx9HKUV8fDw33HADAKmpqUycOJE77rgDg8HA9ddfj+HsxinXXXcdjzzyCE6nk+nTpzcn9tdccw1Lly7l1VdfZeDAgfJzxo/kV1iJCjYSGdxKZ5eE/qiwcB9EJoT/cStJP3jwIAkJCXz99dcXfE4GTyGE8B9dHc+HDRvG66+/fsHxpp7oLbnyyiu58sorW3xNS69LTEzkscceazcW0fMUVFpb7I+utYZjeajhY3wQlRD+ya0k/dxd6IQQQvgvGc+FtzjPdnaZnRl14SctpVBZLqUuQnSAWzXpd911V4vHFy1a5NFghBBCeJeM58JbimsasTp0yzuNHjsIgBo4tJujEsJ/uZWkFxUVXXBMa82ZM2c8HpAQQgjvkfFceEt+ZTuLRk0mSEnv5qiE8F9tlrs8++yzgKvdVtPHTUpKSpoX+QghhOjZZDwX3lZwtrNLamTgBZ/Tx/IgNQMVENDdYQnht9pM0pu2a/72x0ophg4dysSJE70XmRBCCI+R8fx8nxdUU3a0jsszQn0dSq9RUGEjIcxEaMD5G2VphwPyj6Aume2jyITwT20m6T/84Q8BGDx4MGPHju2WgIQQQniejOfn23OmlnXHqpk7MNOvd1zsSfIrraRFtlCPfiofbFZZNCpEB7lVky4DuhBC9A4ynrskRwRR3+jAUm/3dSi9gt2pOVXVSvvFs5sYKUnShegQt5J0IYQQojdJjnDVTZ+qsvk4kt7hdJUNu7PlRaMcOwjmCIhP6v7AhPBjkqQLIYTocyRJ96z8s4tGWyp30UfzYOAQKSsSooNaTdKXLFnS/PG//vWvbglGCCGE58l4fqHYUBMhAQZJ0j2kpLYRgKTw87u36Po6KDqJSh/sg6iE8G+tJum7du1ybeML/O1vf+uueIQQQniYjOcXMihFalQIJyVJ9whLg51gk7qgswvHD4HWqAypRxeio1rt7jJs2DDuv/9++vXrh81mu6CvbpNf//rXXgtOCCFE18l43rIB0aHsOlXh6zB6BUudnZiQC1OKpkWj0tlFiI5rNUm/44472LJlC6WlpSilzuurK4QQwn/IeN6ytOgQ1uaVYLU7CTLJEq2uKK+3E91akp7QHxUW7oOohPBvrSbpgYGBTJkyBXDtUNfUY1cIIYR/kfG8ZWkxIWigsNpGenSwr8Pxa+UNdjJjzv8aaq3hWB5q+BgfRSWEf2tzM6MmV199NYWFhWzatAmLxUJMTAyTJ0+mX79+3o5PCCGEB8l4/o206BAATlZJkt4VWmssdXaik7+VUlhKobJcSl2E6CS33t/btm0bixYt4tSpU5jNZk6fPs2iRYvYtm2bt+MTQgjhQTKefyM1ypWkS4eXrqm3O7E69IU16cebNjEa6oOohPB/bs2k/+Mf/+DOO+9k5MiRzcf27dvHiy++SG5urteCE0II4Vkynn8jJMBIfKhJkvQustS5dm39dk26PpoHJhOkpPsgKiH8n1sz6RaLheHDh593bNiwYZSVlXklKCGEEN4h4/n5kiMCpQ1jF1nqXUn6t2fS9bGDkJqBCgho6WVCiHa4laSnp6fz7rvvnnfsvffeIz093RsxCSGE8BIZz8+XHBnEqSpbcx950XEtJena4YD8I6gMKXURorPcKndZsGABjz/+OGvWrCE2NpaysjICAwO5++67vR2fEEIID5Lx/HzJ4YE02J1Y6u3EhsqMb2eU17dQ7nIqH2xWWTQqRBe4laQnJyezZMkSDh061NwNIDMzE5PJrZcLIYToIWQ8P19yRCDgWjwqSXrnlNfbCTIqQgO+eXO+aRMjJUm6EJ3m9qhsNBoZNmyYN2MRQgjRDWQ8/0ZK5DdJ+uikMB9H458sZzcyUkp9c/BYHpgjID7Jd4EJ4edkizUhhBB9VmyIiWCTksWjXVBeb29h0WgeDBxyfuIuhOgQSdKFEEL0WUopkiMCpQ1jFzTNpDfR9XVQeAKVPth3QQnRC3RbEeJzzz3H9u3biYyM5KmnngKgpqaGJUuWUFJSQnx8PLfffjtmsxmtNatWrWLHjh0EBQVx8803k5GRAcD69et56623ALjyyiuZNm0aAEePHmXFihXYbDays7OZP38+SqlW7yGEEEIAJIcHcaC0ztdh+C1LvYNx/c9JJ44fAq1RGVKPLkRXuD2TXlNTw4YNG3j77bfZsGEDNTU1HbrRtGnTuPfee887tnr1akaNGsWyZcsYNWoUq1evBmDHjh0UFRWxbNkybrjhBl544YXmGN58800effRRHn30Ud58883mOJ5//nluvPFGli1bRlFRETt37mzzHkII0Vd1dTzvbZIjAymptWO1O30dit+pa3TQYHee337x7KJR6ewiRNe4laTn5eWxcOFCPvnkE/Lz81m7di0LFy4kLy/P7RuNGDHighnsrVu3MnXqVACmTp3K1q1bAde21VOmTEEpxZAhQ6itraW8vJydO3cyevRozGYzZrOZ0aNHs3PnTsrLy6mvr2fIEFf925QpU5qv1do9hBCiL/LEeN7bJIcHooHT1VLy0lHl9Q7g/PaL+lgeJPRHhYX7KiwhegW3yl3+9re/sWDBAiZPntx8bPPmzaxatYrHHnus0zevrKwkOjoagKioKCorKwHXjnhxcXHN58XGxmKxWLBYLMTGxjYfj4mJafF40/lt3UMIIfoib43n/uzcNowDo4N9HI1/aeqRHhPqSie01nAsDzV8jC/DEqJXcCtJLywsZOLEiecdmzBhAs8//7zHAlFKeX0VeFv3WLt2LWvXrgVg8eLF5/2S4C6TydSp1/mD3vxs0LufT57Nf3nj+bpjPPc35ybpomMs397IqLwUKsul1EUID3ArSU9KSmLz5s185zvfaT72+eefk5iY2KWbR0ZGUl5eTnR0NOXl5URERACuGfLS0tLm88rKyoiJiSEmJob9+/c3H7dYLIwYMYKYmBjKysouOL+te3zbrFmzmDVrVvOfz72/u+Li4jr1On/Qm58NevfzybP5r848X//+/dv8vLfGc38WZDIQH2qSNoyd0DyT3pSkN29iNNRXIQnRa7iVpP/yl79k8eLFrFmzhri4OEpKSigsLGTRokVdunlubi4bNmxg3rx5bNiwgfHjxzcf//DDD5k8eTKHDh0iNDSU6Ohoxo4dyz/+8Y/mRU67du3ipz/9KWazmZCQEPLy8hg8eDAbN25kzpw5bd5DCCH6Im+N5/4uOTJIZtI7wVJvJ9CoCDu726g+mgcmE6Sk+zYwIXoBt5L0oUOHsnz5crZv3055eTnjxo0jJyenQ60Mly5dyv79+6muruamm27i6quvZt68eSxZsoR169Y1t0cEyM7OZvv27fzmN78hMDCQm2++GQCz2cwPfvAD7rnnHgCuuuqq5hgWLFjAc889h81mY+zYsWRnZwO0eg8hhOiLPDGe90bJEYF8eqQSrbVswNMBlrMbGTV9zfSxg5CagQoI8HFkQvg/t/ukm81mpkyZ0ukb3XbbbS0ef+CBBy44ppRiwYIFLZ4/Y8YMZsyYccHxQYMGNfdfP1d4eHiL9xBCiL6qq+N5b5QSEUiD3Yml3k5sqCSY7jp3IyPtcED+EdQls30clRC9Q5tJ+sMPP9zmi5VSkgALIYQfkPG8bU2LR09W2SRJ74DyejsDooJcfzhdADarLBoVwkPaTNIvueSSFo9bLBbWrFmD1Wr1SlBCCCE8S8bztp3b4WVMUpiPo/Ef5fV2svu5vl762EEAlCTpQnhEm0n6t8tKqqurefvtt/n00+08ibgAACAASURBVE+ZNGkSV111lVeDE0II4RkynrctNsREsEnJ4tEOaLA7qWt0ftN+8WgemCMgPsm3gQnRS7hVk15XV8c///lPPvroI3Jycnj88cdJSpJ/hML/aYcDvX4NdZGR6MBgiImD6HgIDZPFY6JXkvG8ZUopkiMCpQ1jB3y7/aI+lgcDh8jYKYSHtJmk22w23n//fd577z1GjBjB73//e1JTU7srNiG8Tm/5F/rVv1L97U8EBUNMPETHoWLiIDoOYpo+jnd9HCQ7Ewr/IeN5+5IjgjhQUufrMPyGpe6bJF3X10HhCdS4ye28SgjhrjaT9FtuuQWn08kVV1zBoEGDqKyspLKy8rxzRo4c6dUAhfAWbbej33sNBmQSd/8fsRzJQ1tKobwELKXo8lLX/08dd+2gB+hzLxBqPjvzfm4iH4+KcSXxRMVKGzLRY8h43r7kiEA2Hq/CancSZDL4Opwez3LuTPrxA6A1KkPq0YXwlDaT9MBA10Kajz/+uMXPK6V49tlnPR+VEN1Af74OSs9g+PENGOMSUBhQg1o5194I5WVQXno2kS8FS4nrY0sp+uhBqHXNx5+XyEdEnTMLH//Nx2f/T2QMymj0+rMKIeN5+1LOLh49XW1jYLS8U9aepiQ9OsSEPpXvOpjWyiAqhOiwNpP0FStWdFccQnQrbW9Ev/86pA+G0bntnq9MAa7FUPFJtFZtqa0NZ5P3b2bhXUl9CRSdQn+9CxrqXec2vchggMiY1pP4mDgwR6IMMqsnukbG8/ad2+FFkvT2ldfbCTAozIEGdFkJBAZCeKSvwxKi13B7MyMhehO9eR2UFWO45iaPLXJSQcGQlAJJKa0n8nW15yTyrrKaphl5nX8Ydn4BjbbzZ+NNJlfyfkF9fLwsdBXCg/qHf9MrXbSv/OxGRkopnJZiiEmQcUgID5IkXfQ5zbPoA4fAyHHdem8VGgahYZA8oMVEXmsNNVVnZ+G/KadpKrPRh/ZDRRk4HOcn8kHBF87CR7sSeWf2Rd30dEL4tyCTgYQwk7RhdNO5u41SVgKx8b4NSIheRpJ00efoTZ+CpQTDtTf3uFkfpZTr7eLwSBgwqOVE3umAqorzkncsZ8tqykvRp7ZDVTlojQZKTCYYlYth8izIykGZ5J+9EM7P/0V12Rm4/MfnHe8fEcSpqr69sZO7LPV2UiPP7jZqKUENkHp0ITxJflqLPkU3NqI/eB0yhkJWjq/D6RRlMEJUrOs/hracyNsbocICZSUEH9pD3boPcO7YAuGRqAnTUJNmolLSuzlyIXqQE0epW78Gw5yrzvvFNSUikLVH6tBa97hf4nua8no7Y5JC0VYrVFe62tYKITxGknTRp+hNn4ClFMPPF/bqH8DKFABxiRCXSPjkaTTM+SHs24Fz81r0uvfRn7wDaYNcyfrFU1DmCF+HLPxEaWkpK1asoKKiAqUUs2bN4rLLLqOmpoYlS5ZQUlJCfHw8t99+O2azGa01q1atYseOHQQFBXHzzTeTkZEBwPr163nrrbcAuPLKK5k2bRoAR48eZcWKFdhsNrKzs5k/f77n/70OyIRGGxSdgJSBzYeTIwJpsGvK6u3EhUoL1dZY7U5qG53EhASApcR1UMpdhPAoSdJFn+GaRX8TBg2DEWN9HU63UiYTjBmPccx4dHUV+suN6M2fol/9K/qNF2HMRRgmzYSROdISUrTJaDRy7bXXkpGRQX19PYsWLWL06NGsX7+eUaNGMW/ePFavXs3q1av52c9+xo4dOygqKmLZsmUcOnSIF154gUcffZSamhrefPNNFi9eDMCiRYvIzc3FbDbz/PPPc+ONNzJ48GAee+wxdu7cSXZ2tkefQ6UNQgM6/yjqnCQ95ZwOL5Kkt+6b9otGKCsGQMUk+DIkIXod6esm+gz974+hvBTDFT/t1bPo7VHhERhmXo7xd0swPPgMasZcOLQP57N/wHnXfJxvrEKfKvB1mKKHio6Obp4JDwkJITk5GYvFwtatW5k6dSoAU6dOZevWrQBs27aNKVOmoJRiyJAh1NbWUl5ezs6dOxk9ejRmsxmz2czo/8/enQdGVd39H3+fO5PJNllmEhaTQCCEiAg0QKhsAoZIW3GhQrW2WqvyqA2P66N9RFv1cUEsRZQWan8utNa6FZVqXbCAgIICCgEEEVkEAoQsMySZ7JN7fn8MTEFQWTK5k5nv6y9zmeVzmKjfOfd7zhkwgJKSErxeLw0NDeTlBY6XHzVqVPC12lSXDFRcAuzadtTlI7dhFN/Me+Qe6cGZdCnShWhLMpMuooJuaQ7Mouf2hbO+Z3WcsKGyeqIuuw596dXw2aeYKxejF7+Bfu91yM5FjRiL+v4oVGKS1VFFGCovL2fnzp3k5uZSXV2Ny+UCIDU1NXiaqcfjIT09PfictLQ0PB4PHo+HtLS04HW3233c64cf39aUYWDr2ZuW3duPuu6OtxNnN2Qbxu/gPfK00aqKwJkPqW6LUwkRWaRIF1FBf/AeHKzCuPbWqJ5F/ybKbof8c7Dln4OurUavWhZoh3nhz+hXngm0w4wogr4DpR1GANDY2MjMmTP55S9/SUJCwlF/ppQK+b9nixYtYtGiRQBMnz79qC8CJ8rX+yxaFi4gzeU66vc6272XigZ9Sq8Zzux2e5uNqWlPYAec3KwuqLpqmtM60alLlzZ57bbSluPtKKJtzJE+XinSRcTTLc3od+ZD777QZ4DVccKeSkpBFV0MRRejd+9Af7QE/fFSzE9XQorrP7vDZHS3OqqwiN/vZ+bMmZx77rmcc845AKSkpOD1enG5XHi9XpKTA4uR3W43lZWVwedWVVXhdrtxu91s3rw5eN3j8dC3b1/cbjdVVVXHPP7rioqKKCoqCv585HucqMQevaGpkcpN64/6fe6SYPB5ue+UXjOcpaent9mY9lRWYzegxXcQc98eSE0Lu7+vthxvRxFtY46U8WZkZBz3uvSki4inly+Eg56o70U/Fap7DsblkzFmzMMovht65qEXvYF533/TOu0OzKVvo+t8VscU7UhrzZNPPklmZiYXXnhh8HpBQQHLli0DYNmyZQwZMiR4ffny5Wit2bp1KwkJCbhcLvLz81m/fj0+nw+fz8f69evJz8/H5XIRHx/P1q1b0VqzfPlyCgoKQjKWmF5nBsa06+iWl6xkBxX1fpr8ZkjeNxJ4Gvy44gKnjeKpREk/uhBtTmbSRUTTzU2BWfS8fiiZRT9lyh4DA4diGzgUXXMQvXoZesVi9N+fRL/8NCp/KGr4WOibL+0wEe6LL75g+fLldO/enTvvvBOAK664ggkTJjBr1iyWLFkS3IIRYODAgaxdu5abb74Zh8NBcXExAE6nk4kTJzJ16lQAJk2ahNPpBGDy5MnMnTuX5uZm8vPz23xnl8Nsmd3B4QgsHh12XvD64cWj+2qb6emKC8l7d3TeBj/uBDu6tRW8lSA7uwjR5qRIFxFNL38Xqr0Y/3Wn1VEihkpORRVdAkWXBNphVi5Gr1qK/uRDSHWjhp6HGl6IOqOb1VFFCPTp04dXXnnluH927733HnNNKcXkyZOP+/jCwkIKCwuPud6rVy9mzpx5ekFPgLLZoVsOevexM+kApdVSpH8TT4M/8GXmoAdMU/ZIFyIEpEgXEUs3NaHfeRXO7I86s5/VcSKS6p6D6p6DnvRL2PBJYHeY915Hv/sq9MwL9K5//1xUgtPqqEIcl+qeg175Pto0UUagA/SMJAcK2FsrO7x8E2+Dn36dE47YI12KdCHamhTpImLpZe9AzUGMG/7X6igRT9ljYNAwbIOGoWu86I8P7Q7z9z8F2mEGHm6H+R7KkHYYEUayc+H9t6F8H3TNAiDWbtAp0c7eainSj6e51cTXbAbaXWSPdCFCRop0EZF0U2NgNves76HyzrY6TlRRyS7UuAno8y+BYDvMMvSaDwLtMMPOC8ywHyqIhLCSyj588uj2o34nM5Nj2VvbZF2wMHbUHum7AjPpyEy6EG1OinQRkfTSd6C2GuPiK6yOErWUUpDdK1AETboGNqwJtMMsfD3QhtSrT6B3veBcVEKi1XFFtOraDewxsHs7nDM6eDkz2cHn2+vRWsuuUF/jObJI91RAUgoqNtbiVEJEHinSRcTRTY3oha8FdhrJ7Wt1HAGomBgYPBzb4OHoam9goemKxei/zUW/dEQ7zFkDpB1GtCtlt0O3nsfdhrHRr6lq8JOeEGNRuvB0uEh3xdvRVeUyiy5EiEiRLiKOXvp2YBb9IplFD0cqxYUa92P0+RNg17ZD7TDL0auXgys90A4zrBDVNdPqqCJKqO456NXLj1o8engbxr01zVKkf81R7S5VFZAhOzkJEQpSpIuIohsb0O++Fji+Pvcsq+OIb6GUgh69UT16o39yHWxYjbliMfqdV9Fv/+NQO8xYVMFIaYcRoZWdC8vehcoy6Bw4+S/ziG0Yv9dVfv+O5Kn3Y1PgdBjgqUD1G2x1JCEikhTpIqLo998GX430oncwgXaYEdgGj0Af9BzRDjMH/fJTqIHDAu0wfQYEZzqFaCuq+xGLRw8V6e54O3F2Q7ZhPA5vo5/UeDtGnQ+zuUn2SBciRKRIFxFDN9aj33sN+g1C9epjdRxxilSqG/WDS9HjfgxfbUOvXBRoRVi1DNzpqKGFqBGFwWJKiNOW2R1sdti1HYacCwTu9GQmO9hbLTu8fJ2nofXQolHZI12IUJIiXUQMveQt8NViXPwzq6OINqCUgp69UT17oy+7Dl2yOtC//s589NuvQG5fGi++HM4KzZHxInooewxkZh/35NHN5fUWpQpf3no/XZNioGpf4ILskS5ESMh9YxERdEM9+r0F0L8A1TPP6jiijakYB8aQkdhuuQ/jd8+gJl4NvhqqH7sPc8Viq+OJCKCye8Gu7Witg9cykx1U1Ptp9JsWJgs/nkY/7vgjDzKSmXQhQkGKdBER9JJ/QV2t7OgSBVRqGsYPJ2Lc/wccAwrQz89Bb99idSzR0WXnQr0PKg8EL2UdWjy6r0b60g9raTWpbWrFdXhnl9g4SEyyOpYQEUmKdNHh6fq6wCz6gCGonr2tjiPaibLZSPmfB8GVjvmnR9DeKqsjiQ5Mde8V+IfdO4LXjtyGUQR4G1qBwMLaw3uky2FPQoSGFOmiw9NL3oR6n+zoEoWM5BSMKb+BxkbMudPQzbLIT5yirGyw2dC7tgUvnZHkQCFF+pGOPMiIqgppdREihKRIFx2arveh//1P+N73Udm5VscRFlCZ3TEm3wZffRnYsvGInmIhTpSKccAZ3Y9aPBprN+iUGCNF+hGOOsjIU45yy6JRIUJFinTRoenF/4L6OplFj3Iqfyjqkp+hP16K/vcCq+OIDuqbFo+W1sgdmsOCM+m2VvDVyky6ECEkRbrosIKz6PlD/9NPKqKWuuAyGDQcPf+v6M/WWh1HdETZvcBXA97K4KWsZAf7apvlDs0hngY/hoLkukNrQGT7RSFCRop00WHpRW9AQx3GRT+1OooIA8owMK65BTK7Yz41A31gn9WRRAcT/LK/6z8tL5nJDhr9mqpDM8jRztvgxxVnxzi0/aIcZCRE6EiRLjokXecLFOkDh6K651gdR4QJFRePUXw3GAbmHx9C19dZHUl0JFk9QRlHLR49vMNLabX0pUNgJt0Vb0dXyR7pQoSaFOmiQ9KL/gkN9dKLLo6hOnXFuPEuqNiP+fRMtNlqdSTRQajYWMjohpZtGL+Rt8GPO8EOngqw2SDVbXUkISKWFOmiw9F1tYFZ9EHDUVk9rY4jwpA6sz/q8v+CjZ+gF/zd6jiiA1Hdc2DXtmAPujveTpzdYK8sHgUOzaTH2aGqHFLTUIbN6khCRCwp0kWHo9/7JzQ2SC+6+FZqzI9Q545DvzMfc80HVscRHUV2LtQchGoPAEopspIdMpMOtLRqappaDx1kVCGLRoUIMSnSRYeifTXoxW+iBo9AZfWwOo4IY0op1M9ugNyz0H95An3EYkAhvonKPv7i0VIp0jnYeGiP9ITDe6RLP7oQoSRFuuhQ9HsLoLkRdZH0oovvpuwxGL+6C5zJmHMfRtcctDqSCHdZPUGpo77UZSU7qKz30+g3LQxmvcN7pKc6FHg9smhUiBCTIl10GLq2Br3kLVTBSFRmd6vjiA5CJbswiu+B2hrMP01H+1usjiTCmIqLh65ZR508enjx6L4on00PnjbqrwNtSruLECEmRbroMPR7rwdm0S+83OooooNR2b1QV98E2zajX/x/cjCN+FaBxaPHFunR3vISPG20/lC/vsykCxFSUqSLDkHXVqPffws15FxUhsyii5NnnDMa9aOJ6OUL0cvesTqOCGfZuXCwCl3jBeCMJAcKmUn3Hj5ttObQHunSky5ESEmRLjoEvfB1aG5CXSg7uohTpyZcCf0L0C89hf7iM6vjiDD19ZNHY+0GnRJjKI3ybRg9DX5S4uzYPOWBC1KkCxFSUqSLsKdrDh6aRR+FOiPL6jiiA1OGDWPy/0CnMzCfnI6uPGB1JBGODp1i/PXFo9G+DaO3wY873hY4yCgpBeWItTqSEBFNinQR9vTC16GlBXWR9KKL06cSEjGm3AOtrZhzHkY3NVodSYQZFZ8AnTOOLtJTAtsw+s3oXc/gafDLHulCtCMp0kVY0zVe9NK3UOeMQnWVWXTRNlTXTIzr74C9uzHnPS4LScUxVHYvOGKHl95p8TS3anYfjN6WF0+DH1d8YI902X5RiNCTIl2ENf3ua9DiR42XWXTRtlS/waiJV8OnK9FvvWJ1HBFusnuBpwJdWwNAXlocAF9UNliZyjJ+U1PT2Iorzg6eCjnISIh2IEW6CFu62ote9g5q6GhU10yr44gIpMZNQA0dg/7n39ElH1sdR4SR4OLRQ7PpXZwxJMfa2FoVne1RBxv9aMCtWqC5WdpdhGgHUqSLsKXffRX8ftkXXYSMUgp11RTIzsV8ehZ6726rI4lwkR0o0vWubUDgdyUvLY6tUTqTfvggI5ffB8ge6UK0BynSRVjSBz3oZe+ihp6H6pxhdRwRwZQjFqP4boiNxZzzELqu1upIIgyoBCd06nrUyaN56fHsrWmmrrnVwmTW8NQfOm20PrB3PG6ZSRci1KRIF2FJv/sqtPpR4y+zOoqIAsqdHijUvZWYf/4dujX6ijBxLNW911Enj+alx6OBL6Ow5eXwaaOptYcOMpKZdCFCTop0EXa0tyowiz6sENX5DKvjiCihevVBXVkMn69Hz59ndRwRDrJ7QeWB4N2V3ocWj26tir6WF2+jHwWkHtwPsfGQ4LQ6khART4p0EXb0u6+CNmUWXbQ7Y0QRauxF6EVvYK5YbHUcYTGVfXjx6A4AnA4bmcmO6JxJr/eTEmfD8FRAWieUUlZHEiLiSZEuwor2VqGXL0QNH4vq1NXqOCIKqZ9cC30GoJ+fg96+xeo4wkrdj148CgQXj0bb3vreQwcZBfZIl350IdqDFOkirOh3/hGYRb/gJ1ZHEVFK2WwYN/waXOmYf3oE7a2yOpKwiHImBwrSQzPpEOhLP9jYSkWd38Jk7S94kFFVBcqdbnUcIaKCFOkibGhPBfqD9wKz6OldrI4jophyJmNMuQcaGzDnTkO3NFsdSVile85RM+nR2pfubfDjdiioq5WZdCHaiRTpImzod+aDRnrRRVhQmdkY194GX32Jfm5O1LU3iACVnQvl+9H1dQD0SI0jxlBRtV96q6k52NiKSx/qxZfTRoVoF1Kki7CgqyrQH/wbNaIIJbM0IkyoQcNQF/8M/fH76H//0+o4wgLBxaN7Ai0vMTZFjjsuqk4eDZ426g98UZH/RgvRPuxWB3j77bdZvHgxWmvGjh3L+PHjeeWVV1i8eDHJyckAXHHFFQwaNAiA119/nSVLlmAYBtdccw35+fkAlJSUMG/ePEzTZOzYsUyYMAGA8vJyHn/8cWpra8nJyeGmm27Cbrd82OJr9Nv/AJBedBF21PjL0KVfoef/BZ3RHdVvkNWRRHsKLh7djjqzPwB56XEs/PIgflNjNyJ/lxNvQ+DcgNSGg4ELUqQL0S4snUnfvXs3ixcvZtq0acyYMYO1a9dSVlYGwPjx45kxYwYzZswIFuilpaWsXLmSxx57jHvuuYdnnnkG0zQxTZNnnnmGu+++m1mzZrFixQpKS0sBeP755xk/fjx/+MMfSExMZMmSJZaNVxyfripHr1iEOvd8OWpahB1lGBjX3AKZ3TGfmoE+sM/qSKIdqeRUcKUffahRWjzNrZpdB5ssTNZ+PA0tALjqKsBmg5RUixMJER0snVLeu3cvubm5xMbGAnDWWWexatWqb3z8mjVrGD58ODExMXTu3JmuXbuybVtgQU/Xrl3p0iWw2HD48OGsWbOGzMxMNm3axC233ALAmDFj+Mc//sG4ceNCPDJxMvRbr4AC9SOZRRfhScXFYxTfjTntfzDnPIwxdQYqPsHqWJaYO3cua9euJSUlhZkzZwJE/t3P7jno3f8p0s9MP7R4tLKBXu44q1K1m8Mz6e6DZeBKRxk2ixMJER0snUnv1q0bW7Zsoba2lqamJtatW0dVVWC7s4ULF3LHHXcwd+5cfD4fAB6Ph7S0tODz3W43Ho/nmOtpaWl4PB5qa2tJSEjAZrMd9XgRPnRFGXrlYtS542RbLxHWVKeuGDf8LxzYi/n0TLTZanUkS4wZM4a77777mOuRfPdTZefCgb3oxnoAOifGkBJri5odXjwNLSggpapUWl2EaEeWTk9kZWVxySWX8NBDDxEXF0ePHj0wDINx48YxadIkAF5++WWee+45iouLQ5pl0aJFLFq0CIDp06eTnn7yBaPdbj+l53UEoRpbzctP0WDYSPv5DdjSrPu7k8+uY2r3sY0spL7GS+1TM4l/73WcV94Y0rcLx8+ub9++lJeXn9BjI+Xup+reK7C7z+6dkHc2Siny0uPYWhkdi0e9Da0kx9mwV5Wj+gywOo4QUcPyFZSFhYUUFhYC8MILL5CWlkZq6n/63caOHcujjz4KBGbCD8+0Q2Bm3e12Axx1vaqqCrfbTVJSEvX19bS2tmKz2Y56/NcVFRVRVFQU/LmysvKkx5Kenn5Kz+sIQjE2XVGG+f7bqNE/wqsVWPh3J59dx2TF2PSQUagtG6l79Tnq07pgDDk3ZO91KuPLyMgIUZpvt3DhQpYvX05OTg6/+MUvcDqdeDweevfuHXzMkXczv37388svvwzfu5+HdnjRu7ej8s4GAn3pn+yto665lURHZLd/eBpacMXZ4KAHZN2QEO3G8iK9urqalJQUKisrWb16NQ8//DBerxeXywXA6tWr6datGwAFBQXMnj2bCy+8EK/Xy/79+8nNzUVrzf79+ykvL8ftdrNy5UpuvvlmlFKcffbZfPzxx4wYMYKlS5dSUFBg5XDFEQK96AbqRxOtjiLECVNKwc9uQO/fg/7LE+guGahDO4BEq4i/+5meToUrDceBUlIOPb4gx8bfN1RS7o9lSEbHWEh5qndmalpK6RJvA22SlJ1DfJjd3fkm4XgnKtSibcyRPl7Li/SZM2dSW1uL3W7nuuuuIzExkWeffZavvvoKpRSdOnXi+uuvBwI97MOGDeP222/HMAyuu+46DCPQVn/ttdfy8MMPY5om5513XrCw//nPf87jjz/OSy+9RM+ePYOz9sJaunw/+qMlqPPGo1LTvvsJQoQRZY/B+NVdmA8dWkh6z2OBXUCiVDTc/TSzetL4xSZaDj2+c0xgTcKaHWX0TPCf9Htb4VTvPFXUNpKVGDh11+eIp66D3JmL5LuI3yTaxhwp4/2mO6CWF+kPPPDAMdduuummb3z8pZdeyqWXXnrM9UGDBgUXKx2pS5cuPPLII6cXUrQ5/dYrYLOjfiiz6KJjUskujCl3Yz56F+aT0zFufxBlj7E6liWi4e6n6tUHvfETdI0XlezC6bCRmeyI+L70wGmjflyOwEFGsnBUiPZjeZEuoo8u34f++H1U4YWo1OPPkgnREajsXNTVN6Gfnol+8SnUVaFt8QgHjz/+OJs3b6a2tpYbb7yRyy67jE2bNkX83U/VbzB6wfPoz9ahhgcy5aXFsXZ/HVrrQBtUBKppasXU4G46dJCR7MIlRLuRIl20O/2vl8Eus+giMhjnjMYs/Qr97quY3XpgjLnA6kghdeuttx5z7dsK6Yi5+9mtJySnwmefwuEiPT2e93fWUF7XQhenw+KAoeFpCLTyuOqqIDkVFROZ4xQiHFm6T7qIPrpsL/rjZajRP0KluKyOI0SbUD++EvoXoF96Cv3FZ1bHESGgDCMwm75pHbo10I+elxYPENEtL97DRfrBMml1EaKdSZEu2pV+62WIsaN+eOzMmhAdlTJsGJP/Bzp1xXxyOrrygNWRRCj0Gwz1Ptj5BQA9XLE4bCqiDzUKzqR79qHcsv2iEO1JinTRbnRZKXrVctSY8ahkmUUXkUUlJGJMuQdaWzHnTEM3Re7sarRSffPBMNAb1wJgNxQ5rsg+1OhwkZ5asUtm0oVoZ1Kki3aj33wZYmJQP/ix1VGECAnVNQvjv+6AvV+h5z0ROKVSRAyV6IScPujPPgley0uPY4e3Eb8ZmZ+1t8FPskMR09wAMpMuRLuSIl20C72/FL1meWBf9CjeT1pEPtV/MGri1ehPV6Df/ofVcUQbU/0Hw+4d6GovEOhLb27V7DrYZHGy0PA0+HHZA19AlJw2KkS7kiJdtAv9r5fAEYv6gfSii8inxv0Ydc7owJZ9JausjiPakOo3GAD9WaDlJS89DoCtlZHZl+5t8OMmcJCRtLsI0b6kSBchp/ftRq/5AFU4HpWUbHUcIUJOKYX6xX9Ddi7m04+h9+62OpJoK916QoobNgZaXjonxpASZ4vYxaOeej+u1vrADzKTLkS7kiJdhJz+18vgiEOdL73oInooRyxG8d0QG4s55yF0Xa3VkUQbUEqh+g1Cby5Bt7ailCIvLTIXj5pa423042qqgfgEH46DkAAAIABJREFUVILT6khCRBUp0kVI6b270Z98KLPoIiopdzrGr6aCtxLzz78L7q8tOjbVfzA01MH2LUCgL720phlfc2R9vjWNgdNGXfVVsmhUCAtIkS5CSr/5IsTGocZNsDqKEJZQuWehfv4r+Hw9ev5frI4j2sJZh7Zi/OxTIHDyKMC2qsiaTT+8/aK7+oAU6UJYQIp0ETK69Cv0pytQhRehnDKLLqKXMfJ8VOGF6EX/xFy52Oo44jSphETIPQu9MVCk56ZF5uLR4Gmj3n0oWTQqRLuTIl2EjPnmS4E+xnGXWB1FCMupn1wLfQag/zYHveMLq+OI06T6FUDpTrS3CqfDRlayI+IWjwZPG605IItGhbCAFOkiJPSenbB2JWrsRajEJKvjCGE5Zbdj3PBrSE3DnPsI+mCV1ZHEaVD9BwEc0fISWDwaSQdYBWfSm2qk3UUIC0iRLkLCfPNFiE9EFcksuhCHKWcyxpR7oLE+UKi3NFsdSZyqzB6Qmvaf/dLT4qluaqW8rsXaXG3I0+AnyaaJ0a3S7iKEBaRIF21O794B6z5GFV0UOEZbCBGksnpgXHsb7NyKfm5ORM28RhOlVGCXl89L0H5/cPFoJG3F6Gnw41KHvnRIu4sQ7U6KdNHmAr3oiaiii62OIkRYUoOGoS66Av3x++h//9PqOOIUqX6DoaEetm8hOzUWh01FVF+6p8GPy2wAux2SXVbHESLqSJEu2pTevR1KPkadf4kcfCHEt1AXXg6DhqHn/wW9aZ3VccSpOOt7YLOhP/sUu6Ho5Y6sQ428DX7cTTXgSkcZUi4I0d7k3zrRpsw3XoSERNTYi6yOIkRYU4aBcc2tkNEN8//9Dn1gn9WRxElS8QmQ2xe98RMAeqfFscPbiN/s+C1MptYcbPTjavDIolEhLCJFumgzetc2WL/60Cx6otVxhAh7Ki4+sJDUMDDnPIxuqLc6kjhJqv9g2LsL7akkLy2e5lbNV94mq2OdttqmVvwmuGrKZdGoEBaRIl20mcAsuhM1VnrRhThRqlNXjBv+Fw7sxXzmMbRpWh1JnATVbzAQ2IoxL/3QoUYR0Jce3H6xWvZIF8IqUqSLNqF3fgkb1qDGTQjcAhZCnDDVZwDq8smwfjX6n3+3Oo44GRndwZ2O/uxTOifGkBJni4iTR4MHGTVVg8ykC2EJKdJFmzDffBESk1CFF1odRYgOSZ03HnXuOPTb/8Bc84HVccQJUkoFZtM3r4dWP3lp8Wyt6viLRw8X6e7mGpT0pAthCSnSxWnTO76AjZ/ILLoQp0EphbriBujVB/2XJwI7JYkOQfUfDE0NsO1z8tLj2FvTjK+p1epYp6WstgUDHdjdRdpdhLCEFOnitJlvvgjOJFTheKujCNGhqZgYjOKpkJiMOWca5kGP1ZHEiegzAGx29MZPyUsLHGr0padjz6aX1jTTVTURo1vBJUW6EFaQIl2cFr19C3y2FjXuUlSczKILcbpUsgtjyt3gq6GpZLXVccQJUHEJkHc2+rNP6Z0WhwK+7OB96aU1TWS21kCKGxUTY3UcIaKSFOnitARm0ZNR511gdRQhIobKzsV4+M/Ej/mh1VHECVL9BsG+3STUeshMdnToHV5aTc3+2mayGirAnW51HCGilhTp4pTp7Vtg0zrUDy9FxcVbHUeIiKJS3VZHECfh6K0Y49la2YjWHfNQozJfC34Tsg6Wyh7pQlhIinRxysw3XoCkFNQYmUUXQkS5M7pBWudAkZ4WR3VTK+V1LVanOiWl1YHDmLIqtsuiUSEsJEW6OCV622bYXBKYRY+NszqOEEJYKrAV4yD4fD29UwM93F9UdszFo3tqmgHIqC2TPdKFsJAU6eKUmG+8GJhFH/0jq6MIIURYUP0LoKmR7MrtOGyqw/al761pwh0Dia2NKLcU6UJYRYp0cdL01k3w+XrUDyfKLLoQQhzWZwDY7dg++4Re7ji2dtSZ9OpmsmICs+mkycJRIawiRbo4aeYbL0ByqsyiCyHEEVRsHOT1Q3+2lj7p8Wz3NFLf0rEONdJaU1rdTKa/JnAhrYu1gYSIYlKki5Oiv/gMvtiI+tFEVGys1XGEECKsqH6DYf8ezklqwW9qVu3xWR3ppHga/DT4TbJq90NaZzlFWggLSZEuTor5xguBwy1Gyf7NQgjxdap/YCvG3qXr6ZRg58NdNRYnOjmlhxaNZpVvg6we1oYRIspJkS5OmN6yAbZ+FphFd8gsuhBCHKNLJqR3QW1ay4jsZErK6vA1dZyWl9LqQJGeWboZJUW6EJaSIl2cEK11YBY91Y0a9QOr4wghRFhSSgVm0z9fz8jMePwmfFxaa3WsE7anuokEG7iaqlHdelodR4ioJkW6OCEtGz+FLzejfjQJFeOwOo4QQoQt1W8wNDfRq3IbXZ0xfPBVx2l52VvTTJatGQWQ2cPiNEJENynSxXfSWuN76RlITUOdO87qOEIIEd7OHAD2GPjsU0ZmJ7PhQD3VjX6rU52QPTXNZLV4weGAzl2tjiNEVJMiXXy3TWtp+Xw96oKfyCy6EEJ8BxUbC2f2Q2/4hJHdnZgaVu4O/5aXuuZWvA1+Mmr2QUY2yrBZHUmIqCZFuvhWes9OzKd+jy2jO2rk+VbHEUKIDkENHgHl+8gu305WsoMPO0CRHtzZpWyrLBoVIgxIkS6+kT6wD3PWvRAbj+u+WaiYGKsjCSFEh6DOGQ3OJPSSNxiZncSmA/VU1bdYHetblVY3AZDl2SXbLwoRBqRIF8elqyowH/stAMZtD2DrfIbFiYQQouNQjljUuT+AklWMSGpGE/4tL6U1zdiVpkujR2bShQgDUqSLY+gab2AGvaEO49b7UWdkWR1JCCE6HDXmAjAMsta8S4/UWD7cFd5F+p7qZs4wmrBpU2bShQgDUqSLo+h6H+as+8FbgXHTvajuvayOJIQQHZJyp6MGDUd/+G9GZMaxpbKBirrwbXnZW9NEVrMXXOmoxCSr4wgR9aRIF0G6qRFz9gOwfw/Gr+5G9e5rdSQhhOjQVNHF0FDPiPL1AHy4Kzz3TG9pNSnztZBZvVdm0YUIE3arA4jwoFtaMOdOgx1bMW74NarfIKsjCSHC0Ny5c1m7di0pKSnMnDkTAJ/Px6xZs6ioqKBTp07cdtttOJ1OtNbMmzePdevWERsbS3FxMTk5OQAsXbqU1157DYBLL72UMWPGALBjxw7mzJlDc3MzAwcO5JprrkEpZclY24LKORN65tF12QJyR/4vH+6q5cd906yOdYx9tS2YGrLKt6MG9rA6jhACmUkXgG5txXxqBmwuQV19E2rwcKsjCSHC1JgxY7j77ruPurZgwQL69+/P7Nmz6d+/PwsWLABg3bp1lJWVMXv2bK6//nqefvppIFDUz58/n2nTpjFt2jTmz5+Pz+cD4KmnnuKGG25g9uzZlJWVUVJS0r4DDAFVdDGU72Oko5ptnkb21zZbHekYpTWHdnbx7ZeTRoUIE1KkRzltmui/zoZ1H6Mun4wxYqzVkYQQYaxv3744nc6jrq1Zs4bRo0cDMHr0aNasWQPAJ598wqhRo1BKkZeXR11dHV6vl5KSEgYMGIDT6cTpdDJgwABKSkrwer00NDSQl5eHUopRo0YFX6sjU4OGQ2oawza+A8CKMFxAWlod+OKQWV+ByuppcRohBEiRHtW01uiXn0Z/9D7q4p9hFF1sdSQhRAdUXV2Ny+UCIDU1lerqagA8Hg/p6enBx6WlpeHxePB4PKSl/aflw+12H/f64cd3dMpuR513AZ02fUSfZIMPwrAvvbS6mU40Emto6JJhdRwhBNKTHtX0P/+OXvIv1PmXoC683Oo4QogIoJRqlx7yRYsWsWjRIgCmT59+1JeBE2W320/peafCnPAzKt56mTG+L3nS7EWdkUC2O6Fd3vuwbxvv/vo9dG85iL17Dmldu7ZrrlBpz883XETbmCN9vFKkRylz4evot15BjTwf9ZNrO/TCLCGEtVJSUvB6vbhcLrxeL8nJyUBghryysjL4uKqqKtxuN263m82bNwevezwe+vbti9vtpqqq6pjHH09RURFFRUXBn498nxOVnp5+Ss87VeqcMRSsmo8a8r+8WbKbnw5o3+Lim8Zras0uTz0/8O6mtUtWu/6dhFJ7f77hINrGHCnjzcg4/t0raXeJQubyhej581AFI1FXFUuBLoQ4LQUFBSxbtgyAZcuWMWTIkOD15cuXo7Vm69atJCQk4HK5yM/PZ/369fh8Pnw+H+vXryc/Px+Xy0V8fDxbt25Fa83y5cspKCiwcmhtSo29CHddFX3tPj7YVYPW2upIAFTUtdDcqsn07pHtF4UIIzKTHmXM1cvRz8+FfoNR192GMmxWRxJCdCCPP/44mzdvpra2lhtvvJHLLruMCRMmMGvWLJYsWRLcghFg4MCBrF27lptvvhmHw0FxcTEATqeTiRMnMnXqVAAmTZoUXIw6efJk5s6dS3NzM/n5+QwcONCagYaAysyGs77HyJ0r+HO3H7DrYBM9XHFWxwouGs2qP4DKGm9xGiHEYVKkRxG9YQ362VmQexbGjXeh7DFWRxJCdDC33nrrca/fe++9x1xTSjF58uTjPr6wsJDCwsJjrvfq1Su4/3okMsZezNA/P8ZT3cbxwa7a8CjSaw4X6eUyky5EGJF2lyihv/gM88lHIasnxk33omJjrY4khBDRp/9gUlzJ9G/Yy4dh0vJSWtNEkm4mOd6BSk61Oo4Q4hAp0qOA3vkl5h8ehPQuGLfcj4pv3x0FhBBCBCjDQBVexIhdH1Hma2Gbp9HqSJRWN5PVWAWyP7oQYUWK9Ain9+7GfOJ+SErGuO0BVFKy1ZGEECKqqRGFnOPbgV2bfBgGBxvtqW4iq7oUJa0uQoQVKdIjmK4ow5x1L9hjMG5/EOVK++4nCSGECCkVl0Dy0JF8z7OVFTsPWtryUtPop7bZJMtXJv3oQoQZKdIjlPZWYT72W/C3BGbQO0XG4RRCCBEJVOF4RpSvp6LR5ItK61pe9hxaNJpZXy4z6UKEGSnSI5CurQnMoNfWBHrQM7tbHUkIIcQRVKeufP+MeGJMPx/s8FqWI7j9YmMldM2yLIcQ4lhSpEcY3VAf6EGvPIBx029QPXtbHUkIIcRxOIsuYFDV56zY4aHVtKblpbSmCYf2k+5yomJkW14hwonl+6S//fbbLF68GK01Y8eOZfz48fh8PmbNmkVFRUXwYAyn04nWmnnz5rFu3TpiY2MpLi4mJycHgKVLl/Laa68BcOmllzJmzBgAduzYwZw5c2hubmbgwIFcc801EXvCpm5qwvzjg1C6E6P4btSZ/a2OJIQQ4pvknc2Ify1hldmfzeX19O+a2O4RSqubyWyswpbZo93fWwjx7SydSd+9ezeLFy9m2rRpzJgxg7Vr11JWVsaCBQvo378/s2fPpn///ixYsACAdevWUVZWxuzZs7n++ut5+umnAfD5fMyfP59p06Yxbdo05s+fj8/nA+Cpp57ihhtuYPbs2ZSVlVFSUmLZeENJ+1swn5wOX25GXXsbasAQqyMJIYT4Fkophny/H7GtzXy4fqclGfYcbCSrZh9062HJ+wshvpmlRfrevXvJzc0lNjYWm83GWWedxapVq1izZg2jR48GYPTo0axZswaATz75hFGjRqGUIi8vj7q6OrxeLyUlJQwYMACn04nT6WTAgAGUlJTg9XppaGggLy8PpRSjRo0KvlYk0WYr+plZ8NmnqCt/hfH9UVZHEkIIcQLih45kcPU2Vpb7273lpclvUtHQKotGhQhTlhbp3bp1Y8uWLdTW1tLU1MS6deuoqqqiuroal8sFQGpqKtXV1QB4PB7S09ODz09LS8Pj8eDxeEhL+8/2gm63+7jXDz8+kmit0c//Cf3Jh6hJ12CM+qHVkYQQQpwgFePg3IxYaow4NmzZ067vvffQzi5Z9eWy/aIQYcjSnvSsrCwuueQSHnroIeLi4ujRoweGcfT3BqVUu/SQL1q0iEWLFgEwffr0o74MnCi73X5KzztVWmt8f/kD9R+8R+Kkq3H+/L9C9l7tPbb2Fsnjk7F1XJE+PhEw+LxhxL+5mw/X7Wdg3/bbjWtPdRMAmboOUtzt9r5CiBNj+cLRwsJCCgsLAXjhhRdIS0sjJSUFr9eLy+XC6/WSnBw4JdPtdlNZWRl8blVVFW63G7fbzebNm4PXPR4Pffv2xe12U1VVdczjj6eoqIiioqLgz0e+z4lKT08/peedKvNfL6HfeAlVeCEN4y6lMYTv3d5ja2+RPD4ZW8d1KuPLyMgIURoRKrFuN99X6/jI7+Za70ESXant8r6lNc0Y2iQjLSliN1QQoiOzfAvGw60slZWVrF69mpEjR1JQUMCyZcsAWLZsGUOGBBZBFhQUsHz5crTWbN26lYSEBFwuF/n5+axfvx6fz4fP52P9+vXk5+fjcrmIj49n69ataK1Zvnw5BQUFlo21LZmL3kD/8wXUsPNQl0+W/8AKIUQHdtGQHOrs8bz+3tp2e8/S6ia6NHpwZMlZGkKEI8tn0mfOnEltbS12u53rrruOxMREJkyYwKxZs1iyZElwC0aAgQMHsnbtWm6++WYcDgfFxcUAOJ1OJk6cyNSpUwGYNGkSTqcTgMmTJzN37lyam5vJz89n4MCB1gy0DZkrFqNffhoGDkVdfTPKsPy7lhBCiNPQ+6yejFy1iDdaO/OjqoOkpYV+Nr3UU09mXTn06RHy9xJCnDzLi/QHHnjgmGtJSUnce++9x1xXSjF58uTjvs6RbTNH6tWrFzNnzjz9oGFCf7oS/dc/QN98jP+6E2WzWR1JCCFEG/j5iBw+/rielxZtZMrl54b0vVpNzb66VgbVH0B1GxDS9xJCnBqZgu1A9GdrMZ/6PeTkBQ4rktPhhBAiYmT0zuEHLbtY1JLG7rLQ7kR2wNeCH0VWfSWc0S2k7yWEODVSpHcQettmzD9NgzO6Ydx8Lyo2zupIQggh2thlY84itrWZvy3dGtL32VNzaGeXOI1yxIb0vYQQp0aK9A5A796OOfsBcHXCuO3/UAlOqyMJIYQIgdScHH7s387q1lQ276767iecotLqwB7p3dLl/ydChCsp0sOc3l+KOes+iE/AuO0BVHL7bM0lhBDCGpeMHYi7qZq/rNiJ1qE5hbTUU4+rqYbErKyQvL4Q4vRJkR7GdFU55qx7QSmM2x5EpXWyOpIQQogQi+uRw+Wt2/nCdPLRttCcA1Ba5SOzvhwlJ40KEbakSA9TutqL+dhvoakhMIPeNdPqSEIIIdpJ0bjv062ujL+t2YvfbNvZdK01pfWarPpykCJdiLAlRXoY0nW1gRn0ai/GzfehuvW0OpIQQoh2ZM/O5Uq9g306jn9/Xt6mr+1p8FOvDbJaDoJb7tAKEa6kSA8zurEe84n/gwN7A9ss9upjdSQhhBAW+P4PRtH34A5eWl9OQ4vZZq+7tyawaDTLaZPTqoUIY1KkhxHd0ow5Zxrs2oZx/a9RffOtjiSEEMIiRo9cfmF8xUEdw4INZW32unsOBrZfzEpParPXFEK0PSnSw4T2+zH//DvYsgH1y1tQA4daHUkIIYTF+lwwjmHlG1iwxcvBBn+bvGZp+UHi/Y24szLa5PWEEKEhRXoY0KaJ/ssTsH416mc3YAw7z+pIQgghwoDKzuXnjr20mPDiuraZTS/11JFVX44hi0aFCGtSpFtMa41+8c/oVctQE67EOG+81ZGEEEKEkazxFzJu/8e8t7M22E9+OkrrNZn1FZCZ3QbphBChIkW6xfTrz6GXvoP6waWoC35idRwhhBBhRvXozU/iK3G0NvO3tftP67XqmlvxaAdZqgEVF982AYUQISFFuoXMd+aj33kVNeqHqIlXyyp7IYQQx+W+8MdM2L2Mj/Y2sKWi4ZRfp/Twzi5J9raKJoQIESnSLWIufRv92nOo749C/fwGKdCFEEJ8I9Uzj4uSakltruUvn5ah9akdcFRaVQdAVqfktownhAgBKdItYH68FP3Cn2HAENQ1t6IMm9WRhBBChLnEiyZx+c73+LyqidV7faf0GqX7K7Gbfs7odkYbpxNCtDUp0tuZLlmFnvc45PXDuOHXKLvcchRCCPHdVM6ZFLlbyGyo5Lm1B2g1T342fY+nnjMaKrF169H2AYUQbUqK9HakP18f2Au9ey+M/74H5Yi1OpIQQogOJOain/Lz7W9RWutn8Y7qk37+3gbIbKyC9C4hSCeEaEtSpLcTveMLzDkPQ5cMjFvuQ8UlWB1JCCFEB6N69eGczg7O9O3h+ZJyvqg88UWkLa0mZTqOLHsLypD//QsR7uTf0nagS3diPvF/kJyKcev/oZyyYEcIIcSpsV30U361+RUcLY1MfW8Xr22qwjyBhaS7vQ2YyiArKaYdUgohTpcU6SGmy/dhzroPHLEYtz+ISnVbHUkIIUQHpnLPonuPM3hszWN8P7GJv5ZU8H/vl3Kwwf+tz/tqd+DE0qzOKe0RUwhxmqRIDyHtqcB87F4wTYzbH0BJD6AQQog2YFxxA4kpKdzxr99yQ80qNh+o45a3d1Kyv+4bn7Nz16EiPTujvWIKIU6DFOkhomsOYs66F+p9gRaXM7pZHUkIIUSEUF0zMX7zGMYV1/ODz9/l0TVP4Gzycf+SPfytpAL/cXZ++aqihvRGL3Hdsy1ILIQ4WVKkh4Cu92E+fh94KjD++7eo7F5WRxJCCBFhlM2GUXghxkNz6dHvTH637CHGVq1n/qYq7v73Lsp9LUc9fne9JqvlICoh0aLEQoiTIUV6G9NNjZh/eBD27cH41VRU3tlWRxJCCBHBVLIL49pbSbjzQYq9K7l989/ZXV7LrW9tZ+XuGgBMrSnV8WTGfHvfuhAifEiR3oZ0SzPm3Edg+xcYk29H9RtsdSQhhBBRQuX2xfjNY5xbeA4zN8zlDO8eHv1gH3/6aC/7PHU0GTF0k51dhOgw5LjLNqJbW6medT9sXoe6+iZUwUirIwkhhIgyymZDjb2QjCEjmDb/r/x99w7+yWhW7vQCdrp1TbU6ohDiBMlMehvQpol+7o80fbQUdfl1GCPPtzqSEEKIKKaSXcReeyvXTDqX3+z7FzQ1orRJVo9Mq6MJIU6QzKS3BdNENzWQePm1NBZdYnUaIYQQAgDVuy8Ft5/J44sXUumpJSVrktWRhBAnSIr0NqDsdozr7ySxU2caq6qsjiOEEJaYMmUKcXFxGIaBzWZj+vTp+Hw+Zs2aRUVFBZ06deK2227D6XSitWbevHmsW7eO2NhYiouLycnJAWDp0qW89tprAFx66aWMGTPGwlF1fMpmI23cBZyZnk5lZaXVcYQQJ0iK9DaiDBtKKatjCCGEpe677z6Sk5ODPy9YsID+/fszYcIEFixYwIIFC7jyyitZt24dZWVlzJ49my+//JKnn36aadOm4fP5mD9/PtOnTwfgrrvuoqCgAKfTadWQhBDCEtKTLoQQImTWrFnD6NGjARg9ejRr1qwB4JNPPmHUqFEopcjLy6Ourg6v10tJSQkDBgzA6XTidDoZMGAAJSUlVg5BCCEsITPpQggh2szDDz8MwPnnn09RURHV1dW4XC4AUlNTqa6uBsDj8ZCenh58XlpaGh6PB4/HQ1paWvC62+3G4/G04wiEECI8SJEuhBCiTTz44IO43W6qq6t56KGHyMjIOOrPlVJt1ha4aNEiFi1aBMD06dOPKvhPlN1uP6XndVQy3sgXbWOO9PFKkS6EEKJNuN1uAFJSUhgyZAjbtm0jJSUFr9eLy+XC6/UG+9XdbvdRixirqqpwu9243W42b94cvO7xeOjbt+8x71VUVERRUVHw51NZEJkeZQspZbyRL9rGHCnj/fqExmHSky6EEOK0NTY20tDQEPznDRs20L17dwoKCli2bBkAy5YtY8iQIQAUFBSwfPlytNZs3bqVhIQEXC4X+fn5rF+/Hp/Ph8/nY/369eTn51s2LiGEsIrMpAshhDht1dXV/P73vwegtbWVkSNHkp+fT69evZg1axZLliwJbsEIMHDgQNauXcvNN9+Mw+GguLgYAKfTycSJE5k6dSoAkyZNkp1dhBBRSYp0IYQQp61Lly7MmDHjmOtJSUnce++9x1xXSjF58uTjvlZhYSGFhYVtnlEIIToSaXcRQgghhBAizEiRLoQQQgghRJiRIl0IIYQQQogwI0W6EEIIIYQQYUaKdCGEEEIIIcKMFOlCCCGEEEKEGSnShRBCCCGECDNSpAshhBBCCBFmpEgXQgghhBAizEiRLoQQQgghRJhRWmttdQghhBBCCCHEf8hMehu66667rI4QMpE8Nojs8cnYOq5IH5/Vou3vV8Yb+aJtzJE+XinShRBCCCGECDNSpAshhBBCCBFmbPfff//9VoeIJDk5OVZHCJlIHhtE9vhkbB1XpI/PatH29yvjjXzRNuZIHq8sHBVCCCGEECLMSLuLEEIIIYQQYcZudYBwcNVVV/G3v/3N6hht5vLLL6d79+7Bn++88046d+583Mfef//9XHXVVfTq1au94oXMZZddxsiRI7n55psBaG1t5frrr6d3795tsgI8HH9PVq9eze9//3tmzZpFZmbmST33ySef5MILLyQrK4spU6bwyCOPkJycHKKkJy/Un6eVwvF3KdqUlJQwb948TNNk7NixTJgwwepIITVlyhTi4uIwDAObzcb06dOtjtSm5s6dy9q1a0lJSWHmzJkA+Hw+Zs2aRUVFBZ06deK2227D6XRanLRtHG+8r7zyCosXLw7+d/yKK65g0KBBVsZsM5WVlcyZM4eDBw+ilKKoqIgLLrggoj9jkCLdMq2trdhstpC8tsPhYMaMGW32em2R1TRNDCO0N25iY2PZs2cPzc3NOBwONmzYgNvtPqnXCOXnEgorVqygT58+rFixgssuu+yEn2eaJjfeeGMIk52+tvg8hTge0zR55pln+M1vfkNaWhpTp06loKCArKwsq6OF1H3N2LH0AAAVlklEQVT33RdWX8Tb0pgxY/jhD3/InDlzgtcWLFhA//79mTBhAgsWLGDBggVceeWVFqZsO8cbL8D48eO5+OKLLUoVOjabjauuuoqcnBwaGhq46667GDBgAEuXLo3YzxikSA9qbGzkd7/7HXV1dfj9fn76058yZMgQysvLeeSRRzjzzDPZunUrbrebX//61zgcjqNmoWtqapg6dSpz5syhvLycP/7xjzQ1NQFw7bXXcuaZZ7Jp0yZefvllEhMT2bdvH8OHD8fpdDJ+/HgAXnzxRVJSUrjgggvafHw7duzgr3/9K42NjSQnJ1NcXIzL5QJg+fLlPPnkk5imya9+9Styc3N55ZVXOHDgAOXl5aSlpZGfn8/27du57rrrAJg+fToXXXQRZ599Nk899RTbt2+nubmZoUOHBovFKVOmMGzYMDZu3Mg555zDqlWrePTRRwHYv38/jz/+ePDntjJw4EDWrl3L0KFDWbFiBSNGjGDLli0AbNu2jXnz5tHS0oLD4aC4uJiMjAyWLl3KqlWraGxsxDRNpk6dyrPPPsv27dtRSjFp0iSGDh0KBD6jtWvX4nA4uPPOO0lNTW3T/CejsbGRLVu2cN999/Hoo49y2WWXsWnTJl555RXi4uIoKyvj7LPPZvLkyRiGwVVXXcX555/Pxo0bue6663jppZfC/i7KqXye9913H9dccw09evQA4Le//S3XXXdd8OdwsWnTJt58883gXYFnnnmGXr16MWbMGKZMmcLo0aP59NNP8fv93H777WRmZtLY2Mizzz7Lnj17aG1t5Sc/+QlDhgyxeCQdz7Zt2+jatStdunQBYPjw4axZsybii/RI1rdvX8rLy4+6tmbNGg7vjTF69Gjuv//+iCngjjfeSOZyuYI1S3x8PJmZmXg8noj+jEGK9KCYmBjuuOMOEhISqKmp4Z577qGgoAAIFJS33HILN954I4899hgff/wxo0aN+sbXSklJ4Te/+Q0Oh4P9+/fzxBNPBG8t7ty5k5kzZ9K5c2fKy8uZOXMm48ePxzRNVq5cybRp0057LM3Nzdx5550AdO7cmdtuu41nn32WX//61yQnJ7Ny5UpefPFFiouLAWhqamLGjBls3ryZP/3pT8FbZ6WlpTz44IM4HA6WLl36je93xRVX4HQ6MU2TBx54gF27dpGdnQ1AUlJSsBDfuHEjX331FT169OD9999nzJgxpz3WrxsxYgTz589n0KBB7Nq1i/POOy9Y1GVkZPDAAw9gs9nYsGEDL7zwAnfccQcQ+Fx+//vf43Q6ef7550lISDjqlunhv6fevXtzxRVX8Pzzz7N48WImTpzY5mM4UWvWrCE/P5+MjAySkpLYsWMHEChAHnvsMTp16sTDDz/M6tWrGTp0KE1NTeTm5vKLX/zCsswn61Q+z/POO4+lS5fyy1/+kn379tHS0hJ2BfqJOPzvzsKFC3nzzTe58cYbee211+jXrx/FxcXU1dVx9913079/f+Li4qyO26F4PB7S0tKCP6elpfHll19amKh9PPzwwwCcf/75FBUVWZwm9Kqrq4OFXWpqKtXV1RYnCr2FCxeyfPlycnJy+MUvfhFRrR+HlZeXs3PnTnJzcyP+M5Yi/RCtNS+++CKff/45Sik8Hk/ww+7cuXPwf/I5OTlUVFR862u1trbyzDPP8NVXX2EYBvv37w/+WW5ubrA/vHPnzjidTnbu3El1dTU9evQgKSnptMfy9XaX3bt3s2fPHh588EEgcKv38C81wMiRI4HAN/P6+nrq6uoAKCgowOFwfOf7rVy5ksWLF9Pa2orX66W0tDRYpA8fPjz4uMLCQt5//32uvvpqPvroozb5QvJ12dnZVFRUsGLFCgYOHHjUn9XX1zNnzhzKysqAwOd02IABA4L/Mdu4cSO33npr8M8OX7fb7QwePBgI/B5s2LChzfOfjBUrVgTvugwfPpwPP/yQwYMHk5ubG5whPDzzPHToUAzDCN4R6ChO5fMcNmwYr776KldeeWXIvgy2h3POOQcI/K6tXr0agA0bNvDpp5/y5ptvAoEv5JWVlTIDLL7Tgw8+iNvtprq6moceeoiMjAz69u1rdax2o5RCKWV1jJAaN24ckyZNAuDll1/mueeeC07GRYrGxkZmzpzJL3/5SxISEo76s0j8jKVIP+TDDz/k/7d39zFNXW8cwL+UFgS7HwKlbjq1ii9THDjHS5y8yFhihhowkE62ySqE6Sy6KPNtimLQCUGDQevQFDCQTeccZqg456ZQXnSIguDbEDeCzZwVLAICQim/P0zvuLQWUbBQn09CQu89Pec5tJx77rnnntvY2IiEhARwuVxIpVK0t7cDeDLKrsPhcJjtlpaW0K1g2dHRwaQ5ceIE7OzskJSUhK6uLnzyySfMPmtra1a5AQEByMvLQ0NDA/z9/Qesfm+++SYzitIb3Ze8e6wcDgfdV+vU1VelUuH48ePYsWMH+Hw+ZDIZ62/RPQ8vLy8cPXoU06dPx/jx4/vlhMQQd3d3ZGVlIS4uDk1NTcz2H374AS4uLlizZg1UKhW2bt1qMM6nsbS0ZP42HA6H1cl/2Zqbm3H16lXU1tbCwsICWq0WAIzeJMTj8Qb8voCB0NfP09raGq6urigtLcX58+cH7Q1y3dsPgN2GAE9OCgH2d62rqwsxMTEYNWrUywvUDDk4OKC+vp55XV9fb/b3O+jqZ2dnBw8PD1RXV5t9J93Ozg5qtRr29vZQq9VmOx9fp/v0y4CAgH6fTmpqGo0Gu3btgo+PDzOIYe6f8dA7Yg+QlpYW2NnZgcvl4urVq72OlgOAk5MTM8XgwoULrLzs7e3B4XCgUCiYDpQhnp6eKC8vx+3btzFjxowXr4gBo0aNQmNjI6qqqgA8+aLfuXOH2V9cXAwAuHnzJmxtbfXOToEno/41NTXQarWoq6tDdXU1gCd1HTZsGGxtbdHQ0IDy8vKnxmFlZQU3NzfI5fIBPSHx9/dHaGgoa4UbXay6A5Wx6Tuurq44ffo081o33WUw0U252rdvH2QyGb799lsIhULcvHkT1dXVUKlU0Gq1OH/+PN566y1Th/tCnufzDAgIQEZGBpydnQft5V6BQAClUomOjg48evQIlZWVvb7Hzc0Np06dYjr3f//990CHaZacnZ1x9+5dqFQqaDQaFBcXM9MbzVFbWxtaW1uZ3ysqKvT+n8yRu7s78vPzAQD5+flmf/+GWq1mfi8pKcGYMWNMGE3/6urqQmpqKkaPHo358+cz2839M37lR9I7OzvB4/Hg7e2NxMRExMTEwNnZ+ZmWs1uwYAGSk5Px22+/sUYw586di127dkGhUMDNzc3oKC2Xy4WLiwuGDx8+YKOcXC4XMTExyMjIQEtLCzo7OxEYGMj8A1tZWWHt2rXo7OzEF198YTCPKVOmQCgUMjewjR8/HgAgEokgEomwatUqODo6YsqUKUZj8fb2RklJCdzc3Pq3kt04OjoavPk2KCgIMpkM2dnZRkecQ0JCIJfLERMTAw6Hg9DQUOasfbAoKipCUFAQa5uXlxfOnDmDiRMnIi0tjblx1NPT00RR9o/n+TwnTJgAGxubAT0ZfF66NkcgEGDWrFmIiYmBUChk/qeMCQ0NxcGDB/HVV1+hq6sLQqFwyC9HaQqWlpaIiIjA9u3bodVq4e/vb1Ydmp4ePnyInTt3Anjy/fP29h6wQSFT2b17N65fv46mpiYsW7YMYrEYwcHBSE5OxtmzZ5nl+cyFofpeu3YNNTU1sLCwgJOTEz7//HNTh9lv/vzzTygUCowdO5a55y4sLMysP2OAnjiKmpoa7N+/Hzt27DBJ+VqtFuvWrcPq1avxxhtvmCSGlyknJwctLS1YtGiRqUMxSz1XDHlVPXjwAFu3bkVycvKgm+Jj6jaHEELI0PBKj6T/+uuvOHXqFCQSiUnKVyqVSEhIgKen5yvRQU9KSsK9e/ewefNmU4dCzFh+fj4OHz6M8PDwQddBN3WbQwghZOh45UfSCSGEEEIIGWwG1zATIYQQQgghhDrphBBCCCGEDDbUSSeEEEIIIWSQoU46Ic9JLBYzT7vsKS8vD7Gxsf1eZkFBAbZt29ZruiNHjiAlJaXfyyeEEHNgrP1+EYsXL8a9e/eMplGpVBCLxSZ9IB4ZGqiTToY8qVSKsLAwNDY2sravXbsWYrEYKpXqhcuIi4vD77///sL5vCgfHx9s2rTJ1GEQQki/kUqlqKioYG0bqIGOgZaVlYWRI0eaOgxiJqiTTsyCUChEUVER87q2thaPHz82YUSEEEIGGxq9JkMJddKJWfD19YVCoWBe5+Xlwc/Pj5WmpaUFe/fuRWRkJJYvX46ffvoJWq2WSR8bG4vMzEwsWbIEUqkUZWVlAIBDhw7hxo0bSE9Px+LFi5GWlsbkWVFRgZUrV0IikUAul8PQiqZyuRyZmZmsbYmJiThx4oTBuojFYuTm5iI6OhqRkZHIysrSi1Pnzp07iI+Px5IlSxAVFYXs7Gy9/DQaDXbv3o2dO3dCo9HoXeaVyWQ4fPgwgCcPQ1q2bBmys7MRGRkJqVSKgoICg3ESQsjLolQqERcXB4lEgtWrV6O0tJTZ1/NKZ892UiwW45dffsHKlSuxcuVKVr7V1dWIiopi2lgA+OOPP5inWvYkk8lw4MABxMfHIzw8HFu2bMH9+/dZZena1/b2dmRmZmL58uX47LPPEBsbi/b2dr08L1y4AKlUitraWlZ7DPzXJutIpVIcO3YMq1atwpIlS7Bv3z6DeRLzQJ10YhYmTZqElpYWKJVKaLVaFBcXw8fHh5UmPT2d6ajHxcVBoVAgLy+P2V9dXY1Ro0YhLS0NQUFBSE1NRVdXF8LCwjB16lREREQgKysLkZGRzHsuX76MHTt2YOfOnTh//jyuXLmiF9ucOXNQVFTEHAQaGxtRWVkJb2/vp9bn4sWLSEhIQGJiIkpLS3Hu3Dm9NK2trYiPj8eMGTOwf/9+pKSk4O2332alaW9vR1JSEng8HlavXg0ut/fnlzU0NKCpqQmpqamQSqU4cOAA/vnnn17fRwghA0Gj0SAxMRGurq6Qy+WIiIhASkpKn9qlixcv4ptvvkFycjJr+8SJE8Hn81ltt0KhgK+v71PzKiwsREhICNLS0iASiZ56/09mZib++usvbNu2DRkZGfj0009hYWHBSnPu3Dl89913iI2NxdixY5+pLoWFhdi4cSP27NmDu3fvGhycIeaBOunEbOhG0ysqKjB69Gg4ODgw+7RaLYqKivDxxx/DxsYGQqEQ8+fPZ42+CwQCfPDBB+BwOPDz84NarcbDhw+NlhkcHIzhw4dDIBDAxcUFNTU1emkmTpwIW1tbXL16FQBQXFwMFxcXjBgx4qn5BgUFgc/nQyAQIDAwkDWVR+fSpUsYMWIEFixYACsrK9jY2GDSpEnM/tbWVmzfvh0jR47E8uXL+/T0zY8++gg8Hg/Tpk3DO++8g+Li4md+LyGE9FVSUhIkEgnzI5fLmX23bt1CW1sbgoODweVyMX36dMycOROFhYXPnP/ChQvB5/NhZWWlt8/Pz4+5Ytjc3IwrV64YHUSZOXMmpk2bBh6Ph7CwMFRVVaGuro6VRqvV4ty5c5BIJHBwcACHw8GUKVPA4/GYNCdPnkROTg7i4uLw+uuvP3Nd5s6dC4FAAD6fj4ULFxo8PhDz0PuwGiFDhK+vL7Zs2QKVSqU31aWxsRGdnZ0QCATMNicnJzx48IB53b3TbG1tDQBoa2szWmbP9zwtvZ+fHxQKBVxdXVFQUIAPP/zQaL6Ojo6sONVqtV6a+vp6ozco3bp1C52dnfjyyy/1Rm+MGT58OIYNG9Zr+YQQ0l/WrFkDV1dX5nVeXh4zhUWtVkMgELAGGnq2373p3qb25Ovri1WrVqGtrQ3FxcWYOnUq7O3tnymvYcOGgc/nMzHqNDU1oaOjw2jn+/jx4wgJCTEamyHGjmPEvNBIOjEbTk5OEAqFKCsrg6enJ2vf//73P1haWrJGO+rq6lij7cb0pZNriI+PD0pLS1FTUwOlUqkXX0/19fWsOA0dMBwdHY2uXOPq6org4GDEx8ejoaGB2W5tbc26qbb7PgB49OgR62TjaeUTQsjLYG9vj7q6Ota88e7td29tGmC8DXdwcMDkyZNRUlKCgoICvamSPXVvn9va2tDc3KzXRr722mvg8XhGl3ncuHEjsrOzceHCBWbbs9TleY9jZOihTjoxK8uWLcPmzZtZI8EAwOFwMGvWLBw6dAitra24f/8+Tpw40WtjrGNnZ9fr2rfGODo6wtnZGXv37oWXl5fBS67d5eTkoLm5GXV1dcjNzcV7772nl+bdd9+FWq3GyZMn0dHRgdbWVty6dYuVJigoCLNnz0Z8fDyzRKVIJEJhYSG0Wi3Ky8tx/fp1vbyPHDkCjUaDGzdu4PLly5g1a9Zz150QQl7EpEmTYG1tjZycHGg0Gly7dg2XLl3C7NmzATxp00pKSvD48WP8+++/OHv2bJ/L8PX1xc8//4za2lp4eXkZTVtWVoabN29Co9Hg8OHDmDx5Mmt0G3hyzPH390dmZiYePHgArVaLqqoqdHR0MGnGjBmDr7/+GmlpacyNsCKRCGVlZWhubkZDQwNyc3P1yj99+jTq6+vR3NyM7Oxsap/NGE13IWbF2KXFiIgIpKenIzo6GlZWVggICIC/v/8z5RsYGAiZTIYzZ87Ax8cHERERfY7Nz88Pe/fuhUQi6TWtu7s71q9fj5aWFsyZMwfvv/++XhobGxts2rQJBw8exNGjR8HlcjFv3jzWvHQACA0NhUajQXx8PLZs2QKJRAKZTIbTp0/Dw8MDHh4erPQjRowAn8/H0qVLYWVlhaioKIwePbrP9SWEkP7A5XKxbt06yOVyHDt2DA4ODoiOjmbapXnz5uH27duIiorCuHHj4O3tjcrKyj6V4enpCblcDg8PD2a649PMnj0bP/74I6qqqjBhwgSsWLHCYLrw8HB8//332LBhA9ra2iASibBx40ZWGpFIhPXr1yMhIQGWlpbw9fVFZWUlpFIpnJycMGfOHL2VwLy9vbFt2zao1Wq4u7sjJCSkT3UlQ4dFl6E14wgh/e769evYs2cP9u3bZ/TSq1gsRkpKSp9uJOov165dw549e5CamvrSyyaEEFNasWIFoqKiWHPje5LJZHB0dMSiRYteYmT/kUqlWLp0qdEYifmg6S6EvAQajQa5ubkICAh44fnthBBC+pduXvj06dNNHAkh/6HpLoQMMKVSiQ0bNmDcuHEIDAw0dTiEEEK6iYuLg1KpRHR0dJ+WqiVkoNF0F0IIIYQQQgYZOmUkhBBCCCFkkKFOOiGEEEIIIYMMddIJIYQQQggZZKiTTgghhBBCyCBDnXRCCCGEEEIGGeqkE0IIIYQQMsj8HzJE718sM3mgAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "fb65c5c16cd74979ed1713b9fa524e82632999a3",
        "_cell_guid": "7c4b67cd-2015-4cba-800b-79a39679692f",
        "id": "65WdlhhCkEut"
      },
      "source": [
        "Trips taken by Vendor 1 lasted for greater trip duration as compared to Vendor2. \n",
        "\n",
        "But, Vendor 2 took greater trips(from the 2nd left graph) as compared to the other vendor and with varying passenger count as well.\n",
        "\n",
        "\n",
        "At the early hours, both the vendors took the same no of trips. But after 7 or 8 AM, Vendor 2 took larger trips as compared to Vendor 1."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "26edaa394644c688ade958b570f1108c2879a913",
        "_cell_guid": "ccf41841-df0d-43ae-8193-934ce95909fb",
        "id": "DX1Qt2IYkEut"
      },
      "source": [
        "*Checking trips wrt storing or not storing the trip and then forwarding*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "a8061c2a57e3301ad5ab029ac24fd89e899c4cca",
        "_cell_guid": "6eefd015-d913-4e74-ab13-7b107ac0005f",
        "id": "zi_WT_dhkEuu",
        "outputId": "63cd20f1-7ea7-4f47-be2b-b70f92ea0d43",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        }
      },
      "source": [
        "plt.figure(figsize=(12,7))\n",
        "\n",
        "store=train.groupby('store_and_fwd_flag').agg({'id':'count'}).reset_index()\n",
        "sns.barplot(x='store_and_fwd_flag',y='id',data=store)\n",
        "plt.xlabel('Whether the trip was stored or not')\n",
        "plt.ylabel('No of trips')\n",
        "plt.title('Trips on the basis of store_and_fwd_flag')\n",
        "pass\n",
        "\n",
        "print(train['store_and_fwd_flag'].value_counts())\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "N    1215322\n",
            "Y       6792\n",
            "Name: store_and_fwd_flag, dtype: int64\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "1cb40afd980185038ad8421e22bbc9e8e2c2884f",
        "_cell_guid": "6d149c72-fb1a-41a2-ad26-1f6df7ef1151",
        "id": "GDQxP_7ikEux",
        "outputId": "ee83252f-aa94-4fe8-846b-bcfbd17fae2b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        }
      },
      "source": [
        "plt.figure(figsize=(12,7))\n",
        "store=train.groupby('store_and_fwd_flag')['trip_duration'].mean()\n",
        "store.plot(kind='bar',x='store_and_fwd_flag',y='trip_duration')\n",
        "plt.xlabel('Whether the trip data was stored or not')\n",
        "plt.ylabel('Trip duration(in sec)')\n",
        "plt.title('Trip duration based on store_and_fwd_flag')\n",
        "pass"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "aa79c054f874cf8fb49636a18527c196935ce0eb",
        "_cell_guid": "4179982b-dc36-46e1-9cea-bec84b7b95b4",
        "id": "sNHpQRFWkEuz",
        "outputId": "e79c3dbd-02e7-40a6-91fc-b11e76410d04",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 319
        }
      },
      "source": [
        "#Passenger count as per hourly pickup\n",
        "plt.figure(figsize=(19,15))\n",
        "hourly_passenger=train.groupby(['hh_pickup','passenger_count']).size().unstack()\n",
        "hourly_passenger.plot(kind='bar',stacked=True,legend=False)\n",
        "plt.xlabel('Hour dist(0-23)')\n",
        "plt.ylabel('No of counts')\n",
        "plt.title('Passenger count as per hourly pickup')\n",
        "plt.legend(loc=\"upper left\")\n",
        "pass\n",
        "\n",
        "#Clearly visible in the graph pattern distribution on hourly basis according to passenger count."
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1368x1080 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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98poGLQ05fPiwEhERodjb2yu2traKn5+f8s033+iXf/PNN0rfvn0VKysrxcXFRZk0aVK1QfxXXnlFcXd3V9q2bas8+OCDyrJly6oNylcelFUURfn+++8VQPn999/1bVOnTlXat2+vALUOqs+ePVvp0KGDYmdnp9x1113KJ598UmVbxrxflV0dlP/ggw+UIUOGKNbW1oqHh4fy8ccfV1nv3LlzyqRJkxR3d3elTZs2iru7uxIREaFkZmYqivK/Qfn//ve/Bvd1lTEDyxUVFcprr72meHh4KGq1WunWrZuSkJBQJeaff/5RIiMjFUdHR6V9+/bKSy+9VOOgfE2fB0Pt06ZNU9RqtXLq1Kk6n8fV/3uLFi1S3NzcFFtbW2XUqFHKuXPn9OvU9P5v2bJFCQoKUmxsbBR7e3slNDRUOXbsWJVtXnXhwgUlLCxM6d27t3LmzBmltLRU/1lxcHBQoqOjlRdffLHaoHxdeTVVKkWROzaKGyMsLAwnJye+/PLLxk6lxTpx4gTdunXj+++/Z/DgwY2dTqMbM2YMly9frnG86Frjxo3j5MmTpKSkmCEz4zXVvIwhg/LCJA4ePEhmZiYDBw6ktLSUDz/8kO3bt+sPQQlxIxUUFPDTTz+xYcMGtm3b1tjptFpSUIRJqFQq3nrrLaZMmUJFRQU9evRgw4YNDB8+vLFTE61AQEAA+fn5PP/889VOVxbmI4e8hBBCmISc5SWEEMIkzHbIa+PGjaSmpqJSqejSpQvR0dH8/fffLFmyhPPnz+Pp6cnkyZNRq9VcvnyZZcuWcfz4cdq1a8e0adP0V7xu2LCB1NRULCwsGD9+vP4K7qysLFavXk1FRQXDhg0jIiLCXE9NCCEEZuqh6HQ6Nm/eTHx8PIsXL6aiooL09HQ++ugj7r77bpYuXUrbtm1JTU0FIDU1lbZt27J06VLuvvtuPv74YwBOnjxJeno6b7zxBrNmzWLVqlVUVFRQUVHBqlWreOGFF0hISGDXrl01XjAmhBDixjFbD6WiooLS0lIsLS0pLS3F0dGR7Oxspk6dClyZpnrt2rXccccd7N27l/vvvx+AoKAg3nvvPRRFISMjg0GDBtGmTRs6dOiAm5ubfg4oNzc3XF1dgSszwGZkZFSZzsOQa69avcrFxaXKnFjGakicOfclcRInca0n7kbsq7bZFcxSULRaLSNGjOCpp57CysqKPn364OnpiZ2dnX56D61Wq5/vX6fT4ezsDFyZVsTOzo7z58+j0+nw8fGpst2rMVfXv/rvaye9uyolJUV/fnd8fLzBm+eo1eoG3VinIXHm3JfESZzEtZ44s+dY74gGKCoqIiMjg+XLl2NnZ8cbb7xBVlaWOXZdTXh4eJWbKhmqws39V4TESZzESZy5eyhmGUM5ePAgHTp0wN7eHrVazYABAzh8+DDFxcX6CfV0Op1+dlutVquf+6a8vJzi4mLatWtXpb1yzLXt+fn5VWbKFUIIceOZpYfi4uJCTk4OJSUlWFlZcfDgQby8vPD19WXPnj0EBweTlpZGYGAgcGVGz7S0NLp3786ePXvw9fVFpVIRGBhIYmIi99xzDwUFBZw+fRpvb28UReH06dPk5eWh1WpJT0+vche8+lAUhUuXLnHmzBlKSkrqHd+QuPrEKIqChYVFvWfnFUKIG80sBcXHx4egoCBmzpyJpaUlHh4ehIeH07dvX5YsWcJnn31Gt27dCAsLA67MAbVs2TImT56MRqNh2rRpAHTp0oWBAwcyY8YMLCwsmDBhgv7GO48//jjz58+noqKCoUOH0qVLlwbleunSJdq0aYO1tXWD7j+hVqvrHVffmLKyMi5dulTf1IQQ4oYy21leY8aMYcyYMVXaXF1dWbhwYbV1rays9FNvX2vUqFGMGjWqWnvfvn3p27fvdedZUVGBWt20Z6RRq9UN6j0JIcSNJFfKX8OYeyg0Bc0lTyFE6yEFpQmaMWMGfn5++kOAQgjRHDTtYztNQPkTI+u3fh3LLVd+Xec2xowZw/jx4/UXfQohTOfz7EcMLnvA90MzZtLySA+lCQoKCsLR0bGx0xBCiHqRHooQQhhBejZ1kx6KEEIIk5CCIoQQwiSkoAghhDAJGUNpgqKjo9m9ezc6nY5+/frx7LPP8tBDDzV2WkK0CJOtDd/WIs+MebREUlDqYMxpvpWp1WrKysqua58rVqy4rnghhGgMUlCEEMII0rOpm4yhCCGEMAkpKEIIIUxCCooQQgiTkIIihBDCJKSgCCGEMAkpKE3MX3/9xejRowkNDWXo0KEkJSU1dkpCCGEUOW24Dvd+/JtJt/fVwz1qXa5Wq3nppZfo3bs3RUVFDB8+nJCQELp3727SPIQQwtTMUlBOnTpFQkKC/nFeXh5jxoxhyJAhJCQkcPbsWdq3b8/06dPRaDQoisLq1avZv38/1tbWREdH4+npCUBaWhrr168HrtwOODQ0FIDjx4+zfPlySktLCQgIYPz48c3yroaurq64uroCoNFo8PHxITc3VwqKEK1Mc5zd2CwFxd3dnUWLFgFX7tk+ceJE+vfvT3JyMr179yYiIoLk5GSSk5OJjIxk//795ObmkpiYSE5ODklJSSxYsICioiLWrVtHfHw8ADExMQQGBqLRaFi5ciUTJ07Ex8eHhQsXkpWVRUBAgDme3g3z3//+l19++aXZPw8hWrPmWBgayuyHvA4ePIibmxvt27cnIyODuLg4AIYMGUJcXByRkZHs3buXkJAQVCoV3bt358KFCxQUFJCdnY2fnx8ajQYAPz8/srKy8PX15eLFi/pf8SEhIWRkZDTrL+ILFy7wxBNP8PLLL9OuXbvGTkeIFmP2po4Gl02ZYsZEWiCzF5Rdu3YRHBwMQGFhIU5OTgA4OjpSWFgIgE6nw8XFRR/j7OyMTqdDp9Ph7Oysb9dqtTW2X12/JikpKaSkpAAQHx9fZT8AZ86cQa2+8rJc/duUDG2zcvvly5d58sknGT16NCNH1nwLYmtra9RqdbX8jc1B4iRO4qqrLX52ouFCNHduw/bb0HyNjTP7e1DviOtQVlbGvn37GDt2bLVlKpXKLGMe4eHhhIeH6x+fO3euyvKSkhIsLS1NMsljTWraZuV9KYrC1KlT8fLyIioqymAOJSUllJWVVcvfGC4uLhIncRJXg4bGN9W4G/Fauru7G4wza0HZv38/3bp1098v3cHBgYKCApycnCgoKMDe3h640vOo/GTy8/PRarVotVoOHTqkb9fpdPTq1QutVkt+fn619ZujjIwMvvzyS3r27Mntt98OXBkrGjZsWCNnJoQwp+Y4GaVZC0rlw10AgYGB7Nixg4iICHbs2MGtt96qb9+yZQvBwcHk5ORgZ2eHk5MT/v7+fPrppxQVFQFw4MABxo4di0ajwdbWliNHjuDj48POnTsZPny4SXKu6zTfa11vz6Z///789ddfDY4XQtSum+ujjZ1Ci2W2gnLp0iV+/vlnnnzySX1bREQECQkJpKam6k8bBggICCAzM5MpU6ZgZWVFdHQ0cOU02vvuu4/Y2FgARo8erR+gj4qKYsWKFZSWluLv79+sB+SFEE1PQwuRuXsajXlWmdkKio2NDe+9916Vtnbt2jFnzpxq66pUKqKiomrcTlhYGGFhYdXavby8WLx4sWmSFUIIUW8y9YoQQgiTkIIihBDCJKSgCCGEMAmZHFIIIVqQxjzdWApKE3Pp0iXuu+8+SkpKKC8v5+677+bZZ59t7LSEEKJOUlDq8J/P/zbp9kY84Fjrcmtra7744gvatm3L5cuX+b//+z+GDh1Kv379TJqHEEKYmhSUJkalUtG2bVvgyjQtly9fbpbT8AvRVCWV5RpcNoLaf/CJ2klBaYLKy8sZPnw4J06cYNy4cfTt27exUxKi1TN3IWqOsyJLQWmCLC0t+e677ygsLGTChAn89ttv9OhRvylghBBNQ3MsDA0lpw03YQ4ODgQHB5OWltbYqQghRJ2kh9LE5Ofno1arcXBw4OLFi+zcuVM/l5kQ4n9a050QmwspKE3MmTNnmDZtGhUVFVRUVDBixAj9NPZCiNajOc6KLAWlDnWd5nut652+vlevXnz77bcNjhfieskvf9NqjoWhoWQMRQghhElID0UIIVqQxjyrTAqKEKJZao63yG3p5JCXEEIIk5AeihBNnAySi+bCbAXlwoULvP322/z3v/9FpVLx1FNP4e7uTkJCAmfPntXfU16j0aAoCqtXr2b//v1YW1sTHR2Np6cnAGlpaaxfvx6AUaNGERoaCsDx48dZvnw5paWlBAQEMH78eJkDS7RqDS1EciipeWvMs8rMVlBWr16Nv78///73vykrK6OkpIQNGzbQu3dvIiIiSE5OJjk5mcjISPbv309ubi6JiYnk5OSQlJTEggULKCoqYt26dcTHxwMQExNDYGAgGo2GlStXMnHiRHx8fFi4cCFZWVkEBASY6+mZXHl5OXfddRdubm588MEHjZ2OEHWSnpQwS0EpLi7m119/5emnn76yU7UatVpNRkYGcXFxAAwZMoS4uDgiIyPZu3cvISEhqFQqunfvzoULFygoKCA7Oxs/Pz80Gg0Afn5+ZGVl4evry8WLF+nevTsAISEhZGRkmKSgJCYmXvc2Kpti5GkWSUlJ+Pj4cP78eZPuXwhhXg2dVLI5zopsloKSl5eHvb09K1as4I8//sDT05Nx48ZRWFiIk5MTAI6OjhQWFgKg0+lwcXHRxzs7O6PT6dDpdDg7O+vbtVptje1X169JSkoKKSkpAMTHx1fZD1y5Ul2tvvKyXP3blAxts3L7qVOnSE1NZdq0abz99ts1xlhbW6NWq6vlb2wOEtd84ypraHytcUfNvL9rGP26NHKeTTfO8D2cjN1fgz/T9Y5ogPLycn7//Xcef/xxfHx8WL16NcnJyVXWUalUZhnzCA8PJzw8XP/43LlzVZaXlJRgaWl53Ve8G1LTNq/d16xZs5g1axZFRUUoilJjTElJCWVlZdXyN4aLi4vENeO4yhoaX1tcBzPv71rGvi6NnWdLjqvtPXB3dzcYZ5aC4uzsjLOzMz4+PgAEBQWRnJyMg4MDBQUFODk5UVBQgL29PXCl51H5yeTn56PVatFqtRw6dEjfrtPp6NWrF1qtlvz8/GrrN0ffffcdLi4u+Pn5kZ6e3tjpiCZABsmFOZhiDMwsBcXR0RFnZ2dOnTqFu7s7Bw8epHPnznTu3JkdO3YQERHBjh07uPXWWwEIDAxky5YtBAcHk5OTg52dHU5OTvj7+/Ppp59SVFQEwIEDBxg7diwajQZbW1uOHDmCj48PO3fuZPjw4eZ4aia3d+9evv32W1JTUykpKeH8+fNMnjyZpUuXNnZqoplp6YWoNd1npLkw21lejz/+OImJiZSVldGhQweio6NRFIWEhARSU1P1pw0DBAQEkJmZyZQpU7CystJP367RaLjvvvuIjY0FYPTo0foB+qioKFasWEFpaSn+/v7N9gyv2NhY/fNLT0/n7bfflmLSghj6FdgSzoJq6QVM1M1sBcXDw0N/um9lc+bMqdamUqmIioqqcTthYWGEhYVVa/fy8mLx4sXXn6gQQjRjjXl2mFwpXwdjT/O9ypSD+YMGDWLQoEEm2ZYQxpJDSaKhpKAIIZql1nSfEXMwxSFLKSiiVZOru4UwHSkoQpiRoV+BMmgtWgIpKKJFkJ6G6cihJNFQUlCEaOIaOkgug+vC3KSgCNEA0iOqTgqYkILSBA0YMACNRoOFhQVqtZrNmzc3dkotllyMJ4TpSEGpQ4ejsSbdXp73QqPWW7t2bbOdj0yYloxp1Kw5Tu/e0klBES2C9DSqk0IkzE0KShOkUql46KGHUKlUREZGEhkZ2dgpCVGn5lLA1qc9b3jhw1+bL5EmxhRjYEYVlB9++AEPDw86d+7MqVOneOedd7CwsCAqKopOnToZtydhtA0bNtCxY0fOnTvHgw8+iLe3N0FBQY2dlmgl5FCSaCijCsrnn3/OvHnzAPjggw/w8vLCxsaGpKQkXnrppRuaYGvUseOVXwouLi7cddddZGVlSUFpYhp6iM3Qr8DWfBZUczljTno2dbMwZqV//vkHR0dHSktLOXz4MA899BCjR4/mxIkTNzi91qe4uFh/v5fi4mJ27Amebj4AACAASURBVNjBzTff3MhZCSFE3Yzqodjb25Obm8uff/6Jl5cXbdq0oaSk5Ebn1iqdPXuWCRMmAFdunRwREcHQoUMbOSshREtnijEwowrKfffdx8yZM7GwsNDfBOvgwYN07dr1uhNo6ow9zfeq652+vmvXrqSkpDQ4XjRtDflPK2MaorkwqqCEhoYycOBAAKytrQHw8fFh2rRpNy4zIcygJV/dLYVImJtRBeX555/ntddeq9Lm4OBATExMjXdhrMnTTz+NjY0NFhYWWFpaEh8fT1FREQkJCZw9e1Z/C2CNRoOiKKxevZr9+/djbW1NdHQ0np6eAKSlpbF+/XoARo0aRWhoKADHjx9n+fLllJaWEhAQwPjx41GpVMa+DqKZa8mFobloaAGTa4haDqMKSm5u9Q+KoiicOXOmXjt76aWXsLe31z9OTk6md+/eREREkJycTHJyMpGRkezfv5/c3FwSExPJyckhKSmJBQsWUFRUxLp16/RFLCYmhsDAQDQaDStXrmTixIn4+PiwcOFCsrKymu195YX5NJdrJ4RoDmotKMuWLQOgrKxM/++rzp49S5cuXa5r5xkZGcTFxQEwZMgQ4uLiiIyMZO/evYSEhKBSqejevTsXLlygoKCA7Oxs/Pz80Gg0APj5+ZGVlYWvry8XL16ke/fuAISEhJCRkSEFRQghzKjWguLq6lrjv1UqFTfffLN+XMVY8+fPB+D2228nPDycwsJCnJycAHB0dKSwsBAAnU6Hi4uLPs7Z2RmdTodOp8PZ2VnfrtVqa2y/ur5oPczd05BDbEJUV2tBuf/++4ErA/D+/v7XtaN58+ah1WopLCzklVdewd3dvcpylUplljGPlJQU/VlU8fHxVQoXwJkzZ1Crr7wsV/+ur4bE1TfG2toatVpdLX9j99Xy4v42uKT2bTQ0zrDa4pLKfquxfbyLt8n31Wzijpp3f7UdqL8RcbVpSnGGPptg/OfTqG8xf39/Tp06xYkTJ7h06VKVZWFhYUbt6OrMuQ4ODtx6660cPXoUBwcHCgoKcHJyoqCgQD++otVqOXfunD42Pz8frVaLVqvl0KFD+nadTkevXr3QarXk5+dXW78m4eHhhIeH6x9X3g9ASUkJlpaWDT79tyFx18YUFhby7LPPcvjwYVQqFYsXLyYwMLBanmVlZdXyN4aLi0uLjrtWQ7dhzrjmkOONiutg5v1J3PXFXdsZqMyogrJ+/Xq+/PJLunbtqj9t+CpjCsqlS5dQFAVbW1suXbrEzz//zOjRowkMDGTHjh1ERESwY8cObr31VgACAwPZsmULwcHB5OTkYGdnh5OTE/7+/nz66af6K8kPHDjA2LFj0Wg02NracuTIEXx8fNi5cyfDhw835qnVqbZpIRrCmKkk5syZw9ChQ1m5ciWlpaVcvHjRpDmI/2nomUkymC+M1ZqmbDGqoGzatIkFCxY0+ELGwsJCXn/9deDK1d+DBw/G398fLy8vEhISSE1N1Z82DBAQEEBmZiZTpkzBysqK6OhoADQaDffddx+xsVfuUTJ69Gj9AH1UVBQrVqygtLQUf3//Zjsg/88///Djjz+yZMkSAKysrLCysmrkrJo+ueai+ZLxqJo1x0JkVEGxsrK6rlmFXV1dWbRoUbX2du3aMWfOnGrtKpWKqKioGrcVFhZWY6/Iy8uLxYsXNzjHpuLPP//E2dmZ6dOnc+jQIfz8/Jg7dy52dnaNnZoQQtTKqMkhH3jgAd577z0KCgqoqKio8keYVnl5OQcPHuTRRx/l22+/xc7Ortop20II0RQZ1UNZsWIFANu2bau27PPPPzdtRq1cx44d6dixI3379gXg7rvvloIiWjQZj2o5jCoo8oVmPh06dMDd3Z2jR4/i7e3NDz/8oL9gUzQdMmYjRHVGFZT27dvf6DxEJfPmzWPy5MlcvnyZm266iTfeeKOxUxJCiDoZVVCWLl1q8KLDZ555xqQJNTX1vWPc9U5fD3DLLbewefPm69qGEEKYm1EFxc3Nrcrjv//+mz179nDbbbfdkKSEEEI0TGOebmxUQbk6BUtlYWFhrF271uQJCSGEaJ6MOm24Jh4eHvz666+mzEUIIUQzZlQP5ZdffqnyuKSkhF27dtG5s+Eb4wghhDHkjLmWw6iC8tZbb1V5bGNjQ9euXZk6deoNSUq0XrXNnVbfEySEEOZlVEFZvnz5jc6j0V39Iuvt9ChuKq8qy7S2no2RkhCNornMIdVc8mxNjL4JR1FREfv27UOn06HVaunXr59+YkZhWklJSXzyyScoisLYsWN54oknGjslIYSok1EF5ciRIyxcuJBOnTrh4uJCZmYma9asITY2tsVfxX3L4QvAQZNt75R/71qX//bbb3zyySd88803tGnThocffpjw8HC6detmshxE8yK/xEVzYVRBWbNmDVFRUQQHB+vb0tPTWb16NQsXLrxhyZnTZOsrJxictrDFWlV5uvgLZs0jJyeHgIAAbG1tAQgKCmLz5s36KfxbuqvvQ03yzJhHSyCFSJibUQXl9OnT1e4fHxQUxMqVK29IUq1Zjx49ePXVV9HpdNja2pKamkqfPn0aO60WS750hTAdo6+UT09PZ/Dgwfq23bt34+rqesMSa618fHx4+umnGTt2LHZ2dvj6+mJh0eDLhVoNKQyNT94DYVRBGTduHPHx8WzevBkXFxfOnj3L6dOniYmJudH5tUoPPfQQDz30EAALFy6kY0fDd7QTzYvBL135whUtgFEF5eabb2bp0qVkZmZSUFBAv3796Nu3r5zldYOcO3cOFxcX/vrrLzZv3sx//vOfxk5JCCHqZFRB0el0WFlZERISom8rKirSn0JsrIqKCmJiYtBqtcTExJCXl8eSJUs4f/48np6eTJ48GbVazeXLl1m2bBnHjx+nXbt2TJs2jQ4dOgCwYcMGUlNTsbCwYPz48fj7+wOQlZXF6tWrqaioYNiwYURERNTndWhSnnjiCQoKClCr1cyfPx8HB4fGTkkIIepkVEFZtGgRTz31VJUeiU6n4+2332bBggVG72zTpk106tSJixcvAvDRRx9x9913ExwczLvvvktqaip33HEHqamptG3blqVLl7Jr1y4+/vhjpk+fzsmTJ0lPT+eNN96goKCAefPm8eabbwKwatUqZs+ejbOzM7GxsQQGBppkapi8Hk6U2Ri/HVNMX79hw4brim/OZm8yfHhvyhQzJiKEqDejRntPnTrFTTfdVKXtpptu4q+//jJ6R/n5+WRmZjJs2DAAFEUhOzuboKAgAEJDQ8nIyABg7969hIaGAlfOJvvll19QFIWMjAwGDRpEmzZt6NChA25ubhw9epSjR4/i5uaGq6srarWaQYMG6bdlrNmbOjJ7U0ey/rLlr8I2Vf4IIYSom1E9FHt7e3Jzc6vcFyU3N5d27doZvaM1a9YQGRmp752cP38eOzs7LC0tAdBqteh0OuBK78fZ2RkAS0tL7OzsOH/+PDqdDh8fH/02K8dcXf/qv3NycozOTTQdzeX+4nJGk2hpTPGZNqqgDB06lMWLF/Pggw/i6upKbm4un3/+OWFhYUbtZN++fTg4OODp6Ul2drZRMTdKSkoKKSkpAMTHx+Pi4lJnjFpt9Aw1DVq/ITHW1tao1Wqj8q9pX0037m+DS2rbxplattgc4ppDjjcqrjZNKU+Jq5tR32IRERGo1Wo+/PBD8vPzcXFxYejQodxzzz1G7eTw4cPs3buX/fv3U1paysWLF1mzZg3FxcWUl5djaWlZZYBfq9WSn5+Ps7Mz5eXlFBcX065dO337VZVjKrfn5+cbPFkgPDyc8PBw/eNz584B//tlrLFRsG5TtedVnzGRhoyhNCTm0qVLlJWV6fOvDxcXl2YRd62GbqM5xDWHHCVO4gDc3d0NrmdUQbGwsGDkyJGMHDmyQcmMHTuWsWPHApCdnc1//vMfpkyZwhtvvMGePXsIDg4mLS2NwMBAAPr160daWhrdu3dnz549+Pr6olKpCAwMJDExkXvuuYeCggJOnz6Nt7c3iqJw+vRp8vLy0Gq1pKenM6WBI7hF5xWcO5Shtqx/L8NcysrK5GJHIUST06jfmg8//DBLlizhs88+o1u3bvpDaGFhYSxbtozJkyej0WiYNm0aAF26dGHgwIHMmDEDCwsLJkyYoP9iffzxx5k/fz4VFRUMHTqULl26NCinU3+ogGI07VSgUgFgZWNVe1Al1tbWlJSU1Guf9YlRFAULCwtsbGzqtY/mQm62JETzZfaC4uvri6+vLwCurq41Ti5pZWXFjBkzaowfNWoUo0aNqtbet29f+vbta4IMVf+/qPzPzb3sjI5uyOEdUx0SEkKIxiTHTYQQQpiEwR5KQkIC06dPB2D79u0MHTrUbEk1BjnUIoQQ18dgD+XAgQMoigJcuYZECCGEqI3BHkqPHj2YPXs2HTt2pLS0lGXLltW43jPPPHPDkhNCtHxykWjLYbCgzJgxgz179nDu3DlUKpXc+0QIIUStDBaUyrMLl5WVcf/995stKSGEEM2PUacNjxkzhtOnT7Nr1y791enBwcFy4ychhBB6Rp02vHfvXmJiYvjrr7/QaDScOnWKmJgY9u7de6PzE0II0UwY1UP59NNPee6557jlllv0bdnZ2bz33nv66VKEEEK0bkb1UHQ6HT179qzS1qNHjyoTMgohhGjdjCooHh4e1e5rvnHjRjw8PG5ETkIIIZohow55RUVF8eqrr7J582acnZ3Jz8/HysqKmTNn3uj8RCsj1yQI0XwZVVA6depEQkICOTk5+rO8vL29G3QjKSGEEC2T0RXB0tKSHj163MhchBBCNGMy27AQQgiTkIIihBDCJKSgCCGEMAmjx1CKiorYt2+fflC+X79+aDSaG5lbs/B59iMGlz3g+6EZMxFCiMZlVEE5cuQICxcupFOnTri4uJCZmcmaNWuIjY2le/fudcaXlpby0ksvUVZWRnl5OUFBQYwZM4a8vDyWLFnC+fPn8fT0ZPLkyajVai5fvsyyZcs4fvw47dq1Y9q0aXTo0AGADRs2kJqaioWFBePHj8ff3x+ArKwsVq9eTUVFBcOGDSMiIuI6XhYhhBD1ZVRBWbNmDVFRUQQHB+vb0tPTWb16dY33hL9WmzZteOmll7CxsaGsrIw5c+bg7+/Pxo0bufvuuwkODubdd98lNTWVO+64g9TUVNq2bcvSpUvZtWsXH3/8MdOnT+fkyZOkp6fzxhtvUFBQwLx583jzzTcBWLVqFbNnz8bZ2ZnY2FgCAwPp3LlzA18WIYQQ9WXUGMrp06cZOHBglbagoCBycw3fNrcylUqFjY0NAOXl5ZSXl6NSqcjOziYoKAiA0NBQMjIygCuTUYaGhur388svv6AoChkZGQwaNIg2bdrQoUMH3NzcOHr0KEePHsXNzQ1XV1fUajWDBg3Sb+tGm2zd2eAfIYRoTYzqobi5uZGens7gwYP1bbt3767XTbcqKiqYOXMmubm53Hnnnbi6umJnZ4elpSUAWq0WnU4HXJk7zNnZGbhy/YudnR3nz59Hp9Ph4+Oj32blmKvrX/13Tk6O0bmBXKEthBDXy6iCMm7cOOLj49m8eTMuLi6cPXuW06dPExMTY/SOLCwsWLRoERcuXOD111/n1KlTDU76eqSkpJCSkgJAfHw8Li4uAJypJebqOjU62sC4StRqtdHrtvS4hr4PzT2uOeQocRJXF6MKys0338zSpUvJzMykoKCAfv360bdv3wad5dW2bVt8fX05cuQIxcXFlJeXY2lpqT97DK70PPLz83F2dqa8vJzi4mLatWunb7+qckzl9vz8fH37tcLDwwkPD9c/PnfuXJ0517ZOhwbGVebi4mL0uq0p7loN3UZziGsOOUqcxAG4u7sbXM/o61A0Gg0hISHce++9hISE1KuY/PPPP1y4cAG4csbXzz//TKdOnfD19WXPnj0ApKWl6e+t0q9fP9LS0gDYs2cPvr6+qFQqAgMDSU9P5/Lly+Tl5XH69Gm8vb3x8vLi9OnT5OXlUVZWRnp6utynRQghzKzWHsrLL79ca7BKpWLOnDl17qSgoIDly5dTUVGBoigMHDiQfv360blzZ5YsWcJnn31Gt27dCAsLAyAsLIxly5YxefJkNBoN06ZNA6BLly4MHDiQGTNmYGFhwYQJE7CwuFITH3/8cebPn09FRQVDhw6lS5cuRr0A12v2JsO3QZ4yxSwpCCFEk1BrQbnttttqbNfpdGzevJmSkhKjdtK1a1dee+21au2urq41nnZsZWXFjBkzatzWqFGjGDVqVLX2vn370rdvX6PyEUIIYXq1FpSrPYarzp8/z4YNG9i2bRuDBg1i9OjRNzS55qCb66ONnYIQQjQJRg3KFxcX8/XXX7N161b69u3Lq6++ipub243OTQghRDNSa0EpLS3lm2++YePGjfTq1Yu5c+eabWxCCCFE81JrQXn66aepqKhg5MiReHl5UVhYSGFhYZV1brnllhuaoBBCiOah1oJiZWUFwLffflvjcpVKxbJly0yfVTOSVGZ4+pkROJoxEyGEaFy1FpTly5ebKw8hhBDNnNxgSwghhElIQRFCCGESUlCEEEKYhBQUIYQQJmH0PeWFqI/Psx8xuOwB3w/NmIkQwlykhyKEEMIkpKAIIYQwCTnkJW6IydadDS7LM2MeQgjzkR6KEEIIk5AeSiORQWshREsjBaWRtPRDQqv2zTS4bIS3GRMRQpiNHPISQghhEmbpoZw7d47ly5fz999/o1KpCA8P51//+hdFRUUkJCRw9uxZ2rdvz/Tp09FoNCiKwurVq9m/fz/W1tZER0fj6ekJQFpaGuvXrweu3A44NDQUgOPHj7N8+XJKS0sJCAhg/PjxqFSqG/7c1qc9b3jhw1/f8P03VTILsxCtj1l6KJaWljzyyCMkJCQwf/58tm7dysmTJ0lOTqZ3794kJibSu3dvkpOTAdi/fz+5ubkkJiby5JNPkpSUBEBRURHr1q1jwYIFLFiwgHXr1lFUVATAypUrmThxIomJieTm5pKVlWWOpyaEEOL/M0sPxcnJCScnJwBsbW3p1KkTOp2OjIwM4uLiABgyZAhxcXFERkayd+9eQkJCUKlUdO/enQsXLlBQUEB2djZ+fn5oNBoA/Pz8yMrKwtfXl4sXL9K9e3cAQkJCyMjIICAgwBxPr0Fmb+pocNmUKWZMRAghTMTsg/J5eXn8/vvveHt7U1hYqC80jo6O+rtB6nQ6XFxc9DHOzs7odDp0Oh3Ozs76dq1WW2P71fVrkpKSQkpKCgDx8fH6/ZypJefKuVyroXHdXB9tUFxlarXa6HUbM+5aN+L1bO5xzSFHiZO4upi1oFy6dInFixczbtw47OzsqixTqVRmGfMIDw8nPDxc//jcuXN1xhizTmPEubi4NGgf5o67VlN9PRszrjnkKHESB+Du7m5wPbOd5VVWVsbixYu57bbbGDBgAAAODg4UFBQAUFBQgL29PXCl51H5CeTn56PVatFqteTn5+vbdTpdje1X1xdCCGE+ZikoiqLw9ttv06lTJ+655x59e2BgIDt27ABgx44d3Hrrrfr2nTt3oigKR44cwc7ODicnJ/z9/Tlw4ABFRUUUFRVx4MAB/P39cXJywtbWliNHjqAoCjt37iQwMNAcT63BkspyDf4RQojmyCyHvA4fPszOnTu56aabeO655wB46KGHiIiIICEhgdTUVP1pwwABAQFkZmYyZcoUrKysiI6OBkCj0XDfffcRGxsLwOjRo/UD9FFRUaxYsYLS0lL8/f2b9IB8ayCnUwvR+piloPTo0YMvvviixmVz5syp1qZSqYiKiqpx/bCwMMLCwqq1e3l5sXjx4utLVAghRIPJlfJCCCFMQgqKEEIIk5CCIoQQwiRktuFmRqa9F0I0VdJDEUIIYRLSQ2lmWvp9VIQQzZf0UIQQQpiE9FAaSUMv/JNZioUQTZUUlGamtlmKhRCiMckhLyGEECYhPZRmRm6tK4RoqqSHIoQQwiSkoAghhDAJKShCCCFMQgqKEEIIk5BB+VZC5gATQtxoUlBaCZmyRQhxo8khLyGEECZhlh7KihUryMzMxMHBQX+b3qKiIhISEjh79qz+fvIajQZFUVi9ejX79+/H2tqa6OhoPD09AUhLS2P9+vUAjBo1itDQUACOHz/O8uXLKS0tJSAggPHjx6NSqczx1MxOpmwRQjRVZikooaGhDB8+nOXLl+vbkpOT6d27NxERESQnJ5OcnExkZCT79+8nNzeXxMREcnJySEpKYsGCBRQVFbFu3Tri4+MBiImJITAwEI1Gw8qVK5k4cSI+Pj4sXLiQrKwsAgICzPHUmo2GTtkiYy9CCGOZpaD06tWLvLyqR+ozMjKIi4sDYMiQIcTFxREZGcnevXsJCQlBpVLRvXt3Lly4QEFBAdnZ2fj5+aHRaADw8/MjKysLX19fLl68SPfu3QEICQkhIyNDCso1GnqFvYy9CCGM1WiD8oWFhTg5OQHg6OhIYWEhADqdDhcXF/16zs7O6HQ6dDodzs7O+natVltj+9X1DUlJSSElJQWA+Ph4/b7O1JJr5Xyu1VzialNb3OxEw4fK5s5tOs+vucc1hxwlTuLq0iTO8lKpVGYb8wgPDyc8PFz/+Ny5c3XGGLNOS42r7VBZU8qzucc1hxwlTuIA3N3dDa7XaAXFwcGBgoICnJycKCgowN7eHrjS86icfH5+PlqtFq1Wy6FDh/TtOp2OXr16odVqyc/Pr7a+MA2ZjFIIYaxGO204MDCQHTt2ALBjxw5uvfVWffvOnTtRFIUjR45gZ2eHk5MT/v7+HDhwgKKiIoqKijhw4AD+/v44OTlha2vLkSNHUBSFnTt3EhgY2FhPSwghWi2z9FCWLFnCoUOHOH/+PJMmTWLMmDFERESQkJBAamqq/rRhgICAADIzM5kyZQpWVlZER0cDoNFouO+++4iNjQVg9OjR+gH6qKgoVqxYQWlpKf7+/jIgX4OGnm4shBDGMktBmTZtWo3tc+bMqdamUqmIioqqcf2wsDDCwsKqtXt5eemvbxGmJYVICGEsuVJeCCGESUhBEUIIYRJSUIQQQpiEFBQhhBAmIQVFCCGESUhBEUIIYRJSUIQQQpiEFBQhhBAmIQVFCCGESUhBEUIIYRJSUIQQQpiEFBQhhBAmIQVFCCGESUhBEUIIYRJSUIQQQpiEFBQhhBAmIQVFCCGESUhBEUIIYRJmuQWwuWRlZbF69WoqKioYNmwYERERjZ2SEEK0Gi2mh1JRUcGqVat44YUXSEhIYNeuXZw8ebKx0xJCiFajxRSUo0eP4ubmhqurK2q1mkGDBpGRkdHYaQkhRKuhUhRFaewkTGHPnj1kZWUxadIkAHbu3ElOTg4TJkyosl5KSgopKSkAxMfHmz1PIYRoqVpMD8VY4eHhxMfH11lMYmJiGrT9hsSZc18SJ3ES13rizJ1jiykoWq2W/Px8/eP8/Hy0Wm0jZiSEEK1LiykoXl5enD59mry8PMrKykhPTycwMLCx0xJCiFbDMi4uLq6xkzAFCwsL3NzcWLp0KVu2bOG2224jKCjourbp6elptjhz7kviJE7iWk+cOffVYgblhRBCNK4Wc8hLCCFE45KCIoQQwiSkoAghhDCJFjWXV0P99ddfZGRkoNPpgCunIAcGBtK5c+cbtj+dToePjw82Njb69qysLPz9/Q3GHT16FABvb29OnjxJVlYW7u7u9O3bt177X7ZsGc8880y9Yn777TeOHj1Kly5d6NOnj8H1cnJy6NSpE3Z2dpSWlpKcnMzx48fp3Lkzo0aNws7Orsa4TZs20b9/f1xcXOqVV1lZGbt27cLJyQk/Pz9++OEHDh8+TKdOnQgPD0etNvwRP3PmDD/++CP5+flYWFjQsWNHBg8ebDBHIUTtWv2gfHJyMrt27SI4OFh/3YpOp9O3NXSCye3btzN06NBq7Zs2bWLr1q106tSJP/74g3HjxnHrrbcCMHPmTF599dUat7d27VqysrIoLy/Hz8+PnJwcfH19OXjwIH369GHUqFE1xl27PUVRyM7O5pZbbtHvsyaxsbEsXLgQuDK7wNatW+nfvz8///wz/fr1M/i6zJgxg0WLFmFpack777yDtbU1QUFBHDx4kD/++INnn322xrjHHnsMGxsbXF1dCQ4OZuDAgdjb29e4bmWJiYmUl5dTUlJC27ZtuXTpEgMGDODgwYMoimKwcG7atInMzEx69uzJ/v378fDwoG3btvz0009ERUXh6+tb575bi8LCQhwcHMy2v/Pnz9OuXTuz7e9GKS4uZsOGDWRkZFBYWIhKpcLBwYHAwEAiIiJo27Ztvbe5YMECXnjhBYP7S05OJj8/n4CAAAYPHqxflpSURFRUVI1xf//9N2vXrkWlUvHAAw+wefNmfvzxRzp16sT48eNxcnIyOr9W30PZvn07ixcvrvZL9p577mHGjBkNLihffPFFjQVl27ZtvPrqq9jY2JCXl8cbb7zB2bNn+de//kVttX3Pnj0sWrSIy5cv8+STT/LWW29hZ2fHyJEjeeGFFwwWFJ1OR6dOnRg2bBgqlQpFUTh+/DgjRoyoNf/y8vIqOb/44ovY29szYsQIZs2aZfB1URQFS0tLAI4fP64vaD169OC5554zuD9XV1fi4+M5ePAg6enpfPHFF3h6ehIcHMyAAQOwtbWtMe7PP//k9ddfp7y8nEmTJvHOO+9gYWHBbbfdVuv+tm3bxqJFi7CwsOCee+5h4cKFxMXFcfvtt/Paa6/x2muv1RjX0r8kioqKqjxWFIUXXnhB/z5qNJoa4yr3rouLi3n//fc5duwYXbp04bHHHsPR0bHGuI8//pgRI0Zgb2/PsWPHSEhIQKVSUV5ezjPPPEOvXr1qjJs5cyb9+/cnODgYNze3GtepybFjx/joo49wcnJi7NixvPXWWxw9ehR3d3eefPJJunXrVmPcpUuX+Oqrr/Q9g+rMBAAADbpJREFUWrVajZubG7fffjuhoaE1xiQkJODr60tcXJz++f/999+kpaWRkJDA7Nmza4w7fvy4wfxPnDhhcNmKFSvo2LEjAwYMYPv27ezZs4epU6fSpk0bcnJyDMYtX76cvn37UlJSwssvv8zgwYOJjY0lIyODlStX8vzzzxuMvVarLygqlYqCggLat29fpb2goACVSlVrrKFf24qiUFhYaHDZ1cNcHTp0IC4ujsWLF3P27NlaC4qlpSUWFhZYW1vj6uqqPyxjZWVVa54LFy5k06ZNrF+/nkceeQQPDw+srKwM/ketnGdRURGKoqAoir63YGNjoy8YNenSpYu+d9a1a1eOHTuGl5cXp06dqvXwk0qlwsLCgj59+tCnTx/KysrIysrihx9+4MMPP2TVqlUG8ywrK+PSpUuUlJRQXFyMRqPh8uXLVYpiTcrLy7GwsODy5ctcunQJABcXl1rjWvqXxIQJE6oddtTpdMycOROVSsWyZctqjPv000/1BeWDDz7AycmJmTNn8uOPP/Luu+8a3F9mZiYPP/wwAB999BHTpk3D29ubU6dOkZiYaHCKpKKiIi5cuMDLL7+Mo6MjwcHBDBo0qM7ZMZKSkhgzZgwXLlzgxRdf5LHHHuPFF1/k4MGDJCUlMX/+/BrjEhMT6d+/P7NmzWL37t1cunSJ4OBgvvzyS06dOsXYsWOrxeTl5TFr1qwqbY6OjkRERLB9+3aDOcbGxhr8/3nhwgWDcWfOnNF/J/Xv35/169czd+7cOgtCYWEhd911FwBbt27V/1i86667SE1NrTX2Wq2+oIwbN465c+fSsWNHnJ2dATh37hy5ubnVJpa8VmFhIbNmzar2q1RRFF588cUaYxwcHDhx4gQeHh7AlS/omJgY3nrrLf7880+D+1Kr1ZSUlGBtbV3lP1lxcTEWFobPrbj6C3zgwIG8//77ODg41PlFe3W7MTExKIqiL7pOTk5cunSp1sI3adIkVq9ezfr162nXrh2zZ8/G2dkZZ2dnJk6caDDu2m2q1WoCAwMJDAykpKTEYNzQoUOZNm0aFRUVPPjgg7zxxht06NCBnJwcBg0aZDBu2LBhxMbG4u3tzW+//ca9994LwD///GPwVzi0/C+JyMhIfv75Zx555BFuuukmAJ5++mmWL19e6/4qO3bsGIsWLQKu9PR37NhhcN2KigrKy8uxtLSktLQUb+//1979x0RZxwEcfx8e3EXN8MQVBFFOTZdYimUmJ5pkm2FBC9L+0MLMBGb+WDK2tnQtyf4CNhdxZLnUpFbaL21kDgVau6BIjh9lNa5ATxJGyY7n4Dj6g/HMg3sQbpcl93n9xT3PfZ7nObbn+3m+z/N9vp8ZAERHR9PX16cZd9NNN7Fu3TrWrVtHU1MT1dXV5ObmEhMTw5IlS0hOTvYZ19/fz/z584HB3tHQy8/x8fG89957mvv7888/1Z5ISkoKeXl5PPnkk2RlZbF9+3afCWXatGl88sknJCUljbj4GO1ZYUxMDM8//zxRUVEj1m3evFkzzu124/F41PbgiSeewGQy8corr6gXTL5cee4lJSV5rfN4PJpxvgR9Qrn33nspLCzkl19+8XooP2PGjFEbaoAFCxagKIqaHK6k1Xjk5OSMuMKfNGkSOTk5micBwO7duwkNDQXwOi632012dvaoxwkwdepUtm/fzvfff695++hKWg2ITqcb9VZSeHg42dnZOJ1O2tvb8Xg8mEwmzVseQ7Zu3aq5zmAwaK5LSUlRE4fJZCIpKYn6+nqSk5PVxsmXVatWER8fT1tbG6tXr+a2224DYPLkyezevVszbqI3EqtXr+bBBx/kwIEDTJ06lYyMjKv21GEwgX3++ecMDAzQ09OjXogMP5bhVq5cSX5+Pqmpqdxzzz288847LFq0CJvN5vO88mXOnDnMmTOHzMxMzp49yzfffKN5LoWGhvLjjz/idDrR6XRYrVbuv/9+GhsbRz3fDQYDzc3NzJ49m5qaGvWiIyQkRPP3bd26lWPHjrFr1y71jkVERAQJCQls27ZNc1/p6ema23z22Wc14xISErDZbMybN09dtmzZMiIiIti/f79m3MKFC1EUBaPRyJo1a9TlDoeD6OhozThfgv6hvBDj0d3dzbFjx6ipqRnRSKSmpmr2br799ltuv/12nyfoUKPmy8GDB5k3b55XIwGDzyz2799PUVGRz7iysjIef/xxr1GEMNhIHDp0iB07dlz1t9bU1HD06FHa29uxWCyjfvfDDz/0+vzII48wefJkurq6OHjw4KijChsaGigvL+fChQv09/cTGRnJfffdx/LlyzVvrxYUFIx6EaKlpaWFQ4cOodPpWL9+PeXl5Zw+fRqTycSmTZu46667fMbZ7XaKi4txOBzExMSwefNmoqOj+fvvv6mqqmLVqlU+49ra2ujo6GDWrFnjGtHp70hQrbgffvhB7ZkFcn8jDAghAuLUqVMTLs7lcg3Y7fZrtr+JFPfFF18MbNmyZWDv3r0DWVlZA1arVV23c+dOze35G3f8+PFrGudL0N/yEiJQtEb2Xc9xYWFh6rOU//Nx/h/j/B3R6W/cyZMnr2mcL5JQhBgHf0b2SVxwxg34OaLzeonzRRKKEOPgz8g+iQvOOH9HdF4vcb5IQhFiHPwZ2SdxwRnn74jO6yXOFxnlJYQQIiBktmEhhBABIQlFCCFEQEhCEeI/kJ2dzdmzZwH4+OOPKS4u9ntbBQUFWK3WQB3amNntds25y0RwkofyYsLLzs5m06ZNXm+bV1RU8PXXX/Pqq6/+h0c2SGum6OF27dqF2WxmxYoV6jK73Y7dbufFF19Ul1VVVXH48GEuX75MfHw8WVlZmm/wV1RUcOLECRwOBzfccAOJiYmsXbtWfUhbVFSEzWbD5XIRERHBY489pu4/Li6OG2+8kZqaGhYuXOjvzxcTiPRQhAigsUy8GUhfffUVZrNZnTfrjz/+oKSkhJycHCwWCwaDgdLSUs343t5ennnmGd5++2327NlDfX09n332mbo+LS2Nffv2ceDAAXbu3MmRI0e8Zk5OTEzk5MmT/94PFNcV6aEIAbS2tlJaWkpLSwsmk4mnn35aveoe3jMY3rvJyMggMzOT48eP09/f73NizTNnznDkyBEURSElJcVr3QcffIDD4WDLli309vZSXFxMXV0dHo+HqKgocnNzOXHiBE1NTZw7d453332XZcuWsWHDBurq6rzmyaqsrCQhIUEdyvrUU0+xbds2enp6fE4KunLlSvVvk8mE2WzGZrOpy2JjY9W/dTodOp0Oh8PB9OnTAbj77rspLi6mr69PnbxUBC9JKCLoud1u9u7dy/Lly3n55Zdpbm7mjTfe4PXXXx/zbKvfffcde/bsISwsbMS61tZWLBYLeXl5zJw5k8OHD9PR0eFzO6dPn8bpdPLmm28SGhpKS0sLYWFhrF27lp9++skrsSmKQnt7u9cxtra2MmvWLPXzrbfeil6v58KFC2oSGE1jY6NXEoHBGiIVFRX09vZy5513epWcNplM6PV6zp8/T1xc3FW3LyY2SSgiKAyVJR7idrvV6nznzp1DURRSU1MJCQlh7ty5LFiwgKqqKjIyMsa0/bS0tFFnGh7ea/jyyy99fnfSpEl0d3fjcDiIi4sbNQk4nU4Ar9lhFUVRi68NCQ8Pp6en56q/4dSpU/z222+88MILXsufe+45MjMz+fnnn2loaBhRKM1oNI5a00UED0koIii89NJLPh/Kw2B1zsjISK96GNOmTVPr44zFUHE2Xzo7O73WG41GzZrpS5cupaOjg4KCApxOJ2azmTVr1visdjmUOBRFUXtGRqNxRPIYut1VWVlJSUkJMFhD5Mqyw1arlffff18t9TxcSEgIs2fP5syZM5SXl3tN164oil+lj8XEIwlFBL0pU6Zw6dIlr0JWly5dUothGQwGr6qRXV1dI7YxWhGqKVOm0NbWpn52uVxcvnzZ53f1ej3p6emkp6fT3t5Ofn4+0dHRPPTQQyP2YTQaueWWWzh//ryaBGJiYrDb7ep3Ll68SF9fH1FRUUyfPh2z2Txin3V1dbz11lvk5eWpMwtr8Xg8XLx4Uf3c2dmJ2+0edyEmMTHJKC8R9GbOnInBYODTTz/F7XbT0NBAbW0tS5YsAeCOO+7AarXicrlwOBzjrrP9wAMPUFtbS3NzM263m7KyMs1ZXG02G7///jsej4fw8HD0er2aSG6++Wavxhxg/vz5NDY2qp/NZjO1tbU0NTWhKAplZWUsWrRIs0qnzWajqKiIHTt2jKhw+ddff1FdXY2iKHg8Hurq6qiuriY+Pl79TmNjI3PnzpUH8gKQHooQ6PV6cnNzKS0t5ejRo5hMJnJyctSywI8++ii//vorGzduJC4ujsTEROrr68e8/djYWDZs2EBhYSEul4uUlBTNW2RdXV1YLBY6OzsxGo0sXryYpUuXAoNli/ft26cOFc7MzCQ5OZmCggLS0tLQ6XTExsayceNGioqK6O7uVt9D0fLRRx/hdDrJz89Xlw3dDtPpdJSXl2OxWBgYGCAyMpL169d7vXNSWVnJww8/POb/hZjYZHJIIa5zhYWFLF68WLOM8L/FbrdTUlLCa6+9dk33K/6/JKEIIYQICHmGIoQQIiAkoQghhAgISShCCCECQhKKEEKIgJCEIoQQIiAkoQghhAgISShCCCECQhKKEEKIgPgH4JuJuR/hjAYAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "b4194ed0acf27802e82548512f1c0096cb36710c",
        "_cell_guid": "856f7bd9-5dab-4da1-9e49-c51ddbbf9194",
        "id": "9Oo0i0-RkEu2"
      },
      "source": [
        "Based on the above visualization plots, maximum no of trips were reported as \"N\" in storing the data and the mean trip duration was higher on those trips where trip data was stored."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "0ecaf0117604d00bf7b0b917d7f0c56dfb3ca195",
        "_cell_guid": "261f7a41-17fe-453e-ae4b-5ecaf4c7441f",
        "id": "qInuZCkxkEu2"
      },
      "source": [
        "Now for further deep analysis, we need to create a couple of columns:\n",
        "\n",
        "*Column 1* - **Distance**\n",
        "\n",
        "*Column 2* - **Speed**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "e612253e5358aa160b50f9dbb60124fab219bdfb",
        "_cell_guid": "30c0968b-39e4-43e2-be0f-f7302ef25b92",
        "id": "SAKePCXdkEu3"
      },
      "source": [
        "We are creating a new column : Distance using **Haversine** formula which takes into consideration of latitude and longitude coordinates.\n",
        "\n",
        "By far, Haversine formula is the most widely formula used\n",
        "\n",
        "As the coordinates are concentrated tightly on the poles than on the Equator.\n",
        "We are taking Earth's radius to be **6371** which is greater than at the poles.\n",
        "\n",
        "As the Earth is not a perfect sphere, there will be few discrepencies in calculating distance using this formula"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "c353a17bb2089d9d49ca526eca46789b3ae3c7f9",
        "_cell_guid": "5f6ef81b-9ef4-41c3-a579-0e4ec45b37fe",
        "id": "54NPK7olkEu4"
      },
      "source": [
        "#Haversine formula to calculate distance using longitude and latitude coordinates, for train dataset\n",
        "def distance(origin, destination):\n",
        "    lat1, lon1 = origin\n",
        "    lat2, lon2 = destination\n",
        "    radius = 6371*1.1 # km\n",
        "\n",
        "    dlat = math.radians(lat2-lat1)\n",
        "    dlon = math.radians(lon2-lon1)\n",
        "    a = math.sin(dlat/2) * math.sin(dlat/2) + math.cos(math.radians(lat1)) \\\n",
        "        * math.cos(math.radians(lat2)) * math.sin(dlon/2) * math.sin(dlon/2)\n",
        "    c = 2 * math.atan2(math.sqrt(a), math.sqrt(1-a))\n",
        "    d = radius * c\n",
        "\n",
        "    return d\n",
        "\n",
        "#Iterating over each row of the 4 columns\n",
        "dist=[]\n",
        "for i,row in train.iterrows():\n",
        "    x=distance((train.pickup_latitude[i],train.pickup_longitude[i]),(train.dropoff_latitude[i],train.dropoff_longitude[i]))\n",
        "    dist.append(x)\n",
        "\n",
        "\n",
        "#Naming it as a new column\n",
        "train['distance_km']=dist"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FXMu9F6nwJfK"
      },
      "source": [
        "#Haversine formula to calculate distance using longitude and latitude coordinates, applying the same for test dataset\n",
        "#Iterating over each row of the 4 columns\n",
        "dist_test=[]\n",
        "for i,row in test.iterrows():\n",
        "    x=distance((test.pickup_latitude[i],test.pickup_longitude[i]),(test.dropoff_latitude[i],test.dropoff_longitude[i]))\n",
        "    dist_test.append(x)\n",
        "\n",
        "\n",
        "#Naming it as a new column\n",
        "test['distance_km']=dist_test"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "71d75af0369a196e192d00010f0b553158d97239",
        "_cell_guid": "7dd7aef8-65d5-4ad5-a34b-d34413887fc7",
        "id": "adNYezRkkEu9",
        "outputId": "cecb0a64-e6a1-44d2-ba5d-35ec9867f748",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 534
        }
      },
      "source": [
        "fig, ax = plt.subplots(nrows=1,ncols=2, figsize=(12, 7))\n",
        "#Plotting histogram\n",
        "plt.subplot(121)\n",
        "plt.hist(train['distance_km'],bins=100)\n",
        "plt.xlabel('Distance in km')\n",
        "plt.ylabel('No of trips')\n",
        "plt.title('Distribution of distance in km')\n",
        "pass\n",
        "\n",
        "#Plotting histogram with a log transformation\n",
        "plt.subplot(122)\n",
        "train['log_distance']=np.log(train['distance_km'].values + 1)\n",
        "sns.distplot(train['log_distance'].values,bins=100)\n",
        "plt.xlabel('Distance(km) in log transformation')\n",
        "plt.ylabel('No of trips')\n",
        "plt.title('Trips in distance using log transformation')\n",
        "\n",
        "#Max trips lasted for shorter distances"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Trips in distance using log transformation')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "5211dabc44d4e0a9145174312a1fe27c6def8eb8",
        "_cell_guid": "39bbb487-5faf-4c2d-9b62-dd0a58c6ef51",
        "id": "PabcDlkckEvC"
      },
      "source": [
        "Now analyzing distribution of distance travelled across days, hours and month of a year along with the passenger count."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "821eaea2c12a438b2faa5c8551d5ed4f0bd861f3",
        "_cell_guid": "ef707922-1d36-4651-8bf9-154f2316c6e0",
        "id": "7leIuARTkEvD"
      },
      "source": [
        "Majority of the distance are shorter in km."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "e02e69b690f2d6c57481aa3d3aa24437582c979c",
        "_cell_guid": "d7e1df8d-50ef-4110-90b8-fe501652e77d",
        "id": "i22OjJnSkEvE",
        "outputId": "08b3558c-7e73-4ac7-854d-f0f88bf2747e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 804
        }
      },
      "source": [
        "#Mean distance over different analysis\n",
        "data1=train.groupby(['hh_pickup','vendor_id'])['distance_km'].mean().unstack()\n",
        "data2=train.groupby(['dow_pickup','vendor_id'])['distance_km'].mean().unstack()\n",
        "data3=train.groupby(['mm_pickup','vendor_id'])['distance_km'].mean().unstack()\n",
        "data4=train.groupby(['hh_pickup','passenger_count'])['distance_km'].mean().unstack()\n",
        "\n",
        "fig, ax = plt.subplots(nrows=2,ncols=2, figsize=(19, 15))\n",
        "\n",
        "#Avg km as per hourly pickup\n",
        "figure=plt.subplot(2,2,1)\n",
        "data1.plot.bar(stacked=True,legend=False,ax=figure)\n",
        "plt.xlabel('Hour dist(0-23)')\n",
        "plt.ylabel('Avg km')\n",
        "plt.title('Avg km as per hourly pickup')\n",
        "pass\n",
        "\n",
        "#Avg km as per week of day pickup\n",
        "figure=plt.subplot(2,2,2)\n",
        "data2.plot.bar(stacked=True,legend=False,ax=figure)\n",
        "plt.xlabel('Week of a day')\n",
        "plt.ylabel('Avg km')\n",
        "plt.title('Avg km as per week of day pickup')\n",
        "plt.xticks(range(0,7),dow_names)\n",
        "pass\n",
        "\n",
        "#Avg km as per monthyly pickup\n",
        "figure=plt.subplot(2,2,3)\n",
        "data3.plot.bar(stacked=True,legend=False,ax=figure)\n",
        "plt.xlabel('Month')\n",
        "plt.ylabel('Avg km')\n",
        "plt.title('Avg km as per monthly pickup')\n",
        "plt.xticks(range(0,7),mm_names)\n",
        "pass\n",
        "\n",
        "figure=plt.subplot(2,2,4)\n",
        "data4.plot.bar(stacked=True,legend=False,ax=figure)\n",
        "plt.xlabel('Hour dist(0-23)')\n",
        "plt.ylabel('Avg km')\n",
        "plt.title('Avg km as per hourly dist with respect to passsenger count')\n",
        "plt.legend(loc = \"upper left\")\n",
        "pass\n",
        "\n",
        "fig.tight_layout()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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cnzNnjhEYGGhcu3Yt1/eRlpZmlC5d2nj44YeNnTt3Ghs3bjQaNGhgFC5c2Pj3v/9tX69cuXL2x3/098nKyjKWL19uSDK2bNlinD592rhw4UKusVeuXGkUKlTIfu02fPhwo3jx4kbjxo3t6zRq1MgYOnSoYRj/fwyuW7fOMAzD2L59uyHJWLZsmXH69Gnj7NmzhmH8/zXQQw89ZGzbts3YuXOnUa9ePaNZs2a55nFTbn/7pKQko0SJEsYLL7xg7N6924iPjzcGDBhgWK1We7yXX37ZiIiIMDZt2mQcPXrU2LBhgzFr1v+xd+9xUdb5//+fA6MgqCiBKJimeUo8UCpqmqhhtllpbusJT5XmJ1st205rJq3mxq0yO6yVuZtt2W7prst6iD5KJFhhi5gnVDymbX4V0MQ0DjJcvz/6OZ9GGI7DXMzwuN9u3m5e11zX9XrN9b5mfM/L9/u63nE4brNmzYwZM2YY+/fvN9avX2+EhoYajz76qH2b+Ph4o127dsa6deuMY8eOGZs2bTKuvfZaY8GCBfZtpk6daoSGhhrvv/++ceTIESM9Pd145ZVXDMMwjJycHMPX19d49dVX7X3i8pw/f9645ZZbjHHjxtm3KyoqqtK16uycVfbe1q1bZ3z88cfGwYMHjX379hkPPPCA0bJlSyMvL88wDMPYsWOH4evra/z1r381vv32W2PPnj3GypUr7dd1Ref38uXLRsuWLY158+YZhw4dMg4dOmSsW7fOSEtLMwzj5+v7hhtuMMaOHWtkZGQYhw8fNp5//nmjcePGxv79+w3DqNpn+dKlS0br1q2NO++809i9e7eRnp5uDBw40OFzUlpaagwdOtSIiYkxtm3bZhw9etRYsWKF0ahRIyM5OdkwjP+7hiMiIozVq1cbx44dM44dO1buuX333XcNq9VqLFq0yMjKyjJ2795tvPrqq0Zubq5hGIbx+OOPG8HBwcaaNWuM7OxsY8mSJYbFYrHHMgyj3O/9W2+91Zg2bZp9ubLfTM6uGXgGCqhAA3H33Xcbjz32mH155MiRxjPPPGNfHj9+vHHHHXfYlzMyMgxJxsGDBw3DMIz58+cb7du3N0pKSuzbJCUlVfkHxO7du43w8HDjt7/9rWGz2eyvX/mHb9myZfZ1//nPfwxJxssvv2xfd6VTt3fv3mq97169ehnPP/+8wzGu/HCqimnTphmBgYHG+fPn7ev+93//15BkHD582DCMn/+hfOuttxz2S01NNSTZOwoxMTFG586dHd57ea50Ov71r3/Z161Zs8aQZPzjH/+wr1u3bp0hyd5Jnjx5stGvXz+HYyUmJhoWi8X49ttv7e8lNDTU/uPNMAwjISHBaN26tX158eLFRvv27cvk1b59e+Ouu+5yWHf77bcbEyZMsC9fXYhcunSp0a5dO/t7PnDggCHJ2Llzp9P3Hx8f73BuDcMwsrOzDUn2DszVP44mT55s9OrVy+m5rewarGoBtbK8AAD1D/0fz+r//POf/7SvO336tCHJ+PTTTw3D+Ll42aRJE3vB48o2/v7+xl//+lfDMKpXQH3//ffLzeFKoen06dNGo0aNjC1btti3GTBggDF37lyn72PlypVGYGCg/f0bhmHs3bvXkOS0gFpZ+2zbtq1K7VdQUGD4+fkZmzZtMgzDMG6++WbjpZdeshdVL1y4YFit1jLFpysF1KvP0xXx8fGGr6+vvcBpGIbx0UcfGRaLxWkh2TDKb/v4+Hijf//+DtuVlpYaHTt2tH8W7r77boeCVHnHvfozuWLFCsPPz8+4ePGicenSJaNJkyZGUlKSw35//etfjaCgIMMwDOPw4cOGJGPt2rVO4/j6+hqrVq1y+voVVxfQDKNq12pN3lt5bDab0aJFC2P16tWGYfz8G6F58+ZGfn5+udtXdH7PnTtX7jVwxapVq4yIiAjj8uXLDuuHDRtmPPLII4ZhVO2z/M4775T5frnyO+HK5+Lzzz83/Pz8HLYxDMO47777jNGjRxuG8X/X8KJFi8rN95euvfZa4+GHHy73tUuXLhmNGzc2li9f7rB+zJgxxrBhw+zLVS2gVvabqbxrBp6BKfxAA/D9999r06ZNDtMLpk2bpnfffdc+nWDatGnavHmzcnJyJP081To6Olpdu3aVJO3fv1/9+vWTr6+v/RhXpgBVJjc3V0OGDNGkSZP0xhtvyMen7FdP79697X9v3bq1JKlXr15l1l3Jz1mc2bNnq1u3bmrRooWaNm2qrKwsnThxwn68kSNHqkePHrrnnnv02muvlZliXp7u3bsrKCjIvnxletT+/fuVm5urEydO6LHHHrNP0WnatKl+9atfSZLDVJ0+ffqU+97LU93zkZWVpSFDhjgcIyYmRoZhOEz179atm/z8/OzL4eHh9in8lYmKinJYrmzfadOmKScnxz7t589//rP69OmjG2+8scI4oaGhDk977dKli0JCQpSVlVXu9pmZmbr11lsrPLdVuQYrU928AADmov/jef2fX/Y1wsLC5Ovra+9rZGVlqXv37goJCXHYpmvXrjX6tzg6OrrC18PCwjR69GitXLlSkrRv3z5t375dM2fOdLrP/v37dcMNN6hly5b2dT169HA4j1eraftczd/fXwMHDlRKSoouXryojIwMTZo0SZ07d1ZaWprS0tLk6+vrMM2/qsLDwxUaGuqwbBhGhdelVLbtMzIylJmZ6XDNNGvWTN9++639lgCzZ8/WP/7xD/Xo0UOPPPKIkpKS7LfTuCI6OtrhMzlo0CAVFRXp6NGjysrKUkFBgX796187xJk1a5by8/OVm5urnTt3SpJuu+22ap+LqqjNtVrRe5Ok48ePa8qUKerUqZOaN2+u5s2bKz8/3/55HzFihDp27KgOHTpowoQJeuedd5SXl2c/XkXnt2XLlpoxY4ZGjhypX/3qV0pISFB2drZ934yMDJ0+fdr+PXPlz7Zt28rc0qGiz/KVz8kvPxdXvr9+Gau4uFgREREOsVavXl0mVmWf5ZycHH333XdO2/vIkSMqLi4u97dUTb5bqvubCZ6DAirQAPzlL3+RzWbTjTfeKKvVKqvVqilTpuj//b//Z3+Ywm233aaQkBD97W9/0+XLl/XRRx9p2rRpDsdxdv+fyrRo0UK33HKLEhMT7fffudovb2B/JU55667uQP3S9OnTtW3bNr344ovatm2bdu3apaioKPvNxH19fZWUlKSUlBT169dP//znP9WlSxdt3LixRu/rl/m89tpr2rVrl/3P7t27dfjwYfXs2dO+bXUeFuCK81Gexo0bOyxbLBYZhlHjfSuKf8011+jee+/VypUrVVxcrPfff18PPvhgtfJ1lYquQR8fnzLnwN0PkwAAuB79H8/r/1zd1/hlrKoor1Dr7N/0quT1P//zP0pMTFReXp7+/Oc/a+DAgerRo0eV86kKV7bP8OHD9dlnn2nbtm3q2LGjwsPDNXz4cKWkpCglJUUDBw6Uv79/tY9bXh9Qqrxtrj7HpaWluvXWWx2umV27dik7O9t+3/2RI0fq5MmTeuaZZ1RYWKjJkydr+PDhstlsVcr1Sk5r1651iLF3714dPnxYwcHBVTpOfXXnnXfq5MmTWr58ubZv365du3apVatW9s9706ZNtWPHDv3rX/9Sly5d9Pbbb6tTp07KzMyUVPn5XblypTIzMzVixAilpqaqR48eWrFihaSfz+0NN9xQpv0OHDhg/4+GKyr7LFf2vVpaWqqgoKAysfbv31/mfqrueiBbeb+byvt+qe5vJngOCqiAl7vy8IT58+eX+Qdo4sSJ9ocp+Pr6Ki4uTh988IGSkpKUn5+vCRMm2I/TvXt3ZWRkOHRetm/fXqUcGjVqpHXr1qlnz56KiYmx/w+pq6WlpWn27Nm6++671bNnT7Vp00bHjh1z2MZisSg6Olrz589XWlqaYmJitGrVqgqPe+DAAd7BjooAACAASURBVF24cMG+/NVXX0n6+ZyEhYXp2muvVXZ2tjp16lTmT006qTURGRnpcAN3SfaHXERGRlb5OI0bN65yB7UqZs2apQ0bNmjFihUqKCjQxIkTK90nNzfX/r/sknTo0CHl5eWpe/fu5W7fp08fffbZZxV2TCq6Blu1aqVTp045bH9lZEJt8gIAmIf+j/f1fyIjI7V//36H0XRnzpxRdna2vajZqlUr2Ww2h9Fe5f2bXlXDhw9Xu3bttGLFCn3wwQcVjj6Vfj43Bw4c0Pnz5+3rsrKylJ+fX+F+FbXPlWJMVfpnw4YN0+7du7V27Vrdeuut9vdwpYA6fPhwp/tWJ05N9e3bV1lZWWrbtm2Za+aXI1yDg4M1ceJErVixQps2bVJqaqrDjKqrP5NfffWV/Pz8dP311ysyMlL+/v46duxYudemr6+vbrrpJknS5s2bneZa1T5xedtV5Vp1pqL3dvbsWe3fv19PP/20Ro4cqe7du8vf37/MSGBfX18NGTJEixYtUmZmptq0aePwQKTKzm+PHj302GOPKSkpSQ888ID9+7Jv3746duyYmjdvXua8hoeHV3qurrjyOfnl5yI7O9vhc9O3b1+dP39ehYWFZWJV9jC6q7Vq1Upt27Z12t6dOnWSn59fub+lftleV/9mKCoqKvNQ36pw9e8tuA8FVMDLJSUl6bvvvtOsWbPUo0cPhz/Tp0/X5s2b7U8Snzp1qnbu3Kn4+HjdeeedDv9DO3v2bJ05c0YPPfSQDhw4oM8//1zPPPOMpKqNzGjUqJHWrFmjvn37KiYmpkzH3hW6du2qDz/8UHv37rX/QLq6A7J48WJ9/fXXOnnypD777DPt2bOn0gKYxWLR1KlTtW/fPqWlpenhhx/W3XffbZ/OvWTJEr3++utasmSJ9u3bp+zsbCUmJmrWrFkuf4/OPPHEE9q5c6fmzZungwcP6tNPP9WcOXMUFxdXrU5Ghw4ddPr0aaWnpysvL08//fRTrfIaPHiwunbtqscff1wTJkxQs2bNKt0nICBA9913n3bs2KEdO3Zo2rRpioqKsv8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            "text/plain": [
              "<Figure size 1368x1080 with 4 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "aedbfffb6b8201647321100d0389bfbe4766c2fd",
        "_cell_guid": "18a64570-ac99-4c97-a184-d16ad9675aff",
        "id": "wLh65f7ikEvG"
      },
      "source": [
        "In the early morning hours, there is a rise in km travelled. People used to prefer going other places in the early hours to avoid rush. \n",
        "\n",
        "In the 2nd barplot, there is a rise in km travelled on Sunday, followed by Monday. People usually go or come from other places on a Sunday and Monday early hours."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "b72449860779e98524c169287b9095f07bb5313e",
        "_cell_guid": "e2c6a0db-3b36-408e-b30c-453d173ce900",
        "id": "bq_oSrnRkEvH"
      },
      "source": [
        "*Creation of an another column* : **Speed**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "bb40cbca6682931b9b888ee21be26ed8ec4bb894",
        "_cell_guid": "73975834-f02b-4408-8ba5-c66673bafbc3",
        "id": "KEefJmzAkEvH",
        "outputId": "31d845df-28f1-45b7-a8fe-3f980db196bc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 534
        }
      },
      "source": [
        "#Speed in km/hr\n",
        "train['speed']=train.distance_km/(train.trip_duration/3600)\n",
        "\n",
        "fig, ax = plt.subplots(nrows=1,ncols=2, figsize=(12, 7))\n",
        "#Plotting histogram\n",
        "plt.subplot(121)\n",
        "plt.hist(train['speed'],bins=100,color='lime')\n",
        "plt.xlabel('Speed in km/hr')\n",
        "plt.ylabel('No of trips')\n",
        "plt.title('Distribution of speed in km/hr')\n",
        "pass\n",
        "\n",
        "plt.subplot(122)\n",
        "train['log_speed']=np.log(train['speed'].values + 1)\n",
        "sns.distplot(train['log_speed'].values,bins=100)\n",
        "plt.xlabel('Speed in log transformation')\n",
        "plt.ylabel('No of trips')\n",
        "plt.title('Speed using log transformation')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Speed using log transformation')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "cd36a66e27d8dba8c2a059a3c6bfbe93d260ee9f",
        "_cell_guid": "37758d3c-fd27-4578-852a-aa053f6a0b62",
        "id": "mdXp5T4DkEvK"
      },
      "source": [
        "As the distance travelled and trip duration are very low. So is the case with the average speed over trips."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "97db85e924f5a604e0d68a90ba89386f15468b01",
        "_cell_guid": "95a90634-1892-4dbe-9250-223fa045e720",
        "id": "GUSqBooGkEvL",
        "outputId": "49d696ba-7ac9-4ebd-9192-b416674ee3e3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 782
        }
      },
      "source": [
        "#Analyzing average speed over different parameters\n",
        "\n",
        "data1=train.groupby(['hh_pickup','vendor_id'])['speed'].mean().unstack()\n",
        "data2=train.groupby(['dow_pickup','vendor_id'])['speed'].mean().unstack()\n",
        "\n",
        "fig, ax = plt.subplots(nrows=2,ncols=2, figsize=(14, 12))\n",
        "\n",
        "figure=plt.subplot(121)\n",
        "data1.plot(kind='bar',stacked=True,alpha=0.7,colormap='coolwarm',ax=figure)\n",
        "plt.xlabel('Hour dist(0-23)')\n",
        "plt.ylabel('Avg speed')\n",
        "plt.title('Avg speed as per hourly pickup')\n",
        "pass\n",
        "\n",
        "#Avg speed as per week of day\n",
        "figure=plt.subplot(122)\n",
        "data2.plot(kind='bar',stacked=True,alpha=0.5,colormap='coolwarm',ax=figure)\n",
        "plt.xlabel('week of day')\n",
        "plt.ylabel('Avg speed')\n",
        "plt.title('Avg speed as per daily pickup')\n",
        "plt.xticks(range(0,7),dow_names)\n",
        "pass"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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dZuPGjWb//v3m888/N7fccotp3ry5cTqdxpj/exNpSkqK2bdvn+ue17/97W+uY4wbN840bdrUrFq1ynz55Zdm9+7dZtmyZWb27NnGmPNvkkxOTjatW7c2r7zyijlw4IDZuXOn+cc//mGWLFlijDEmJyfHNG3a1AwePNjs3r3b/Pe//zXdunUr802k999/v2ncuLHZvHmz2bdvn3nkkUdMRESEadGihTHGmFOnTpnJkyebd955xxw8eNDs2rXLJCUlFbkv/GIX3kTapUsXs3XrVpOWlmZuvPFG07RpU5OTk2OMMSYjI8PUq1fP3H777eZ///ufOXjwoNm8ebOZMmWKOXDggDHm/D3UrVq1KvE8F5MH72O55ZZbXIsg7Nmzp8giCMYY06tXL9O5c2eze/dus3PnTjNgwAATFhZW5D1Axd1XX9zjH330kQkMDDSBgYFu92qXxJPxcukiCI888ogJDw83//znP82+ffvM7t27zcyZM92OeWEM7Nmzx8TGxprRo0ebwsJCY4wxI0aMMC1btjQffvih+eyzz8ytt95qIiIiil0EobS6AHiH+Yv5y+l0mp///OemW7du5n//+5/55JNPTP/+/d0WQTh27JgJCQkxv/vd78z+/ftNamqq6dq1q3E4HG7vb7p0DiruvTTfffedCQoKMsHBwaWOjQsuLDYwadIkk5GR4VqwY8qUKa59Ln0P0NKlS12LIGRkZJjPP//cLFy4sNhFEL7//nvTrl07079/f9ciE4888ohp0KCB2bRpk9m7d6+57777TERERLGLIJRWF7xDAKphhgwZYnr06FHsc+fOnTMxMTFubybt2LGjkWTWrVtXZP+3337btG/f3gQHB5sOHTqY119/3Ugy//nPf0o8/+TJk03r1q1NaGioiY6ONoMGDTKff/656/kWLVqYGTNmmDFjxpj69eub6Oho89BDD7n+82mMMQUFBWbOnDnmyiuvNHXq1DENGzY0vXv3NmvXrnXtk5ubax566CHTsmVLU6dOHdOkSRMzYMAA884777j22bVrl+nRo4cJDg428fHx5sUXXyz2F+DFTpw4YW655RZXbZMnTzZ/+MMfXBPImTNnzG233WZatmxpQkJCTKNGjczw4cPN4cOHSzzmihUrTGBgoNm0aZNp06aNCQ4ONldffbX5+OOP3fZLS0szQ4YMMVFRUSY0NNS0atXKTJgwwfz000/GmMoPQNnZ2WbixIkmJibGBAcHmy5duphNmza5tdm3b5/p3bu3CQsLMwkJCeall14qdhEETwOQMefHXLt27Tzqhyfj5dIA5HQ6zYIFC8wVV1xh6tSpYxo3bmyGDRvmdsyLx8CXX35pmjdvbkaMGGEKCgrM999/b2644QZTv35906xZM/PUU08VuwhCWXUB8A7zF/OXMecX4LnuuutMSEiIiYuLMwsWLCjye/7f//63SUhIMCEhIaZjx45my5YtJjAw0OsAZIwxQ4cONdHR0SYvL6/M2pKSkszYsWPNAw88YKKjo029evXMnXfe6QorxhQNQMacX3E0MTHRBAcHu8ZWVlaW65gX9+3o0aMmMTHR9O3b1+Tk5JiTJ0+akSNHmqioKNOoUSOTkpJS7CIIZdUF7ziM8fKaImqtbdu2KSkpSWlpaerQoUO5jtGyZUuNHz9ef/jDHyq5uupr5cqVGj9+vOsNvDY7d+6cWrZsqd///ve69957y9y/uo6X6loXgOIxf5WPDfNXt27d1KtXL82fP7/Mffv06aOEhAQ988wzPqjMc9W1rpqMRRAs9q9//Us///nPFRsbq4yMDE2dOlXdu3cv9+QBezmdTmVmZmrx4sXKycnR2LFj/V0SgFqM+QtlyczM1IYNG7Rr1y6tXr3a3+WgmiEAWezrr7/WrFmz9OOPP6pp06a67rrrNGfOHH+XhRro8OHDuvzyy/Wzn/1My5cvZ6EAAFWK+QtladSokRo0aKB//OMfio+P93c5qGa4BQ4AAACANVgGGwAAAIA1CEAAAAAArEEAAgAAAGCNGrkIwqWfmHtBTEyMMjMzy3XMmta2ptXrr7Y1rV5/ta1p9fqrbU2rtyrbxsbGluuYtihpnqosFfm+Vjf0pfqpLf2Q6Et15Yu+lDZPcQUIAAAAgDUIQAAAAACsQQACAAAAYI0a+R4gAKgujDHKy8uT0+mUw+Eocb8ff/xRZ8+eLdc5/Nk2Pz9foaGhpfYNZfN0nHiqIt/XymaMUUBAAOMEQI1BAAKACsjLy1OdOnUUFFT6r9OgoCAFBgaW6xz+bHvhP+5169Yt1zFwnqfjxFMV+b5WhYKCAsYJgBqDW+AAoAKcTmel/ae2OgoKCpLT6fR3GTUe4wQAqg8CEABUgA23/NjQx6pmw2toQx8B1A4EIAAAAADWIAABQDV3+PBh9e3bt8LH+eGHHzRhwoRinxs2bJg+/fTTCp8D/nPkyBHGCQB4gAAEALVMQUFBsY83bdpUS5cu9XE1qK4YJwBsVXvfkQkAfjBz5kzFxsZqzJgxkqR58+YpPDxcDodDr776qvLz8zVw4EA98MADOnLkiEaOHKlu3bpp586datq0qZYvX666desqLS1N06ZNkyRde+21ruPn5eXp4YcfVlpamgIDA5WSkqJevXppzZo1euONN5STkyOn06mXXnqpSG1HjhzR6NGjtXnzZp05c0bTpk1TRkaGEhISlJeX55PXB+eVNE6MMVq/fn2Z42TVqlWqU6eO2zhJSkpyHZ9xAgAl4woQAFSiIUOGaP369a7t9evXKzo6WgcPHtTGjRv11ltvKS0tTdu3b5ckHTp0SKNHj9a7776riIgIvf7665KkadOm6YknnlBqaqrb8VeuXCmHw6F33nlHTz31lO677z7Xf0o/++wzLVmypNj/1F5q1apVqlu3rrZu3ar7779faWlplfUSwAMljZNDhw55NE42btwoiXECAOVBAAKASnTVVVcpMzNTP/zwg9LT0xUZGam9e/dq69at6t+/vwYMGKADBw7o0KFDkqTmzZvrqquukiQlJibqyJEjys7OVnZ2tnr06CHp/PsuLtixY4d+/etfS5ISEhLUrFkzHTx4UJLUu3dvNWjQwKM6//e//7mO065dO7Vt27ZyXgB4pKLj5PDhw0XGyc033+w6PuMEAErGLXAAUMluuOEGbdy4UUePHtWQIUP0zTffaMqUKbr99tvd9jty5IhCQkJc24GBgRW6xSgsLKzcbeF7xY2Tu+++W6NGjXLbr7hxkp+fX+7zMk4A2I4rQABQyYYMGaJXX31VGzdu1A033KA+ffrohRdeUE5OjiTp+++/V2ZmZontIyMjFRkZqY8++kiS9PLLL7ue69atm1555RVJ0oEDB/Ttt9+qVatWXtfYvXt3rVu3TpK0d+9e7dmzx+tjoGKKGydr1qwp9zi5MC4kxgkAlIYrQABQya688krl5OSoadOmatKkiZo0aaIDBw5oyJAhks7/BX7hwoUKDAws8Rh/+9vfNG3aNDkcDrdFEEaPHq2HH35Y/fr1U2BgoObPn+92dcBTd9xxh6ZNm6akpCS1bt1aiYmJ3ncUFVLcOPnyyy/LPU4uXgSBcQIAJXMYY4y/i/DWd999V+zjMTExpf61rDQ1rW1Nq9dfbWtavf5qW9Pq9Vfb4trl5uZ6dEtRUFBQicsOV/e2xfUxNja2XMe0xaXzlKfjxFMV+b5WlfL2sSI/y9VNbelLbemHRF+qK1/0pbR5ilvgAAAAAFiDW+AAoJbZs2ePpkyZIklyOBwyxigkJEQbNmzwc2WoTi4eJxcwTgDYgAAEALVM27Zt9fbbb0uqnrdKoXq4eJwAgE24BQ4AAACANQhAAAAAAKxBAAIAAABgDQIQANRi9957rxITE9W3b19/l4JqbNq0aYwTANZgEQQA8JHZ/yz+M8zKEhDgkNNZ9CPbpt9d9mfx3HrrrRozZozuvffecp0bvrd2/U9l7hMQECCn0+nR8Ybf2LDsfYYP19ixYxknAKzAFSAAqMV69uypqKgof5eBaq5Hjx6MEwDWIAABAAAAsAYBCAAAAIA1CEAAAAAArMEiCJY4MG6G6+sjwcHKz893bbdaPtMfJQEAAKCG+37+Sq/bZIeFKTc31+P9fzZ1jNfnKA1XgACgFps0aZKGDBmiAwcOqEuXLnrxxRf9XRKqocmTJzNOAFiDK0AA4COeLFtdnKCgIBUUFJSr7eLFi8vdFv7hybLVFRkTxXnqqacq7VgAUN1xBQgAAACANQhAAAAAAKxBAAIAAABgDQIQAAAAAGsQgAAAAABYgwAEAAAAwBoEIACoxb799lsNGzZMffr00bXXXqtnnnnG3yWhGmKcALAJnwMEAD5yYNyMcrVzOBwyxhR5vNXymWW2DQoKUkpKijp06KDTp09r4MCB6t27t6644opy1YKq58mnqgcEBMjpdHp0PE8+QZ1xAsAmXAECgFqsSZMm6tChgySpXr16at26tX744Qc/V4XqhnECwCYEIACwxJEjR/T555+rU6dO/i4F1RjjBEBtRwACAAvk5ORowoQJevzxx1W/fn1/l4NqinECwAYEIACo5c6dO6cJEybopptu0qBBg/xdDqopxgkAW7AIAgDUYsYY3X///UpISNCkSZP8XU61lZ+fr5SUFBUUFKiwsFA9evTQ8OHDtWjRImVkZCgsLEySdNddd6lly5b+LbYKME4A2IQABAC12EcffaSXXnpJbdu21XXXXSdJmj59uvr16+fnyqqXOnXqKCUlRaGhoSooKNCjjz6qjh07SpJGjRqlHj16+LnCqrVjxw7GCQBrEIAAwEc8Wba6OEFBQSooKChX2+7du+vbb78tV1ubOBwOhYaGSpIKCwtVWFgoh8Phl1o8Xba6vGOiON26dWOcALAG7wECAECS0+nUgw8+qPHjx6tDhw5q3bq1JOnFF1/UAw88oJUrV+rcuXN+rhIAUFFcAQIAQOc/XHTu3LnKycnRk08+qcOHD+v2229XVFSUCgoKtHjxYr366qsaNmxYkbapqalKTU2VJM2ePVsxMTFuz//4448KCqrcKbeyj1dRISEhRfrtiaCgoHK1q45qS19qSz8k+uIL2f//eyS9ERAQ4HpvpScqu9/V67cnAAB+Fh4ervbt22v37t0aMmSIpPPvEbr22mu1fv36YtskJycrOTnZtZ2Zmen2/NmzZxUYGFhpNVb2LXCV4ezZs0X67YmYmJhytauOaktfaks/JPriC7m5uV63CQsL86pdefodGxtb4nPcAgcAFWCM8XcJVc6GPp48eVI5OTmSzq8Il5aWpri4OGVlZUk6/xrs2LFDzZs3L9fxbXgNbegjgNqBK0AAUAEBAQEqKCiodrcjVZaCggIFBNT+v5VlZWVp0aJFcjqdMsaoZ8+e6tKlix5//HGdPHlSktSiRQtNnDixXMdnnABA9VE7fxMDgI+EhoYqLy9PZ8+eLXXVsJCQEJ09e7Zc5/Bn23PnzrlWR6vNWrRoob/+9a9FHk9JSamU43s6TjxVke9rZTPGKCAgwIpxAqB2IAABQAU4HA7VrVu3zP0qcu92TWwLd56OE0/xvQGA8uN6NQAAAABrEIAAAAAAWIMABAAAAMAaBCAAAAAA1iAAAQAAALAGAQgAAACANQhAAAAAAKxBAAIAAABgDQIQAAAAAGsQgAAAAABYgwAEAAAAwBoEIAAAAADWIAABAAAAsAYBCAAAAIA1CEAAAAAArEEAAgAAAGANAhAAAAAAaxCAAAAAAFiDAAQAAADAGgQgAAAAANYgAAEAAACwBgEIAAAAgDUIQAAAAACsQQACAAAAYA0CEAAAAABrEIAAAAAAWIMABAAAAMAaBCAAAAAA1iAAAQAAALAGAQgAAACANQhAAAAAAKxBAAIAAABgDQIQAAAAAGsQgAAAAABYgwAEAAAAwBpBvjrRXXfdpdDQUAUEBCgwMFCzZ8/W6dOnNX/+fB07dkyNGjXS1KlTVa9ePV+VBAAAAMAyPgtAkpSSkqKIiAjX9rp169ShQwcNHTpU69at07p16zRy5EhflgQAAADAIn69BW7Hjh1KSkqSJCUlJWnHjh3+LAcAAABALefTK0B/+ctfJEnXXXedkpOTlZ2drQYNGkiSoqKilJ2d7ctyAAAAADMVvQcAACAASURBVFjGZwHoz3/+s6Kjo5Wdna0nnnhCsbGxbs87HA45HI5i26ampio1NVWSNHv2bMXExBS7X1BQUInPlaWmtfW23ZHgYNfXDodDwRdte3Oc2v462dq2ptXrr7Y1rV5/toV3vp+/0qv9s8PClJub61Wbn00d49X+AFBb+SwARUdHS5IiIyN19dVXa//+/YqMjFRWVpYaNGigrKwst/cHXSw5OVnJycmu7czMzGL3i4mJKfG5stSEtgfGzXB9HRwcrPz8fNd2q+UzS2178b6XtvWm9prwOvn7nDWxbU2r119ta1q9Vdn20j9iAQBQU/jkPUB5eXk6c+aM6+u0tDRddtll6tq1q7Zu3SpJ2rp1q66++mpflAMAAADAUj65ApSdna0nn3xSklRYWKhrrrlGHTt2VKtWrTR//nxt3rzZtQw2AAAAAFQVnwSgJk2aaO7cuUUer1+/vh599FFflAAAAAAA/l0GGwAAAAB8yafLYAMAAAC283blR4nVHysTV4AAAAAAWIMABAAAAMAaBCAAAAAA1iAAAQAAALAGAQgAAACANQhAAAAAAKxBAAIAAABgDQIQAAAAAGsQgAAAAABYgwAEAAAAwBoEIAAAAADWIAABAAAAsAYBCAAAAIA1CEAAAAAArEEAAgAAAGANAhAAAAAAaxCAAAAAAFiDAAQAAADAGgQgAAAAANYgAAEAAACwBgEIAAAAgDUIQAAAAACsQQACAAAAYA0CEAAAAABrEIAAAAAAWIMABAAAAMAaBCAAAAAA1iAAAQAAALAGAQgAAACANQhAAAAAAKwR5O8CAADwt/z8fKWkpKigoECFhYXq0aOHhg8frqNHj2rBggU6deqU4uPjdc899ygoiKkTAGoyfosDAKxXp04dpaSkKDQ0VAUFBXr00UfVsWNHbdiwQYMHD1avXr20ZMkSbd68Wf379/d3uQCACuAWOACA9RwOh0JDQyVJhYWFKiwslMPhUHp6unr06CFJ6tOnj3bs2OHPMgEAlYArQAAASHI6nXrooYf0ww8/aMCAAWrSpInCwsIUGBgoSYqOjtbx48f9XCUAoKIIQAAASAoICNDcuXOVk5OjJ598Ut99953HbVNTU5WamipJmj17tmJiYrw6d3ZYmNe1hnnZxtuafCUoKKja1uat2tKX2tIPqfr2xdufean6/tz7oi+V3Q8CEAAAFwkPD1f79u31xRdfKDc3V4WFhQoMDNTx48cVHR1dbJvk5GQlJye7tjMzM706Z25urlf7h4WFed3G25p8JSYmptrW5q3a0pfa0g+p+vbF259fqfr+3PuiL+XpR2xsbInP8R4gAID1Tp48qZycHEnnV4RLS0tTXFyc2rdvr+3bt0uStmzZoq5du/qzTABAJeAKEADAellZWVq0aJGcTqeMMerZs6e6dOmiZs2aacGCBVq9erUuv/xy9e3b19+lAgAqiAAEALBeixYt9Ne//rXI402aNNGsWbP8UBEAoKpwCxwAAAAAaxCAAAAAAFiDAAQAAADAGgQgAAAAANYgAAEAAACwBgEIAAAAgDVYBhulOjBuhtv2keBg5efnu7ZbLZ/p65IAAACAciMAAQAAoEb4fv5Kr/bPDgtTbm6uV21+NnWMV/uj5iEAAQCASuHtf04l/oMKwPd4DxAAAAAAaxCAAAAAAFiDAAQAAADAGgQgAAAAANYgAAEAAACwBgEIAAAAgDVYBtvHSvtgUT5UFAAAAKhaXAECAAAAYA0CEAAAAABrcAscAADAJb6fv9LrNtlhYcrNzfV4/59NHeP1OQBUHFeAAAAAAFiDK0AAAAC1mLdXs7y9kiVxNQs1C1eAAAAAAFiDAAQAAADAGgQgAAAAANYgAAEAAACwBgEIAAAAgDUIQAAAAACsQQACAAAAYA0CEAAAAABrEIAAAAAAWIMABAAAAMAaBCAAAAAA1iAAAQAAALAGAQgAAACANQhAAAAAAKxBAAIAAABgDQIQAAAAAGsQgAAAAABYgwAEAAAAwBoEIAAAAADWIAABAAAAsAYBCAAAAIA1CEAAAAAArEEAAgAAAGANAhAAAAAAaxCAAAAAAFgjyN8F1EQHxs1w2z4SHKz8/HzXdqvlM31dEgAAAAAPcAUIAAAAgDUIQAAAAACsQQACAAAAYA0CEAAAAABrEIAAAAAAWIMABAAAAMAaBCAAAAAA1iAAAQAAALAGAQgAAACANQhAAAAAAKwR5O8C/OXAuBlu20eCg5Wfn+/abrV8pq9LAgAAAFDFuAIEAAAAwBoEIAAAAADWIAABAAAAsAYBCAAAAIA1fLoIgtPp1PTp0xUdHa3p06fr6NGjWrBggU6dOqX4+Hjdc889Cgqydl0GAAAAAFXMp1eAXn/9dcXFxbm2n3vuOQ0ePFgLFy5UeHi4Nm/e7MtyAAAAAFjGZwHop59+0q5du9SvXz9JkjFG6enp6tGjhySpT58+2rFjh6/KAQAAAGAhn91vtnLlSo0cOVJnzpyRJJ06dUphYWEKDAyUJEVHR+v48ePFtk1NTVVqaqokafbs2YqJiSl2v6CgoBKfu9SR4GC3bYfDoeCLHivtOFXVtqzaL27rzTkr0rYifb2UN9+fymrrj3PWxLY1rV5/ta1p9fqzLQAA1ZVPAtDHH3+syMhIxcfHKz093ev2ycnJSk5Odm1nZmYWu19MTEyJz13q4g89laTgSz4ItbTjVFXbsmq/uK0356xI24r09VLefH8qq60/zlkT29a0ev3VtqbVW5VtY2Njy3VMAAD8zScBaN++fdq5c6c++eQT5efn68yZM1q5cqVyc3NVWFiowMBAHT9+XNHR0b4oBwAAAIClfBKAbr/9dt1+++2SpPT0dK1fv15TpkzR3/72N23fvl29evXSli1b1LVrV1+UAwAAAMBSfv0coBEjRmjDhg265557dPr0afXt29ef5QAAAACo5Xz+oTvt27dX+/btJUlNmjTRrFmzfF0CAAAAAEv59QoQAAAAAPgSAQgAAACANQhAAAAAAKxBAAIAAABgDQIQAAAAAGsQgAAAAABYw+fLYAMAUN1kZmZq0aJFOnHihBwOh5KTkzVo0CCtXbtW77zzjiIiIiRJt912mzp37uznagEAFUEAAgBYLzAwUKNGjVJ8fLzOnDmj6dOnKzExUZI0ePBgDRkyxM8VAgAqCwEIAGC9Bg0aqEGDBpKkunXrKi4uTsePH/dzVQCAqlDjA9CBcTNcXx8JDlZ+fr5ru9Xymf4oCQBQgx09elSHDh1SQkKC9u7dq02bNmnbtm2Kj4/XHXfcoXr16vm7RABABdT4AAQAQGXJy8vTvHnzNGbMGIWFhal///4aNmyYJGnNmjVatWqVJk+eXKRdamqqUlNTJUmzZ89WTEyMV+fNDgvzav+AgACFednG25rKw9t+SHb3xRf9kGrP+JJqT1/4WfHvzwoBCAAASQUFBZo3b55++ctfqnv37pKkqKgo1/P9+vXTnDlzim2bnJys5ORk13ZmZqZX587NzfVq/7CwMK/beFtTeXhbk2R3X3zRD6n2jC+p9vSFn5Wq/1mJjY0t8TmWwQYAWM8Yo6efflpxcXG64YYbXI9nZWW5vv7oo4/UvHlzf5QHAKhEXAECAFhv37592rZtmy677DI9+OCDks4vef3BBx/oq6++ksPhUKNGjTRx4kQ/VwoAqCgCEADAem3atNHatWuLPM5n/gBA7cMtcAAAAACsQQACAAAAYA0CEAAAAABrEIAAAAAAWIMABAAAAMAaBCAAAAAA1iAAAQAAALAGAQgAAACANQhAAAAAAKxBAAIAAABgDQIQAAAAAGsQgAAAAABYgwAEAAAAwBoEIAAAAADWIAABAAAAsAYBCAAAAIA1gvxdAACgejgwbobb9pHgYOXn50uSWi2f6Y+SAACodFwBAgAAAGANAhAAAAAAaxCAAAAAAFiDAAQAAADAGgQgAAAAANYgAAEAAACwBgEIAAAAgDUIQAAAAACsQQACAAAAYA0CEAAAAABrEIAAAAAAWIMABAAAAMAaBCAAAAAA1iAAAQAAALAGAQgAAACANQhAAAAAAKxBAAIAAABgDQIQAAAAAGsQgAAAAABYgwAEAAAAwBoEIAAAAADWIAABAAAAsEaQvwsAAFSeA+NmuG0fCQ5Wfn6+JKnV8pn+KAkAgGqFK0AAAAAArEEAAgAAAGANAhAAAAAAaxCAAAAAAFiDRRAAoJopbSEDicUMAACoCK4AAQAAALAGAQgAAACANQhAAAAAAKxBAAIAAABgDQIQAAAAAGuwChyqTGkrWbGKFQAAAPyBK0AAAAAArEEAAgAAAGANAhAAAAAAaxCAAAAAAFiDAAQAAADAGgQgAAAAANYgAAEAAACwBgEIAAAAgDUIQAAAAACsQQACAAAAYI0gfxcAALXRgXEz3LaPBAcrPz/ftd1q+UxflwQAAMQVIAAAAAAWIQABAAAAsAYBCAAAAIA1CEAAAAAArEEAAgAAAGANAhAAAAAAaxCAAAAAAFiDAAQAAADAGiV+EOrmzZs9OkDfvn0rrRgAADzFPAUAKI8SA9B7773n+toYo3379ikqKkoNGzbUTz/9pBMnTqhNmzZMLAAAv2CeAgCUR4kBKCUlxfX18uXLdfXVV2vw4MGux15//XX98MMPVVsdAAAlYJ4CAJSHR+8Beu+993T99de7PTZw4EC3v74BAOAvzFMAAE95FICioqK0c+dOt8d27typiIiIKikKAABvME8BADxV4i1wFxs7dqzmzZun1157TQ0bNlRmZqa++eYbTZs2rarrAwCgTMxTAABPeRSAEhMTtXDhQu3evVvHjx9X586d1blzZ9WvX7+q6wMAoEzMUwAAT3kUgCQpIiJC7dq10/Hjx3XFFVdUZU0AAHitIvNUZmamFi1apBMnTsjhcCg5OVmDBg3S6dOnNX/+fB07dkyNGjXS1KlTVa9evSrqAQDAFzwKQJmZmfr73/+ur776SpL07LPPavv27dq9e7d++9vfVmV9AACUqaLzVGBgoEaNGqX4+HidOXNG06dPV2JiorZs2aIOHTpo6NChWrdundatW6eRI0dWcW8AAFXJo0UQlixZok6dOun//b//p6Cg85kpMTFRaWlpVVocAACeqOg81aBBA8XHx0uS6tatq7i4OB0/flw7duxQUlKSJCkpKUk7duyomg4AAHzGowC0f/9+DR06VAEB/7d7WFiYcnNzq6wwAAA8VZnz1NGjR3Xo0CElJCQoOztbDRo0kHR+pbns7OxKqxkA4B8e3QIXGRmpH374QbGxsa7HvvnmG8XExFRZYQAAeKqy5qm8vDzNmzdPY8aMUVhYmNtzDodDDoej2HapqalKTU2VJM2ePdvr82Zfcq6yBAQEFKmvLL6Ys73th2R3X3z1/6jaMr6k2tMXflb8+7PiUQC68cYbNWfOHA0dOlROp1Pvv/++XnnlFQ0dOrRSiwEAoDwqY54qKCjQvHnz9Mtf/lLdu3eXdD5YZWVlqUGDBsrKyirxc4WSk5OVnJzs2s7MzPSqfm+vVJXn6pa3NZVHea642dwXX/RDqj3jS6o9feFnpep/Vi7+g9ilPApAffv2Vf369ZWamqqGDRtq27Zt+s1vfqNu3bp5XQwAAJWtovOUMUZPP/204uLidMMNN7ge79q1q7Zu3aqhQ4dq69atuvrqq6uqCwAAH/F4Geyrr76aX/wAgGqrIvPUvn37tG3bNl122WV68MEHJUm33Xabhg4dqvnz52vz5s2uZbABADWbRwHIGKN33nlHH374oU6ePKknn3xSGRkZOnHihH7xi19UdY0AAJSqovNUmzZttHbt2mKfe/TRRyu7XACAH3m0CtyaNWv07rvvql+/fq578Bo2bKhXX321SosDAMATzFMAAE95dAVo69atmjNnjiIiIvTMM89Ikho3bqyjR496dJL8/HylpKSooKBAhYWF6tGjh4YPH66jR49qwYIFOnXqlOLj43XPPfe4Pr8BAABPVXSeAgDYw6O04XQ6FRoa6vZYXl5ekcdKUqdOHaWkpCg0NFQFBQV69NFH1bFjR23YsEGDBw9Wr169tGTJEm3evFn9+/f3vhcAAKtVdJ4CANjDo1vgOnXqpFWrVuncuXOSzt9rvWbNGnXp0sWjkzgcDtckVFhYqMLCQjkcDqWnp6tHjx6SpD59+vAJ2wCAcqnoPAUAsIdHAeiOO+5QVlaWxowZo9zcXN1xxx06duyYRowY4fGJnE6nHnzwQY0fP14dOnRQkyZNFBYWpsDAQElSdHS0jh8/Xr5eAACsVhnzFADADh7dAhcWFqYHH3xQ2dnZOnbsmGJiYhQVFeXViQICAjR37lzl5OToySef1Hfffedx29I+YftIcLDra4fDoeCLtkv71NiL21WXtmV9ym15+1qRtv7q66WCgoLK9SnA5W1nW9uaVq+/2nrTrqb/jvG2rb9VxjwFALCDxysO5OTkKC0tzfWJ2J06dVK9evW8PmF4eLjat2+vL774Qrm5uSosLFRgYKCOHz+u6OjoYtuU9gnb+fn5rq+Dg4Pdtkv71NiL96subcv6lNvy9rUibf3V10vFxMSU61OAy9vOtrY1rV5/tfWmXU3/HVNW29I+YdtfKmueAgDUbh7dAvf555/rrrvu0htvvKH9+/frzTff1N13363PPvvMo5OcPHlSOTk5ks5PsGlpaYqLi1P79u21fft2SdKWLVvUtWvXcnYDAGCzis5TAAB7eHQFaNmyZZo4caLbh8n997//1bJly7RgwYIy22dlZWnRokVyOp0yxqhnz57q0qWLmjVrpgULFmj16tW6/PLL1bdv3/L3BABgrYrOUwAAe3gUgLKyslyrtV3QrVs3LV682KOTtGjRQn/961+LPN6kSRPNmjXLo2MAAFCSis5TAAB7eHQLXO/evfXmm2+6PfbWW2+pd+/eVVIUAADeYJ4CAHjKoytAhw4d0ttvv63XXnvNtVx1dna2WrdurZSUFNd+jz/+eJUVCgBASZinAACe8igA9evXT/369avqWgAAKBfmKQCApzwKQH369KniMgAAKD/mKQCApzwKQO+//75atmypZs2a6bvvvtPixYsVEBCg8ePHKy4urqprBACgVMxTAABPebQIwpo1a1wfJrdq1Sq1atVKbdu21TPPPFOlxQEA4AnmKQCApzy6AnTy5ElFRUUpPz9f+/bt0/3336/AwEDdeeedVV0fAPjVgXEzXF8fCQ5Wfn6+a7vV8pn+KAnFYJ4CAHjKowAUERGhH374QYcPH1arVq1Up04dnT17tqprAwDAI8xTAABPeRSAbr75Zj300EMKCAjQ1KlTJUmfffaZWrRoUaXFAQDgCeYpAICnPF4FrmfPnpKkkJAQSVLr1q113333VV1lAAB4iHkKAOApjwKQ9H8TygWRkZGVXgwAAOXFPAUA8IRHq8ABAAAAQG1AAAIAAABgDQIQAAAAAGt49B6gH3/8sdjH69Spo6ioKAUEkKMAAP7DPAUA8JRHAWjKlCklPhcQEKAuXbpo/PjxioqKqrTCAADwFPMUAMBTHgWgSZMmKT09XbfccotiYmKUmZmpl156SVdccYXatWun559/XsuWLdP9999f1fUCAFAE8xQAwFMe3ROwdu1aTZo0SU2bNlVQUJCaNm2q8ePH66WXXlJcXJwmT56sjIyMqq4VAIBiMU8BADzl0RUgY4yOHTumuLg412OZmZlyOp2SpNDQUBUWFlZNhQAAlIF5CgD8472EG71uExYWptzcXI/3H+71GUrnUQAaNGiQ/vSnP6lPnz5q2LChjh8/rnfffVeDBg2SJO3atUtXXHFFJZcGAIBnmKcAAJ7yKAD96le/UosWLfTf//5Xhw4dUlRUlH73u9+pY8eOkqRu3bqpW7duVVooAAAlYZ4CAHjKowB08uRJdezY0TWRoOb5d+e7XV8HBwcrPz/ftT3dHwUBQCVingIAeMqjADR58mS1b99e11xzjbp166aQkJCqrgsAAI8xTwEAPOXRKnBPPfWUOnfurLfeeksTJkzQggULtHPnTt5QCgCoFpinAACe8ugKUEREhAYMGKABAwbo2LFj+uCDD7R69Wr961//0rJly6q6RgAASsU8BQDwlEcB6GLZ2dk6ceKETp06pfDw8KqoCdCBcTPcto9c9L6lVstn+qMkADUE8xQAoDQeBaBvvvlG77//vj744APl5+erZ8+eevDBB5WQkFDV9QEAUCbmKQCApzwKQH/84x/VvXt3TZw4Ue3bt1dAwPm3DjmdTtfXAAD4C/MUAMBTHgWgpUuXKijo/3Y9fPiwtmzZog8++ECLFy+usuIAAPAE8xQAwFMeBaCgoCCdPHlS77//vrZu3aqvvvpKbdu21ZgxY6q4PMB3SnvfkcR7j4DqjHkKAOCpUgNQQUGBdu7cqS1btujTTz9V06ZN1atXLx07dkxTp05VZGSkr+oEAKAI5ikAgLdKDUATJkxQQECAkpKSNHz4cMXHx0uS3nrrLZ8UBwBAaZinAADeKvWdoS1atFBOTo7279+vAwcO6PTp076qCwCAMjFPAQC8VeoVoMcee0zHjh3T1q1btX79eq1YsUKJiYk6e/Ysn64NAPA75ikAgLfKXAShUaNGGjZsmIYNG6a9e/dq69atcjgcevDBB3Xttddq5MiRvqgT8NjFixmwkAEkPli3tmOeAgB4w6NV4C5o06aN2rRpo7Fjx+qjjz7Stm3bqqouAB7gP/aAO+YpAEBZvApAFwQHB+uaa67RNddcU9n1ADUSS2gD1QvzFACgJOUKQABQHgRFAADgbwQgADUCt/sBAIDKUOoy2AAAAABQm3AFCPAzrmwAAAD4DgEIsBTLhQMAABtxCxwAAAAAaxCAAAAAAFiDAAQAAADAGgQgAAAAANZgEQQAXuHDTAEAQE3GFSAAAAAA1iAAAQAAALAGAQgAAACANXgPEAAAfvZewo1e7R8WFqbc3Fyv2gz3am8AqL24AgQAAADAGlwBqkH+3flu19fBl6y8Nd0fBQEAAAA1DFeAAAAAAFiDK0AAAACAD3n7vj+J9/5VJq4AAQAAALAGAQgAAACANQhAAAAAAKxBAAIAAABgDQIQAAAAAGsQgAAAAABYgwAEAAAAwBoEIAAAAADWIAABAAAAsAYBCAAAAIA1CEAAAAAArEEAAgAAAGCNIH8XAACAvz311FPatWuXIiMjNW/ePEnS2rVr9c477ygiIkKSdNttt6lz587+LBMAUAkIQAAA6/Xp00cDBw7UokWL3B4fPHiwhgwZ4qeqAABVgVvgAADWa9eunerVq+fvMgAAPsAVIAAASrBp0yZt27ZN8fHxuuOOOwhJAFALEIAAAChG//79NWzYMEnSmjVrtGrVKk2ePLnYfVNTU5WamipJmj17tmJiYrw6V1jYGa/2DwgIUFhYmFdtvK2pPLK9rEmyuy++6IfkfV+q6/dEqj198fZnXrK7L5XdDwIQAADFiIqKcn3dr18/zZkzp8R9k5OTlZyc7NrOzMz06ly5uble7R8WFuZ1G29rKg9va5Ls7osv+iHVnvEl1Z6+8LNS9T8rsbGxJT7He4AAAChGVlaW6+uPPvpIzZs392M1AIDKwhUgAID1FixYoIyMDJ06dUq//e1vNXz4cKWnp+urr76Sw+FQo0aNNHHiRH+XCQCoBAQgAID17rvvviKP9e3b1w+VAACqGrfAAQAAALAGV4AAAABQI7yXcKNX+5dn4YDhXu2NmogAhFL9u/PdbtvBwcHKz893bU/3dUEAgGrL2/+cSvwHFYDvcQscAAAAAGtwBcjHSruiwtUUAAAAoGpxBQgAAACANQhAAAAAAKzBLXAAAACX8MWCDizmAPgHAQgAAKAWY+lowB23wAEAAACwBgEIAAAAgDUIQAAAAACsQQACAAAAYA0CEAAAAABrEIAAAAAAWIMABAAAAMAaBCAAAAAA1iAAAQAAALAGAQgAAACANQhAAAAAAKwR5O8CaqJ/d77bbTs4OFj5+fmu7em+LggAAACAR7gCBAAAAMAaBCAAAAAA1iAAAQAAALAGAQgAAACANaxdBIGFDAAAAAD7cAUIAAAAgDV8cgUoMzNTixYt0okTJ+RwOJScnKxBgwbp9OnTmj9/vo4dO6ZGjRpp6tSpqlevni9KAgAAAGAhnwSgwMBAjRo1SvHx8Tpz5oymT5+uxMREbdmyRR06dNDQoUO1bt06rVu3TiNHjvRFSQAAAAAs5JNb4Bo0aKD4+HhJUt26dRUXF6fjx49rx44d/1979x0eVZX/cfwzSQghhDQSAkGq9CbSe427qwuKPAIWlOKugrAKLkgXcEG6FLFQBCnKCqK4q6AY6VWqCCFU6SWEFAghpMz8/uCXWQJpEyB3Jvf9eh4fM+XM/d4Z7sx85px7jlq3bi1Jat26tXbt2pUf5QAAAAAwqXyfBCEqKkp//PGHKlWqpPj4eAUEBEiS/P39FR8fn2mb8PBwhYeHS5ImTpyooKAg+21nPT3tf1ssFnnecfnO+93N0zM6w2U3N+PbZtfu7raObPN+2t7Pvt752kgZX5+c6n1QbR35N5HdNo1qy/OUu7Y8T7lr+zCfJwAAXEW+BqCkpCRNmzZNPXv2lLe3d4bbLBaLLBZLpu3CwsIUFhZmvxwd/b8v5XfO3Hb3TG533u9ud97PWdpm1+7uto5s837aOsO+3k9bZ9jX+2nL85S7tjxPuWv7IJ+n0NDQbB8LAABnlW+zwKWmpmratGlq2bKlGjduLEny8/NTbGysJCk2Nla+vr75VQ4AAAAAE8qXAGSz2fTpp5+qdOnS6tChg/36Bg0aaOPGjZKkjRs3qmHDhvlRDgAAAACTypchcEeOHNGmTZtUtmxZDR48WJL0wgsvqFOnTpo+fbrWrVtnnwYbAAAAAB6WfAlA1apV0/LlyzO97d13382PEgAAAAAg/84BAgAAAACjEYAAAAAAmEa+rwP0dnmsUQAAIABJREFUoK2o19/+991TxQ41oiAAAAAAToseIAAAAACmQQACAAAAYBoEIAAAAACmQQACAAAAYBoEIAAAAACmQQACAAAAYBoEIAAAAACmQQACAAAAYBoEIAAAAACmQQACAAAAYBoeRhcAAHAOK+r1z3DZ09NTycnJkqShRhQEAMBDQA8QAAAAANMgAAEAAAAwDQIQAAAAANMgAAEAAAAwDQIQAAAAANMgAAEAAAAwDQIQAAAAANMgAAEAAAAwDQIQAAAAANMgAAEAAAAwDQ+jCwAAPDgr6vXPcNnT01PJycmSpKFGFAQAgJOhBwgAAACAaRCAAAAAAJgGQ+AAwMlkN4xNYigbAAD3gx4gAAAAAKZBDxAeGk7GBgAAgLOhBwgAAACAaRCAAAAAAJgGAQgAAACAaRCAAAAAAJgGAQgAAACAaTALHAA8BKzlAwCAc6IHCAAAAIBpEIAAAAAAmAYBCAAAAIBpEIAAAAAAmAYBCAAAAIBpMAscAMD0Pv74Y+3du1d+fn6aNm2aJCkhIUHTp0/XlStXFBwcrIEDB8rHx8fgSgEA94seIACA6bVp00bDhw/PcN2qVatUu3ZtzZo1S7Vr19aqVasMqg4A8CARgAAAplejRo17end27dql1q1bS5Jat26tXbt2GVEaAOABIwABAJCJ+Ph4BQQESJL8/f0VHx9vcEUAgAeBc4AAAMiBxWKRxWLJ8vbw8HCFh4dLkiZOnKigoCCHHt/b+6ZD93dzc5O3t7dDbRytKS8c3Q/J3PuSH/shFZx/X1LB2ReOFWOPFQIQAACZ8PPzU2xsrAICAhQbGytfX98s7xsWFqawsDD75ejoaIe2lZiY6ND9vb29HW7jaE154WhNkrn3JT/2Qyo4/76kgrMvHCsP/1gJDQ3N8jaGwAEAkIkGDRpo48aNkqSNGzeqYcOGBlcEAHgQ6AECAJjejBkzFBERoevXr6tPnz7q2rWrOnXqpOnTp2vdunX2abABAK6PAAQAML0BAwZkev27776bz5UAAB42hsABAAAAMA0CEAAAAADTIAABAAAAMA0CEAAAAADTIAABAAAAMA0CEAAAAADTYBpsAMjGinr97X97enoqOTnZfnmoEQUBAID7Qg8QAAAAANMgAAEAAAAwDQIQAAAAANMgAAEAAAAwDQIQAAAAANMgAAEAAAAwDQIQAAAAANMgAAEAAAAwDRZChVO6c/FJKeMClCw+CQAAgLyiBwgAAACAaRCAAAAAAJgGQ+CA/5fdsDuJoXcAAAAFAQEIBc6dQYYQAwAAgDsRgAAUeEyqAQAA0hGAgAfAqOFzfLEHAABwDAEIQL7hPCsAAGA0AhAAl0BvFwAAeBAIQIDBjPpiz2QRAADAjFgHCAAAAIBp0AMEwCGcxwMAAFwZPUAAAAAATIMABAAAAMA0CEAAAAAATIMABAAAAMA0CEAAAAAATIMABAAAAMA0CEAAAAAATIMABAAAAMA0CEAAAAAATIMABAAAAMA0CEAAAAAATIMABAAAAMA0CEAAAAAATIMABAAAAMA0CEAAAAAATIMABAAAAMA0CEAAAAAATIMABAAAAMA0CEAAAAAATIMABAAAAMA0CEAAAAAATIMABAAAAMA0CEAAAAAATIMABAAAAMA0CEAAAAAATMMjPzby8ccfa+/evfLz89O0adMkSQkJCZo+fbquXLmi4OBgDRw4UD4+PvlRDgAAAACTypceoDZt2mj48OEZrlu1apVq166tWbNmqXbt2lq1alV+lAIAAADAxPIlANWoUeOe3p1du3apdevWkqTWrVtr165d+VEKAAAAABPLlyFwmYmPj1dAQIAkyd/fX/Hx8VneNzw8XOHh4ZKkiRMnKigoyH6bp2e0/W83N4s8PT3tl++8393ubOcsbbNrd3dbR7Z5P22dYV/vp60z7Ov9tOV5yl1bnqfctX2YzxMAAK7CsAB0J4vFIovFkuXtYWFhCgsLs1+Ojv7fh3RycrL9b09PzwyX77zf3e68n7O0za7d3W0d2eb9tHWGfb2fts6wr/fTlucpd215nnLX9kE+T6Ghodk+FgAAzsqwWeD8/PwUGxsrSYqNjZWvr69RpQAAAAAwCcMCUIMGDbRx40ZJ0saNG9WwYUOjSgEAAABgEvkyBG7GjBmKiIjQ9evX1adPH3Xt2lWdOnXS9OnTtW7dOvs02AAAAADwMOVLABowYECm17/77rv5sXkAAAAAkGTgEDgAAAAAyG8EIAAAAACmQQACAAAAYBoEIAAAAACmQQACAAAAYBoEIAAAAACmQQACAAAAYBoEIAAAAACmQQACAAAAYBoEIAAAAACmQQACAAAAYBoEIAAAAACmQQACAAAAYBoEIAAAAACmQQACAAAAYBoEIAAAAACmQQACAAAAYBoeRhcAAIAz69evn7y8vOTm5iZ3d3dNnDjR6JIAAPeBAAQAQA5Gjx4tX19fo8sAADwADIEDAAAAYBr0AAEAkIPx48dLkp544gmFhYXdc3t4eLjCw8MlSRMnTlRQUJBDj+/tfdOh+7u5ucnb29uhNo7WlBeO7odk7n3Jj/2QCs6/L6ng7AvHirHHCgEIAIBs/Otf/1JgYKDi4+M1btw4hYaGqkaNGhnuExYWliEYRUdHO7SNxMREh+7v7e3tcBtHa8oLR2uSzL0v+bEfUsH59yUVnH3hWHn4x0poaGiWtzEEDgCAbAQGBkqS/Pz81LBhQx0/ftzgigAA94MABABAFpKSknTz5k373wcOHFDZsmUNrgoAcD8YAgcAQBbi4+M1depUSVJaWppatGihunXrGlwVAOB+EIAAAMhCSEiIpkyZYnQZAIAHiCFwAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEyDAAQAAADANAhAAAAAAEzDw+gC9u/fr4ULF8pqtap9+/bq1KmT0SUBAGDH5xQAFCyG9gBZrVZ99tlnGj58uKZPn66tW7fq3LlzRpYEAIAdn1MAUPAYGoCOHz+ukiVLKiQkRB4eHmrWrJl27dplZEkAANjxOQUABY/FZrPZjNr4jh07tH//fvXp00eStGnTJh07dkyvvvpqhvuFh4crPDxckjRx4sR8rxMAYE58TgFAweMSkyCEhYVp4sSJOX6oDB06NM/bcLW2rlavUW1drV6j2rpavUa1dbV6jWxrNrn9nHpQCtJrw744n4KyHxL74qyM3hdDA1BgYKCuXr1qv3z16lUFBgYaWBEAAP/D5xQAFDyGBqBHH31UFy9eVFRUlFJTU7Vt2zY1aNDAyJIAALDjcwoACh73MWPGjDFq425ubipZsqQ+/PBD/fjjj2rZsqWaNGlyX49ZsWJF07R1tXqNautq9RrV1tXqNaqtq9VrZNuC4GF8Tj0oBem1YV+cT0HZD4l9cVZG7ouhkyAAAAAAQH5yiUkQAAAAAOBBIAABAAAAMA0CEAAAyDdnzpwxugTc5fr160aXAOQrQydBuF/nz5/XunXrtG3bNu3bt0+nT5+Wj4+PfH19H/p2T58+LT8/P3l4eNiv379/v0qWLJllu+PHjysmJkaBgYE6d+6cNm3apISEBJUqVcrhGmbPnq1GjRo53C4yMlI7duzQzZs3s61Vko4dO6YiRYqoUKFCSk5O1sqVK/Xf//5Xp06dUqVKlVSoUKEs265evVoBAQHy9vZ2qL7U1FRt3rxZ165dU0hIiLZs2aKff/5ZUVFRKl++vNzcss/sly9ftv+bOHDggKKiolSqVKlsawUAV2C1WmWxWIwu475NmzZNa9euVVpamkJDQ136/XnNmjUqVaqUPD09jS7lvgwePFiHDx9W4cKFVbJkSZf/d1ZQjpWCxNleE5cNQKtWrdKKFStUtmxZlS5dWoGBgbp586ZWrFihxMREVatWLU+Pu379elWoUCHL21evXq3Fixfr8uXLWr58uUqUKKHSpUtLkqZPn64nnngi03YrVqzQjz/+qD179igqKkrh4eEKDAzUpk2bFBsbq+rVq2e5zUmTJmnr1q32/7Zs2aJ9+/bp2LFj2rp1q1q0aJFl22HDhiksLEzS7ZXKV6xYoZCQEK1fv17Xrl3L9nkaP368nnzySbm5uWn+/Pmy2WwKCwvT1atXFR4ermbNmmXZdty4cdq0aZN27dql5ORklShRQoULF87y/ulmz56tCxcuKDIyUvv27dOpU6dUp04dRUZGavfu3dmGvtWrV+uHH35QYGCgIiIi5Ovrq9TUVC1ZskRlypRRiRIlcty+WcXHx8vLyyvft3v9+vVc/btwNYmJiVq+fLkWLFigr776Sv/5z3+0YcMGXb16VY8++mievyy9//77atmyZZbbXLFihTZs2KCUlBSVLVvWftv8+fNVr169LB83Li5OS5Ys0b59+1S5cmV99913WrBggQ4dOqRq1aqpSJEieaoXD9Y//vEPXb16VcWLF3/oP/Q9TG3btlXNmjUVERGhhQsX6tixY/L29lZISIjRpTlsz549WrhwoSIjI1WkSBGFhIQ41Ze83PrLX/4iHx8fbdiwQV9++aXi4uJUvHhxFStWzOjS8qSgHCuStHjxYgUGBsrPz8/oUu6Ls70mHjnfxTmtX79e06ZNy9ADI0kdOnTQ22+/rU6dOuXpcZcvX662bdtmefsvv/yiSZMmycvLS1FRUfrggw905coVPfXUU8puQr0dO3ZoypQpSklJ0WuvvaZPPvlE3t7eevrppzV8+HB17tw5y7YxMTEqXbq02rdvL4vFIpvNppMnT6pjx4457k9aWlqG2keNGiVfX1917NhRI0aMyPZ5stlscnd3lySdPHlSkyZNkiRVq1ZNgwcPzna7ISEhmjhxon7//Xdt27ZNy5cvV8WKFdW8eXM1btw4yy9UZ86c0dSpU5WWlqY+ffpozpw5cnNzU8uWLXPc5i+//KIpU6bIzc1NHTp00IQJEzRmzBg98cQTmjx5siZPnpxl28TERH377bfatWuX4uPjZbFY5OfnpwYNGqhTp04qWrRottvOyvvvv6/hw4dnu91Vq1bp6tWrevzxxzOE2fnz5+tvf/tblm3j4uK0YsUKWSwWdevWTWvWrNHOnTtVunRp9erVSwEBAZm2S0hIyHDZZrNp+PDh9tfXx8cny23u379fdevWtde+aNEinThxQmXKlFGPHj3k7++fZdsvvvhCHTt2lK+vr06cOKHp06fLYrEoLS1N/fv3V40aNbJsO2TIEDVq1EjNmzfPsefybidOnNDSpUsVEBCgF198UZ988omOHz+u0NBQvfbaa1n+4JGUlKTvvvtOO3fu1NWrV+Xh4aGSJUvqiSeeUJs2bbLd5vTp01WzZk2NGTPG/pzExcVpw4YNmj59ukaOHJll25MnT2Z526lTp7K87eOPP1apUqXUuHFjrV+/Xjt27NBbb72lQoUK6dixY9nW+9FHH6levXq6deuWxo4dqxYtWmjYsGHatWuX5s2bp3feeSfb9sgfU6ZM0datW/Xpp5/KZrOpbdu2atasmcM97c6gVKlSev7551WxYkUtXLhQp06dks1m0wsvvKDGjRsbXV6uPf/88+rWrZt+++03bdiwQZ999pmaNm2qdu3aOfxeZSSLxaI6deqoTp06OnjwoD788EOtXbtW5cqV00svvaQqVaoYXaJDCtKxUrp0ac2dO1dpaWlq06aNWrRo4ZL74WyvicsGIIvFotjYWAUHB2e4PjY2NsdfXwYNGpTp9TabTfHx8dm2tdls9l/KS5QooTFjxmjatGm6cuVKtgHI3d1dbm5uKly4sEJCQuwvuKenZ471TpgwQatXr9Y333yjl19+WeXLl5enp2e2XxjvrDchIUE2m002m82eur28vOzhJitlypTR+vXr1bZtW5UrV04nTpzQo48+qgsXLtwTPO9msVjk5uamxx57TI899phSU1O1f/9+bdmyRUuWLNFnn32WZb2pqalKSkrSrVu3lJiYKB8fH6WkpGQIc1lJS0uTm5ubUlJSlJSUJEkKCgrKsa0RX1glY760vvrqqwoKCspwXUxMjIYMGSKLxaLZs2dnuc1ly5bZA9DixYsVEBCgIUOGaOfOnZo7d262X5T37t2rl156SZK0dOlSDRgwQJUqVdKFCxc0a9YsTZw4Mcu2CQkJunHjhsaOHSt/f381b95czZo1U2BgYJZt0s2fP19du3bVjRs3NGrUKPXo0UOjRo3S77//rvnz52v8+PGZtps1a5YaNWqkESNGaPv27UpKSlLz5s21cuVKXbhwQS+++GKW24yKitKIESMyXOfv769OnTpp/fr12dY7bNiwLI/tGzduZNnu8uXL9ve2Ro0a6ZtvvtF7772Xq/ASHx+vJ598UpL0008/2X8YefLJJ7Vu3boc2yN/FClSRGFhYQoLC1NERIRmzpypRYsWqXHjxnruuedc5gv36dOntX79eu3bt0+1a9fWkCFDVLFiRcXExGjkyJEuFYCk2593/v7+8vf3l7u7u27cuKEPPvhAderUUffu3Y0uL1euX7+uzZs3a9OmTfLz81Pv3r3VoEEDnTp1Sh988IE++ugjo0t0SEE5ViSpffv2at++vS5cuKD169dr0KBBqlq1qtq3b69atWoZXV6uOdtr4rIBqGfPnnrvvfdUqlQpFS9eXJIUHR2tS5cu6dVXX822bXx8vEaMGHHPr/o2m02jRo3Ktq2fn59OnTql8uXLS7odJIYOHapPPvkk2xM7PTw8dOvWLRUuXDjDF73ExMQcz2tJ79Fo2rSpFi1aJD8/v1yFgfTHHzp0qGw2mz00BgQEKCkpKdvAJkl9+vTRwoUL9c0336hYsWIaOXKkihcvruLFi+v111/Ptu3dj+3h4aEGDRqoQYMGunXrVpbt2rZtqwEDBshqter555/XBx98oBIlSujYsWPZDrmTbr9JDBs2TJUqVVJkZKSeeeYZSdK1a9ey7dWQjPnCKhnzpbV79+46cOCAXn75ZfswqX79+jn8AXfixAlNmTJF0u2e140bN2Z7f6vVqrS0NLm7uys5OVmVKlWSJIWGhiolJSXbtj4+PnrllVf0yiuv6PDhw9q6dauGDBmiRx55RM2bN7cP88xMWlqaHn/8cUm3e6HSF7GsXbu2lixZkmW7K1eu2Ht6OnTooGHDhum5557TG2+8obfffjvbABQcHKzvvvtOrVu3vidQ3x0+7/bII4/otddey/TcwL59+2bZLjU1VVar1f5+0rlzZwUGBmr06NH2HwOycufx2rp16wy3Wa3WbNsi/1itVu3du1fr16/XlStX1LFjR7Vo0UKRkZGaMGGCZs6caXSJubJgwQK1b99eL774YobhoIGBgXr++ecNrMxxq1ev1saNG+Xr66t27dqpe/fu8vDwkNVq1VtvveUyAWjkyJH2kRbp36kk6dFHH81yaL8zKyjHSjqr1arz58/r/PnzKlasmMqVK6fvv/9e4eHhGjBggNHl5YqzvSYuG4Dq1q2rmTNn2icWkG6/eVaqVCnHQFGvXj0lJSXZQ8ydcupV6d+//z09J+7u7urfv3+2X8LGjh1rP9HzzvpSU1PVr1+/bLeZrnjx4nr77be1d+/eXI/Jz+pLrcViyXFImbe3t/r166fExERFRUXJarUqMDAw22FO6bI7ILM756NDhw72oBMYGKjWrVvr999/V1hYmP0Lc1aeeuop1a5dW+fPn1fHjh3t52b5+vpq7Nix2bY14gurZMyX1o4dO6pZs2ZatGiRihcvrq5du+Z6zHp8fLy+//572Ww23bx50x6s764nM3/60580YcIEderUSY899pgWLlyoxo0b6+DBg5kei1mpXr26qlevrt69e+vAgQPatm1btsdeoUKF9NtvvykxMVEWi0W//vqrGjVqpIiIiGzfKwoXLqzIyEhVq1ZNu3fvtodoNze3HPd1wIABWrVqlcaMGWPvVfb391f9+vU1cODAbNt26dIly8fv1atXlu3q16+vgwcPqk6dOvbr2rRpI39/fy1YsCDbbTZo0EBJSUny8vLK8AX00qVLCg0NzbYt8s+bb76pmjVr6umnn1bVqlXt1zdp0kQREREGVuaY7N6PW7VqlY+V3L+EhAQNGjTontEobm5uGjJkiEFVOW7GjBlZfg7k9ZQCIxWUY0WSPv/8c+3du1e1atVS586dM3wXeuuttwyszDHO9ppYbDl9kgMmkJCQoFWrVmn37t33fGHt1KlTtj1IO3bsUNmyZTP9opj+ZTsrS5cutY+7vtP+/fu1YMECzZo1K8u2X331lZ555pl7Ji+4dOmSvvjiC/3zn//Msm263bt369tvv1VUVJTmzZuX4/1XrFiR4fKf//xn+fr6Ki4uTkuXLlX//v2zbX/o0CGtXbtWFy9eVFpamoKCgtSwYUO1bds22yGZM2bMyPOvXKdOndIXX3whi8WiHj16aO3atdq4caMCAwP1+uuvZ3gjvtPp06f16aef6tKlS3rkkUfUt29fhYaG6tq1a9qyZYueeuqpbLd7/vx5Xb16VVWqVMnwGt15HlV2bWNiYlS5cmWH2mbVbt++ffZesAe9TeSf9JDq6i5evKgvv/xS586dy9D7m93wW2cXHx+fYV9y+uHM2Vy7dk3fffedzp07p+TkZPv1o0ePNrCqvCsox4p0+5z3pk2bZro/iYmJLnM+kLO9JgQgIAfp50EV1LbJycm6dOmSypYt6xL1OkPbnNqtXr1aP/30k0qXLq3Tp0+rZ8+eatiwoaTbEzqkTzjxINuuWbNGP/74Y562eT9tkX+Sk5O1bt26e76kvvHGGwZW5bhRo0apa9euWrRokYYMGaL169fLZrOpW7duRpfmsN27d2vx4sWKjY2Vr6+voqOjVbp0aX3wwQdGl+aQcePGqVmzZvrvf/+rv//979qwYYN8fX1dZgjf3QrKsZIuISFBly5dyrAvuTkP3Jk422vCQqhADpYvX16g23p6etrPBXKFep2hbU7t0meLfOeddzR69GitXLlSq1evlpTzUMG8tg0PD8/zNu+nLfLP7NmzFRcXp99++001atRQTEyMS05RnpycrNq1a8tmsyk4OFhdu3bV3r17jS4rT7766iuNHz9epUqV0kcffaRRo0apcuXKRpflsOvXr6tdu3Zyd3dXjRo19MYbb+jQoUNGl5VnBeVYkW5/JowePVrjx4/XihUr7P93Nc72mrjsOUDAg3Q/MwO6WltXq9eotkbMFnk/bY3YJvLXpUuX9Pbbb2v37t326XBdcYhSoUKFZLVaVapUKf34448KDAzM8ZxHZ+Xu7q5ixYrJZrPJarWqVq1aWrRokdFlOSx9ZteAgADt3btXAQEB9yyZ4EoKyrEi3R4VMGHCBI0YMUKjR4/W+fPntWzZMqPLcpizvSYEIED3NzOgq7V1tXqNamvEbJH309aIbSJ/pZ8nV7RoUZ05c0b+/v45hnFn1LNnTyUnJ6tXr1766quvdPDgwVxPBuRsihYtqqSkJFWvXl2zZs2Sn5+fSy7u3LlzZyUmJurll1/WwoULlZiYqB49ehhdVp4VlGNFuj1KI322xJSUFJUuXVoXLlwwuCrHOdtrQgACdH8zA7paW1er16i2RswWeT9tjdgm8ldYWJgSEhLUrVs3TZ48WUlJSeratavRZTksfRYrLy8vlz0nI93gwYPl6empHj16aPPmzUpMTNRzzz1ndFkOq1+/viSpbNmyLttTcqeCcqxIt2fEvXHjhho2bKhx48apaNGi98w66Aqc7TVhEgQAAPDQTZw4Mdsp911p2uiCIqcp8nv37p1PlSA3IiIilJiYqLp16+a4ID2yx7MHAIAT+/7777O9vUOHDvlUyf15+umnJUk7d+5UXFycWrZsKUnaunWr/Pz8jCzNYa+88kq2Yc5VzgOqWLGiJOnIkSM6d+6cfR2+HTt22NfScyUF5ViRlOk5WOkTFiUlJeW4wLuzcNbXhAAEAIATu3nzpiTpwoULOnHihBo0aCBJ2rNnjx599FEjS3NI+tDRxYsXa+LEifbrGzRooKFDhxpVVp4sXrxYkvTvf/9bAQEBatWqlWw2m7Zs2aLY2FiDq8u9Nm3aSJJ+/vlnvffee/ahsE888YRLDoUrKMeKdLtH1GKxyGazKTo6Wj4+PrLZbLpx44aCgoKyXOje2Tjra0IAAh6Cfv366fXXX1edOnX0zTffKCoqSn369MnTY82YMUPNmjXLdkHVh+H06dOaN2+exo0bl6/bBZBRly5dJN1elHLSpEn2qWO7dOmSIUi4ilu3buny5csKCQmRJEVFRekfKItWAAAaJUlEQVTWrVsGV5U3e/bs0ZQpU+yX//SnP2nw4MEut6ZRQkKCbt68ae9VSEpKcslZ4ArSsZIecD799FM1atRI9erVk3R7Yetdu3YZWZpDnPU1IQDB5d0ZNtJt2LBBv/zyi/71r38ZWNltnTt3ztX9xowZo5YtW6p9+/b2606fPq3Tp0/rrbfesl+3ZcsWffnll7p+/bpq166tN954I8uu8A0bNmjNmjW6dOmSihQpohYtWuiFF16w/8o3a9YsHTx4ULdu3ZK/v7+efvpp+/bLlSunokWLavfu3fZfbAAYJy4uLsO4fw8PD8XFxRlYUd706NFDY8aMUUhIiP3X7ddee83osvKkcOHC2rx5s5o3by7p9nA+V5wFrlOnTnrnnXdUs2ZN2Ww2HT582P7F1RUVlGNFko4dO5bhB9THH39cS5cuNbCivHG214QABDggLS3tntmyHqaff/5ZLVu2tI81P3v2rObOnauhQ4eqYsWKmjNnjubPn68BAwZk2j45OVk9e/ZU5cqVde3aNU2aNEk+Pj7q1KmTJOnZZ59V3759VahQIZ0/f15jxoxRhQoV7OPCW7RoofDwcAIQ4ARat26t4cOHq2HDhpKkXbt2qXXr1gZX5bi6detq1qxZOn/+vCSpdOnSKlSokMFV5c2bb76pzz//XJ9//rkkqWrVqnrzzTeNLSoP2rZtq8cff1zHjh2TJHXv3l3+/v4GV5V3mR0r6cP9XE1gYKBWrlxpP2duy5YtCgwMNLgqxznb+xcBCKZw7tw5zZ8/X6dOnVJgYKBefPFF+5f6u3te7u496tq1q3r37q3Vq1crLS0t03G3mzZt0r///W8lJSXdc0Lf8uXLdenSJb355ptKTk7Wp59+qv3799sXAhwyZIjWrFmjw4cP69ixY/r888/Vpk0bvfrqq9q/f7/69+9vf6zNmzerfv369rH03bp108CBA3Xz5s1MV1T+05/+ZP87MDBQLVu21MGDB+3XlSlTxv63xWKRxWLRpUuX7AGoZs2a+vTTT5WSkuKyX1CAgqJz586qW7euIiMjJUlvvPGGKlSoYHBVjtu+fbvq1q2r8uXLa+XKlfr666/VuXNn+/uOKylRooTeeecdo8u4b5GRkSpfvrwaNmyoTZs26bvvvtNTTz3lktMtSwXnWJGkt956SytWrNDUqVNlsVhUvXr1DKNCXIWzvSYEIBR4qampmjRpktq2bauRI0cqMjJSkydP1sSJExUaGpqrx9i1a5fef/99+2Jkdzp37pzmzZunYcOGqXLlyvryyy919erVTB9n48aNSkxM1CeffKJChQrp1KlT8vT01AsvvKAjR45kCGJJSUmKiorKUOO5c+dUpUoV++WSJUvKw8NDFy9ezNWXh4iIiAyhR5Lmz5+vDRs2KDk5WRUqVLCPM5ZuhyYPDw9duHBB5cqVy/HxATxc5cuXl7+/v6xWqyQpOjpaQUFBBlflmJUrV6pp06aKjIzUwYMH1bFjR82fP1/vv/++0aU5bOnSpercubM8PT31/vvv6/Tp0+rRo4datWpldGkOmT9/vqZMmaJTp07phx9+UNu2bTV79myNHTvW6NIckpiYKG9vbyUkJKhEiRIqUaKE/baEhASXmTktndVq1YIFC1yyVzEzzvT+RQBCgTBlypQMQ9NSU1PtvywcO3ZMSUlJ6tSpk9zc3FSrVi3Vq1dPW7ZsyfUiXM8++2yWb5w7duy4p1fmxx9/zPS+7u7uSkhI0KVLl1SuXLlsQ0tiYqKk24sFpktKSpK3t3eG+3l7e9tnWcnOunXrdPLkyXsmY/jb3/6m3r176+jRozp06NA9awt4eXnpxo0bOT4+gIdrzZo1+vrrr+Xn5yc3NzfZbDZZLBZNnTrV6NIc4ubmJknau3ev2rdvr3r16unf//63wVXlzW+//abu3bvr119/VXBwsAYNGqTRo0e7XAByd3eXxWLR7t279ec//1nt2rXT+vXrjS7LYbNmzdLQoUPtM6ilSz9WZs+ebWB1jnNzc9OVK1eUmprq8uv+ONv7l2s/m8D/Gzx4cKaTIEhSbGysgoKC7B+6khQcHKyYmJhcP37x4sWzvC0mJibD7V5eXipWrFim923VqpWuXr2qGTNmKDExUS1bttTzzz+f6RtbetBJSkqy9zx5eXndE3bSh79t3rxZc+fOlSRVr15dw4cPt9/n119/1bJlyzRq1Cj5+vresy03NzdVq1ZNmzZt0tq1a/XUU0/Zb0tKSlLRokWz3H8A+WP16tWaMWNGlu8vriIwMFBz587VgQMH9MwzzyglJUWuuiZ7+i/Ze/fuVdOmTe/5gcpVeHl56dtvv9XmzZs1duxYWa1WpaamGl2Ww4YOHSqbzaaxY8e6XM9oVkJCQjRq1CjVr18/ww+irrSmkeR8718EIBR4AQEBio6OltVqtYeg6OholSpVStLtWXzunII1s1lJslvwLiAgwH4yr3R7itfr169nel8PDw916dJFXbp0UVRUlCZMmKDQ0FC1a9funm14eXkpJCREFy5csIeWRx55RKdPn7bf5/Lly0pJSVGpUqVUsWJF+0mSd9q/f7/mzJmjYcOG2RdRy4rVatXly5ftl2NiYpSamprroYIAHp6goCCX/YJ9p4EDB2r//v3q2LGjihYtqtjYWHXv3t3osvKkXr16GjBggDw9PfW3v/1N165dc8nzJQcOHKgtW7aoT58+8vf3V3R0tH3hWldjsVg0YcIETZs2zehSHoiQkBD7jIm5Ge3hrJzt/YsAhAKvcuXKKly4sP7zn/+oQ4cOOnLkiPbs2aMJEyZIuj0m9ddff1X79u0VGxurdevWObQqeZMmTTR8+HBFRkaqUqVK+uqrr7L8NfPgwYPy9fXVI488Im9vb3l4eNiDj5+fX4bwId2e7jIiIkLVqlWTJLVs2VIjR47U4cOHVaFCBX311Vdq3LhxphMgpG9v1qxZGjRokCpVqpThtvj4eB08eFD169eXp6enDhw4oK1bt2Y4uTIiIkK1atVyyQ90oKApUaKExowZo3r16mU4Jl3tl+DChQvLz89PkZGRKlWqlNzd3e0/SLmal156Sc8884y8vb3l5uYmT09Pl5sUwWq1aubMmRkWPg0KCnLJGQbTVahQQcePH7/nc88VufJ05HdytvcvAhAKPA8PDw0ZMkTz58/Xt99+q8DAQPXv31+lS5eWJP31r3/ViRMn9Pe//13lypVTixYt9Pvvv+f68cuUKaNXX31VM2fO1K1bt9ShQ4csh8zFxcVp3rx5iomJkZeXl5o2bWofK/7UU0/po48+sk993bt3b4WFhWnGjBl69tlnZbFYVKZMGf3973/XrFmzlJCQYF8HKCsrV65UYmKiPexJ/xseZ7FYtHbtWs2bN082m01BQUHq0aNHhimvN2/erCeeeCLXzwWAhycoKEhBQUFKTU11yeFJ6VasWKETJ07o4sWLatu2rVJTU/Xhhx86xbptjrp165Z++uknRUdH6/XXX1dsbKwuXLig+vXrG11arrm5uclisdgnECgIjh8/rhEjRqhEiRIqXLiw4eeb3I+sJqK4M7C6Amd7/7LYXHXgLWASM2fOVNOmTdWoUaN83e7p06c1d+5cjR8/Pl+3CyB7SUlJkjJOkOJKBg8erMmTJ2vIkCGaPHmyJGnQoEEu+eV0+vTpqlixojZt2qRp06bp1q1bGjlypKZMmWJ0aQ6ZPHmy/vjjD9WpUyfDQq69e/c2sCrHpc8qduXKlUxvd8VpvU+ePGn/Ozk5WTt37pS7u7vLDht1FvQAAU7OqPn+y5UrR/gBnMiZM2c0e/ZsJSQkSJKKFSum/v373zO1vbNLH/qbPvw3PdC5osuXL2vgwIHaunWrJGUID66kUaNG+f4j28MwZcoUTZo0ScHBwZo6daoGDRpkdEn37e7ZYqtVq6Zhw4YZVE3eOVtPFgEIAAAXMHfuXL3yyiuqVauWJOnQoUOaM2eOxo0bZ3BljmnatKnmzp2rGzduKDw8XOvXr7evf+ZqPDw8lJycbA9zly5dcsnpitu0aWN0CQ/EnYOaoqKiDKzkwUn/wUO6fb7WyZMn7ctkuJKXX37Z/vedPVlGcb2jFAAAE7p165Y9/EhSzZo1M8xg6SqefvppHThwQEWKFNGFCxfUrVu3DMsYuJKuXbtq/Pjxio6O1qxZs3TkyJFsz8t0Vv369ct0tlNXWzfnzn3IbvZWV5K+ppHNZpO7u7tKlCihvn37Gl2Ww5ytJ4tzgAAAcAFTpkxRhQoV7BOnbN68WSdPntTgwYMNrszcrl+/rmPHjslms6ly5cqZrrXm7O5cuiElJUXbt29XQkKCunXrZmBVjuvWrZu8vLxks9mUnJxsH5KYPgnCokWLDK7QccnJyfa1ANOlpKS43OysmfVkLVy4UDNnzjSkHgIQAAAuICEhQcuXL9eRI0ck3f4FtUuXLvLx8TG4Mse88sor9l/n02eE8vLycskvp9Lt9dKuXLmitLQ0+3U1atQwsKIHY8iQIZo0aZLRZZheZq+DK742d/Yyuru7Kzg4WM8995x9mY/8xhA4AABcgI+Pj8vNypWZxYsX2/+22WzatWuXjh07ZmBFebd06VJt375djzzyiP3LncVicbkAdOdMYzabTSdOnJDVajWwIsTFxSkmJkbJycn6448/7Oc33bx506WGvh4/flxBQUH66KOPJEkbNmzQzp07FRwcrEceecSwughAAAA4sZx+6R0yZEg+VXJ/0tLS7jnp2WKxqFGjRvr666/10ksvGVRZ3u3atUszZsxwueFId1uyZIn9bzc3NwUHB2vgwIEGVoT9+/dr48aNunr1aoYfDby8vPTCCy8YWJlj5s2bp1GjRkm6vbj6smXL1KtXL506dUpz5szRP//5T0PqIgABAODEjh49qqCgIDVv3tylV7YfPny4Jk2apJ07d9qvS+9tcNUAERISorS0NJetP52rLappBm3atFGbNm20Y8cONWnSxOhy8sxqtdqH6W7btk3t27dXkyZN1KRJE0PPXyQAAQDgxObNm6cDBw5oy5Yt2rJli+rVq6fmzZu73Po/6fbs2WP/O/1cAFfpxbqbp6enBg8erNq1a2eY/trVhiqmpKRo586dioqKyjD07bnnnjOwKkhSkyZNtHfvXp09e1YpKSn2613ltbFarfbe34MHD+q1117LcJtRCEAAADgxNzc31a1bV3Xr1lVKSoq2bt2qMWPGqEuXLvrLX/5idHm5Fh8fr++///6e4GaxWLRp0yZ16NDBoMryrkGDBmrQoIHRZdy3yZMny9vbWxUrVnT53qyCZu7cuUpOTtahQ4fUrl077dixw6V6gps3b64xY8aoWLFi8vT0VPXq1SXdXjPL29vbsLoIQAAAOLmUlBTt3btXW7du1ZUrV/Tkk0+qUaNGRpflEKvVqqSkJBWkyWcLygKiMTExGjFihNFlIBNHjx7V1KlTNWjQIHXp0kUdO3bU+++/b3RZuda5c2fVqlVLcXFxqlOnjn2yEKvVql69ehlWFwEIAAAnNnv2bJ09e1aPP/64nnvuOZUtW9bokvIkICDAZYbt5OSf//xntgttTp06NR+ruX9VqlTRmTNnXPbfVkGWvgZQ4cKFFRMTIx8fH8XGxhpclWOqVKlyz3WhoaEGVPI/BCAAAJzY5s2bVbhwYV28eFFr1qyxX+9qizsWpJ6foUOHSpJ++uknSbIvTrtp06Zsg5GzSQ9yaWlp2rBhg0qUKKFChQrZ/225WpAriOrVq6cbN27o6aeftv+7a9euncFVuT4WQgUAAA9dQkKCyy3ampN33nlHkydPznCdKy1S2atXr3vqv1NwcHA+VoM7pa+f4+/vL0nauHGjNm/erNDQUHXt2rXAHUv5zc3oAgAAQMFXEL+w2Ww2RUZG2i8fOXLEpRYQLVGihIKDg7P8D8aZN2+efWbBiIgIffnllwoLC5O3t7fmzJljcHWujyFwAAAAedC3b1998sknSkxMlCR5e3urb9++BleVe+kz82XFFWfmKyicdf2cgoIABAAAkAcVK1bUlClTMgQgV1IQZ+YrKJx1/ZyCggAEAACQB3FxcVq2bJliY2M1fPhwnTt3TkePHnWZk9QL0sx8BY2zrp9TUHAOEAAAQB58/PHHeuyxx+zTEpcqVUo//PCDwVXlHj0/zqtz5856+eWX1aZNG7333ntOs35OQUEPEAAAQB5cv35dzZo106pVqyRJ7u7ucnNznd+W3333XaNLQDaccf2cgsJ1jlIAAAAnUrhwYV2/ft3+6/zRo0ddanhSQZyZD8gN1gECAABwwA8//KCqVatKkhYtWqSzZ8+qTJkyunbtmgYOHKjy5csbWyCAbBGAAAAAHLB48WIdPXpU58+fV+nSpRUYGKjq1aurefPm8vX1Nbo8ADkgAAEAAORBamqqTpw4oSNHjujo0aM6duyYvL29NX36dKNLA5ANJkEAAADIg+TkZN28eVOJiYm6efOmAgICVLZsWaPLApADeoAAAAAcMGfOHJ07d05eXl6qXLmy/T8mFQBcA7PAAQAAOCA6OlopKSny9/dXYGCgihcvrqJFixpdFoBcogcIAADAQTabTWfPntXRo0d15MgRnT17Vj4+PqpSpYq6du1qdHkAssE5QAAAAA6yWCwqW7asihYtKm9vb3l7e2vv3r06fvw4AQhwcvQAAQAAOGD16tX2nh8PDw9VqVJFVatWVZUqVVS2bFm5uXGGAeDM6AECAABwwJUrV9SkSRP16NFDAQEBRpcDwEH0AAEAAAAwDfpoAQAAAJgGAQgAAACAaRCAAAAACrhDhw6pT58+D+Sxfv31V/Xt21cvv/yy/vjjjxzvP2bMGP3yyy8PZNvAg8AkCAAAAMi1JUuWqHfv3mrYsKHRpQB5Qg8QAAAAcu3KlSsqU6aM0WUAeUYPEAAAgIHWr1+vnTt3aujQoZKkN998U+XLl9fbb78tSerbt6+GDBmi8uXL6/z581qwYIFOnjwpX19fdevWTc2aNZMkpaSkaNmyZdq+fbtSU1PVsGFD9ezZU56envdsc/Xq1fr55581cuRIFS9ePMNtVqtV3377rX755RclJyerbt266t27twoVKqTevXvLarVq8ODB8vf314cffnjPYx84cEALFixQbGysWrVqpTsnHL506ZLmzJmj06dPy2Kx6LHHHtOrr76qokWL6j//+Y+OHj2qQYMG2e+/YMECWSwW9erV6/6faOD/0QMEAABgoBo1aigyMlJWq1UxMTFKTU3V0aNHJUmXL19WUlKSypYtq6SkJI0bN04tWrTQ/PnzNWDAAH322Wc6d+6cJOmLL77QxYsXNWXKFM2aNUsxMTH6+uuv79ne119/rY0bN2rs2LH3hB9J2rBhgzZs2KDRo0dr9uzZSkpK0meffaZChQppyZIlkqQpU6ZkGn6uXbumqVOn6vnnn9dnn32mkJAQHTlyJMN9nn32Wc2ZM0fTp0/X1atXtWLFCklSy5Yt9dtvv+nGjRuSpLS0NG3btk2tW7e+j2cXuBcBCAAAwEAhISEqUqSITp06pcOHD+uxxx5TQECAzp8/r4iICFWrVk1ubm7au3evgoOD1bZtW7m7u6tChQpq3Lixtm/fLpvNpl9++UU9evSQj4+PihQpos6dO2vr1q327dhsNi1atEi//fabRo8eLV9f30zr2bJlizp06KCQkBB5eXnpxRdf1LZt25SWlpbjvuzbt09lypRRkyZN5OHhob/+9a/y9/e3316yZEnVqVNHhQoVkq+vr/76178qIiJCkhQQEKDq1atr+/btkqT9+/erWLFiqlix4v08vcA9GAIHAABgsOrVqysiIkKXLl1SjRo1VLRoUUVEROjo0aOqUaOGpNvn3hw7dkw9e/a0t0tLS1OrVq107do13bp1yz6MTrodeKxWq/1yYmKiwsPDNXDgQHl7e2dZS2xsrIKDg+2Xg4KClJaWpvj4eAUGBma7H7GxsRl6lSwWS4bLcXFx+vzzz3X48GElJSXJarXKx8fHfnvr1q21du1ahYWFafPmzWrVqlW22wPyggAEAABgsBo1amjPnj2KiorSs88+q6JFi2rz5s06evSo/vKXv0iSihcvrho1amjUqFH3tLdarfL09NQHH3yQZUgpWrSo/vGPf2j69OkaNGiQqlWrlun9AgICdOXKFfvl6Ohoubu7y8/PL8f98Pf319WrV+2XbTZbhsvLli2TJE2bNk0+Pj769ddftWDBAvvtDRs21Pz583XmzBnt2bNH3bt3z3GbgKMYAgcAAGCwGjVq6NChQ0pOTlbx4sVVrVo17d+/XwkJCapQoYIkqX79+rp48aI2bdqk1NRUpaam6vjx4zp37pzc3NzUvn17ff7554qPj5ckxcTEaP/+/Rm2U7NmTb355puaNm2ajh8/nmktzZs31w8//KCoqCglJSVp2bJlatq0qdzd3XPcj3r16uns2bPauXOn0tLStGbNGsXFxdlvv3nzpry8vOTt7a2YmBj997//zdDe09NTjRs31qxZs1SpUiUFBQU59DwCuUEAAgAAMFhoaKi8vLxUvXp1SZK3t7dCQkJUtWpVubnd/rpWpEgRjRw5Ulu3btXrr7+u1157TV988YVSU1MlSS+99JJKliypESNGqEePHvrXv/6lCxcu3LOtOnXqqG/fvpo0aZJOnjx5z+1t27ZVq1atNHr0aPXr188++1tu+Pr66u2339aXX36p3r176+LFi6patar99i5duuiPP/5Qjx49NGHCBDVq1Oiex2jTpo3OnDnD8Dc8NBbbnXMTAgAAAAaKjo7WgAEDNHfu3GzPVQLyih4gAAAAOAWr1arvv/9ezZo1I/zgoSEAAQAAwHBJSUnq0aOHDhw4oK5duxpdDgowhsABAAAAMA16gAAAAACYBgEIAAAAgGkQgAAAAACYBgEIAAAAgGkQgAAAAACYBgEIAAAAgGn8H3PAA80L0Um3AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1008x864 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "1149925e8570ba532043af052a8d8cfba26e1715",
        "_cell_guid": "dd152426-0a08-4ec2-a267-d89f62bb1aeb",
        "id": "bJ1aaM93kEvN"
      },
      "source": [
        "From the above graphs, it is not that people prefer travelling more on Sunday and Monday. Due to fewer no of pickups in early morning hours, average speed also rises."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "99ed3a372d271a50d0712f800c2c378a6993f260",
        "_cell_guid": "530e8343-daa0-41e5-990a-43b239dba596",
        "id": "isy_VTdekEvO"
      },
      "source": [
        "How our **train and test datset top 5 entries** look like after creating few new columns"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "c882caabc7c60f7d5bd60432a03e714aa8ecd467",
        "_cell_guid": "681583da-cedb-42a5-9d14-02262f8283d9",
        "id": "DgZZsyG2kEvO"
      },
      "source": [
        "#Dropping log_speed column\n",
        "train=train.drop('log_speed',axis=1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "ad400d6b38f168020f985c2c03aee4d6413c2a6c",
        "_cell_guid": "7d0fa037-9aba-402e-bd04-5547f90b65b2",
        "id": "vxaSO35ZkEvR",
        "outputId": "fb1b85d1-b29d-4d69-a719-1748fb1fa860",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        }
      },
      "source": [
        "train.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>vendor_id</th>\n",
              "      <th>pickup_datetime</th>\n",
              "      <th>dropoff_datetime</th>\n",
              "      <th>passenger_count</th>\n",
              "      <th>pickup_longitude</th>\n",
              "      <th>pickup_latitude</th>\n",
              "      <th>dropoff_longitude</th>\n",
              "      <th>dropoff_latitude</th>\n",
              "      <th>store_and_fwd_flag</th>\n",
              "      <th>trip_duration</th>\n",
              "      <th>mm_pickup</th>\n",
              "      <th>mm_dropoff</th>\n",
              "      <th>dow_pickup</th>\n",
              "      <th>dow_dropoff</th>\n",
              "      <th>yday</th>\n",
              "      <th>hh_pickup</th>\n",
              "      <th>hh_dropoff</th>\n",
              "      <th>distance_km</th>\n",
              "      <th>log_distance</th>\n",
              "      <th>speed</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id2875421</td>\n",
              "      <td>2</td>\n",
              "      <td>2016-03-14 17:24:55</td>\n",
              "      <td>2016-03-14 17:32:30</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.982155</td>\n",
              "      <td>40.767937</td>\n",
              "      <td>-73.964630</td>\n",
              "      <td>40.765602</td>\n",
              "      <td>N</td>\n",
              "      <td>455</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>74</td>\n",
              "      <td>17</td>\n",
              "      <td>17</td>\n",
              "      <td>1.648373</td>\n",
              "      <td>0.973945</td>\n",
              "      <td>13.042071</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id2377394</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-06-12 00:43:35</td>\n",
              "      <td>2016-06-12 00:54:38</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.980415</td>\n",
              "      <td>40.738564</td>\n",
              "      <td>-73.999481</td>\n",
              "      <td>40.731152</td>\n",
              "      <td>N</td>\n",
              "      <td>663</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>-92</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.986058</td>\n",
              "      <td>1.093954</td>\n",
              "      <td>10.784025</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id3858529</td>\n",
              "      <td>2</td>\n",
              "      <td>2016-01-19 11:35:24</td>\n",
              "      <td>2016-01-19 12:10:48</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.979027</td>\n",
              "      <td>40.763939</td>\n",
              "      <td>-74.005333</td>\n",
              "      <td>40.710087</td>\n",
              "      <td>N</td>\n",
              "      <td>2124</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>19</td>\n",
              "      <td>11</td>\n",
              "      <td>12</td>\n",
              "      <td>7.023608</td>\n",
              "      <td>2.082388</td>\n",
              "      <td>11.904421</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id3504673</td>\n",
              "      <td>2</td>\n",
              "      <td>2016-04-06 19:32:31</td>\n",
              "      <td>2016-04-06 19:39:40</td>\n",
              "      <td>1</td>\n",
              "      <td>-74.010040</td>\n",
              "      <td>40.719971</td>\n",
              "      <td>-74.012268</td>\n",
              "      <td>40.706718</td>\n",
              "      <td>N</td>\n",
              "      <td>429</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>97</td>\n",
              "      <td>19</td>\n",
              "      <td>19</td>\n",
              "      <td>1.634048</td>\n",
              "      <td>0.968522</td>\n",
              "      <td>13.712293</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id2181028</td>\n",
              "      <td>2</td>\n",
              "      <td>2016-03-26 13:30:55</td>\n",
              "      <td>2016-03-26 13:38:10</td>\n",
              "      <td>1</td>\n",
              "      <td>-73.973053</td>\n",
              "      <td>40.793209</td>\n",
              "      <td>-73.972923</td>\n",
              "      <td>40.782520</td>\n",
              "      <td>N</td>\n",
              "      <td>435</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>86</td>\n",
              "      <td>13</td>\n",
              "      <td>13</td>\n",
              "      <td>1.307447</td>\n",
              "      <td>0.836142</td>\n",
              "      <td>10.820254</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          id  vendor_id  ... log_distance      speed\n",
              "0  id2875421          2  ...     0.973945  13.042071\n",
              "1  id2377394          1  ...     1.093954  10.784025\n",
              "2  id3858529          2  ...     2.082388  11.904421\n",
              "3  id3504673          2  ...     0.968522  13.712293\n",
              "4  id2181028          2  ...     0.836142  10.820254\n",
              "\n",
              "[5 rows x 21 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "0eab870e0dc9fe701d0b27e349f9571dfde1f7ef",
        "_cell_guid": "ee1bfa46-3d54-49c7-bc16-3ff127c4e3a4",
        "id": "v0mo7ovBkEvT"
      },
      "source": [
        "Analyzing **NYC Map**(pickups and dropoffs)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "be0974ec8de2b791f66d124ccd7a4a45e0496365",
        "_cell_guid": "7af557ea-cac4-4cab-8261-4216ca74bcc9",
        "id": "iR2R-wBCkEvU",
        "outputId": "fa9faa9a-32d1-4a6c-9fc4-58f3bfdce9f5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 462
        }
      },
      "source": [
        "#Plotting the pickup and dropoff locations of New York\n",
        "f, (ax1, ax2) = plt.subplots(1, 2, sharey=True,figsize=(10,7))\n",
        "\n",
        "#Plotting pickup map in  NYC\n",
        "Pickups=train.plot(kind='scatter',x='pickup_longitude',y='pickup_latitude',s=.02,alpha=.6,xlim=(long_min,long_max),ylim=(lat_min,lat_max),color='gold',subplots=True,ax=ax1)\n",
        "ax1.set_title('Pickups in New York City')\n",
        "# ax1.set_axis_bgcolor('black') # black as a background color\n",
        "pass\n",
        "\n",
        "#Plotting pickup map in  NYC\n",
        "Dropoffs=train.plot(kind='scatter',x='dropoff_longitude',y='dropoff_latitude',s=.02,alpha=.6,xlim=(long_min,long_max),ylim=(lat_min,lat_max),color='gold',subplots=True,ax=ax2)\n",
        "ax2.set_title('Dropoffs in New York City')\n",
        "# ax2.set_axis_bgcolor('black') # black as a background color\n",
        "pass\n",
        "\n",
        "fig.tight_layout()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "12d0923f71dd6f90ef7fd57aaa34e0d5d1b95a57",
        "_cell_guid": "5313ced3-89a4-4e6c-8758-94273f133596",
        "id": "YCXOjv3kkEvW"
      },
      "source": [
        "Pickups are almost concentrated in Manhatten and dropoffs across the NYC.\n",
        "This approximately could explain the reason why Vendor 2 pickups were greater than Vendor 1. May be Vendor 2 was operating mostly in the Manhatten region."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "4d4236ac4b4ba51ccdb679fdbb4a7df9556d3ae5",
        "_cell_guid": "d34ce720-18ff-474f-bad6-93c6a1c001fe",
        "id": "fixBLlOVkEvX"
      },
      "source": [
        "Analyzing NYC Map in 4 shifts:\n",
        "\n",
        "> Indented block\n",
        "\n",
        "\n",
        "Shift 1 - 7AM to 11 AM\n",
        "Shift 2 - 11AM to 5PM\n",
        "Shift 3 - 5PM to 11PM\n",
        "Shift 4 - 11PM to 7AM"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "0b86c19c156560bc8ee07509f8f30c445761900c",
        "_cell_guid": "7abe901d-6fea-48a5-b1f4-2ae1c18c800b",
        "id": "EfGlnv7KkEvX",
        "outputId": "b9477a11-d9f6-49b6-e83a-81717f718409",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 462
        }
      },
      "source": [
        "f, (ax1, ax2) = plt.subplots(1, 2, sharey=True,figsize=(10,7))\n",
        "\n",
        "#Shift 1\n",
        "Mtime=train[(train['hh_dropoff']>=7) & (train['hh_dropoff']<11)]\n",
        "Mtime.plot(kind='scatter',xlim=(long_min,long_max),ylim=(lat_min,lat_max),s=0.2,x='dropoff_longitude',y='dropoff_latitude',color='hotpink',subplots=True,ax=ax1)\n",
        "ax1.set_title('Dropoffs between 6AM - 11AM')\n",
        "# ax1.set_axis_bgcolor('black')\n",
        "pass\n",
        "\n",
        "#Shift 2 \n",
        "Atime=train[(train['hh_dropoff']>=11) & (train['hh_dropoff']<17)]\n",
        "Atime.plot(kind='scatter',xlim=(long_min,long_max),ylim=(lat_min,lat_max),s=0.2,x='dropoff_longitude',y='dropoff_latitude',color='hotpink',subplots=True,ax=ax2)\n",
        "ax2.set_title('Dropoffs between 11AM - 5PM')\n",
        "# ax2.set_axis_bgcolor('black')\n",
        "pass\n",
        "\n",
        "fig.tight_layout()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "d07bbb02334769f9ec2ecc2e0280b36013f65ba1",
        "_cell_guid": "74288c3a-084c-4f9e-bd02-bbacd49e882c",
        "id": "U5Ok35uekEva",
        "outputId": "8e95edff-5756-4e11-f328-9d347492f715",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 462
        }
      },
      "source": [
        "f, (ax1, ax2) = plt.subplots(1, 2, sharey=True,figsize=(10,7))\n",
        "\n",
        "#Shift 3\n",
        "Etime=train[(train['hh_dropoff']>=17) & (train['hh_dropoff']<23)]\n",
        "Etime.plot(kind='scatter',xlim=(long_min,long_max),ylim=(lat_min,lat_max),s=0.05,x='dropoff_longitude',y='dropoff_latitude',color='hotpink',subplots=True,ax=ax1)\n",
        "ax1.set_title('Dropoffs between 5PM to 11PM')\n",
        "# ax1.set_axis_bgcolor('black')\n",
        "pass\n",
        "\n",
        "#Shift 4 : Night Time - 0AM to 5AM\n",
        "Ntime=train[(train['hh_dropoff']>=0) & (train['hh_dropoff']<7)]\n",
        "Ntime.plot(kind='scatter',xlim=(long_min,long_max),ylim=(lat_min,lat_max),s=0.05,x='dropoff_longitude',y='dropoff_latitude',color='hotpink',subplots=True,ax=ax2)\n",
        "ax2.set_title('Dropoffs between 12AM to 5AM')\n",
        "# ax2.set_axis_bgcolor('black')\n",
        "pass"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "f55467481254c4d9d1ff0d4cd8de377c40e62a3a",
        "_cell_guid": "63208b7a-afd1-4db2-9039-d749d25f966e",
        "id": "VBNdd0T2kEvy"
      },
      "source": [
        "**Modification** "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "2277a5db2633361abb732068659feb197be628a8",
        "_cell_guid": "5fd49cd7-ab37-422d-a3e2-ab42f18fea10",
        "id": "r6SfoNVOkEvz"
      },
      "source": [
        "Creating **Seasons** -\n",
        "\n",
        "S1 = Month of January and February as they are the cold months\n",
        "S2=Month of March, April and May less cold \n",
        "S3=Month of June as a little warmer month"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "3f009d43b48172e58e07065bb1b0994689ee8a53",
        "_cell_guid": "9490aca6-11fb-454e-9ffe-7faeb0487791",
        "id": "h7Dt16WmkEv3"
      },
      "source": [
        "#For the train dataset\n",
        "train['s1']= train['mm_pickup']<=2\n",
        "train['s2']= train['mm_pickup'].between(3,5)\n",
        "train['s3']= train['mm_pickup']>=6\n",
        "\n",
        "#For the test dataset\n",
        "test['s1']= test['mm_pickup']<=2\n",
        "test['s2']= test['mm_pickup'].between(3,5)\n",
        "test['s3']= test['mm_pickup']>=6"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "42a22c9c92a740e272d97d30e56a1af21068421f",
        "_cell_guid": "66af45ae-9455-431a-a0e6-268c779d8cb8",
        "id": "nOzoGZ3mkEv7"
      },
      "source": [
        "**Model and Predict**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "0538c2fb9a6e7ecb5fe54427e76f2757913db3e0",
        "_cell_guid": "11014e62-a21b-4e11-8337-2da2728dede2",
        "id": "pGnk03KRkEv8"
      },
      "source": [
        "Importing **scikit-learn** packages"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "dff3cf1fd44868e058695bebd3b9d090cd0ec224",
        "_cell_guid": "176bf898-5f97-41f0-ad4f-e4a8ca52739c",
        "id": "XH0kDpQWkEv8"
      },
      "source": [
        "from sklearn import linear_model\n",
        "import statsmodels.api as sm\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn import metrics\n",
        "from sklearn.model_selection import cross_val_score\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "e2ce252090dc98289304e404e7079198bf77e7c9",
        "_cell_guid": "cf87f62e-314d-4aab-aaa9-7adbaee05858",
        "id": "CA3uE_bFkEwA",
        "outputId": "3b8f5c47-f80d-4a5f-c7d3-510ad2dcdf3e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(train.columns)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Index(['id', 'vendor_id', 'pickup_datetime', 'dropoff_datetime',\n",
            "       'passenger_count', 'pickup_longitude', 'pickup_latitude',\n",
            "       'dropoff_longitude', 'dropoff_latitude', 'store_and_fwd_flag',\n",
            "       'trip_duration', 'mm_pickup', 'mm_dropoff', 'dow_pickup', 'dow_dropoff',\n",
            "       'yday', 'hh_pickup', 'hh_dropoff', 'distance_km', 'log_distance',\n",
            "       'speed', 's1', 's2', 's3'],\n",
            "      dtype='object')\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "88ba78970c0b2327e540f3dec09c6bc0e45f5892",
        "_cell_guid": "b5245f71-678c-45fb-b33a-e6d04f58d580",
        "id": "SLEr9V7FkEwD",
        "outputId": "0f86b01e-674e-4f5f-9761-52c7f6ee908c",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(test.columns)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Index(['id', 'vendor_id', 'pickup_datetime', 'passenger_count',\n",
            "       'pickup_longitude', 'pickup_latitude', 'dropoff_longitude',\n",
            "       'dropoff_latitude', 'store_and_fwd_flag', 'mm_pickup', 'dow_pickup',\n",
            "       'yday', 'hh_pickup', 'distance_km', 's1', 's2', 's3'],\n",
            "      dtype='object')\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "7a54f46db843429a69e627d6d2fc3d6e77e9c6d8",
        "_cell_guid": "d42d50d4-d8ae-456d-898d-32f0dbf31446",
        "id": "sR2AK7uvkEwG"
      },
      "source": [
        "Checking significant variables through **ANOVA** table"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "d10985bc0a86b0d9645361f1fe553dd0f8a38264",
        "_cell_guid": "57eba512-f1d1-4fb0-a495-2f5925838274",
        "id": "mtow12MRkEwG",
        "outputId": "08c76ad4-2a60-4cb9-e1a8-32ff73a585d1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 682
        }
      },
      "source": [
        "x=train[['distance_km','pickup_longitude','passenger_count','vendor_id','pickup_latitude','yday','dropoff_longitude','dropoff_latitude','dow_pickup','hh_pickup','mm_pickup']]\n",
        "Y=train['trip_duration']\n",
        "x=sm.add_constant(x)\n",
        "model=sm.OLS(Y,x).fit()\n",
        "model.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<table class=\"simpletable\">\n",
              "<caption>OLS Regression Results</caption>\n",
              "<tr>\n",
              "  <th>Dep. Variable:</th>      <td>trip_duration</td>  <th>  R-squared:         </th>  <td>   0.555</td>  \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th>  <td>   0.555</td>  \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th>  <td>1.383e+05</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Date:</th>             <td>Thu, 15 Oct 2020</td> <th>  Prob (F-statistic):</th>   <td>  0.00</td>   \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Time:</th>                 <td>17:21:01</td>     <th>  Log-Likelihood:    </th> <td>-8.9888e+06</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>No. Observations:</th>      <td>1222114</td>     <th>  AIC:               </th>  <td>1.798e+07</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Df Residuals:</th>          <td>1222102</td>     <th>  BIC:               </th>  <td>1.798e+07</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Df Model:</th>              <td>    11</td>      <th>                     </th>      <td> </td>     \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>      <td> </td>     \n",
              "</tr>\n",
              "</table>\n",
              "<table class=\"simpletable\">\n",
              "<tr>\n",
              "          <td></td>             <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>const</th>             <td>-1.035e+05</td> <td> 1382.718</td> <td>  -74.858</td> <td> 0.000</td> <td>-1.06e+05</td> <td>-1.01e+05</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>distance_km</th>       <td>  106.3137</td> <td>    0.108</td> <td>  987.108</td> <td> 0.000</td> <td>  106.103</td> <td>  106.525</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>pickup_longitude</th>  <td> -538.3020</td> <td>   10.683</td> <td>  -50.390</td> <td> 0.000</td> <td> -559.240</td> <td> -517.364</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>passenger_count</th>   <td>    2.7237</td> <td>    0.272</td> <td>   10.032</td> <td> 0.000</td> <td>    2.192</td> <td>    3.256</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>vendor_id</th>         <td>   -0.8882</td> <td>    0.716</td> <td>   -1.241</td> <td> 0.215</td> <td>   -2.291</td> <td>    0.515</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>pickup_latitude</th>   <td> 1200.7563</td> <td>   13.971</td> <td>   85.949</td> <td> 0.000</td> <td> 1173.374</td> <td> 1228.138</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>yday</th>              <td>    0.0098</td> <td>    0.005</td> <td>    2.058</td> <td> 0.040</td> <td>    0.000</td> <td>    0.019</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>dropoff_longitude</th> <td> -794.6743</td> <td>   10.819</td> <td>  -73.452</td> <td> 0.000</td> <td> -815.879</td> <td> -773.470</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>dropoff_latitude</th>  <td>-1070.5333</td> <td>   11.816</td> <td>  -90.599</td> <td> 0.000</td> <td>-1093.692</td> <td>-1047.374</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>dow_pickup</th>        <td>  -12.1373</td> <td>    0.177</td> <td>  -68.465</td> <td> 0.000</td> <td>  -12.485</td> <td>  -11.790</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>hh_pickup</th>         <td>    3.7298</td> <td>    0.054</td> <td>   68.843</td> <td> 0.000</td> <td>    3.624</td> <td>    3.836</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>mm_pickup</th>         <td>   17.4253</td> <td>    0.234</td> <td>   74.358</td> <td> 0.000</td> <td>   16.966</td> <td>   17.885</td>\n",
              "</tr>\n",
              "</table>\n",
              "<table class=\"simpletable\">\n",
              "<tr>\n",
              "  <th>Omnibus:</th>       <td>331673.305</td> <th>  Durbin-Watson:     </th>  <td>   1.999</td>  \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Prob(Omnibus):</th>   <td> 0.000</td>   <th>  Jarque-Bera (JB):  </th> <td>1241328.891</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Skew:</th>            <td> 1.326</td>   <th>  Prob(JB):          </th>  <td>    0.00</td>  \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Kurtosis:</th>        <td> 7.164</td>   <th>  Cond. No.          </th>  <td>4.94e+05</td>  \n",
              "</tr>\n",
              "</table><br/><br/>Warnings:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.<br/>[2] The condition number is large, 4.94e+05. This might indicate that there are<br/>strong multicollinearity or other numerical problems."
            ],
            "text/plain": [
              "<class 'statsmodels.iolib.summary.Summary'>\n",
              "\"\"\"\n",
              "                            OLS Regression Results                            \n",
              "==============================================================================\n",
              "Dep. Variable:          trip_duration   R-squared:                       0.555\n",
              "Model:                            OLS   Adj. R-squared:                  0.555\n",
              "Method:                 Least Squares   F-statistic:                 1.383e+05\n",
              "Date:                Thu, 15 Oct 2020   Prob (F-statistic):               0.00\n",
              "Time:                        17:21:01   Log-Likelihood:            -8.9888e+06\n",
              "No. Observations:             1222114   AIC:                         1.798e+07\n",
              "Df Residuals:                 1222102   BIC:                         1.798e+07\n",
              "Df Model:                          11                                         \n",
              "Covariance Type:            nonrobust                                         \n",
              "=====================================================================================\n",
              "                        coef    std err          t      P>|t|      [0.025      0.975]\n",
              "-------------------------------------------------------------------------------------\n",
              "const             -1.035e+05   1382.718    -74.858      0.000   -1.06e+05   -1.01e+05\n",
              "distance_km         106.3137      0.108    987.108      0.000     106.103     106.525\n",
              "pickup_longitude   -538.3020     10.683    -50.390      0.000    -559.240    -517.364\n",
              "passenger_count       2.7237      0.272     10.032      0.000       2.192       3.256\n",
              "vendor_id            -0.8882      0.716     -1.241      0.215      -2.291       0.515\n",
              "pickup_latitude    1200.7563     13.971     85.949      0.000    1173.374    1228.138\n",
              "yday                  0.0098      0.005      2.058      0.040       0.000       0.019\n",
              "dropoff_longitude  -794.6743     10.819    -73.452      0.000    -815.879    -773.470\n",
              "dropoff_latitude  -1070.5333     11.816    -90.599      0.000   -1093.692   -1047.374\n",
              "dow_pickup          -12.1373      0.177    -68.465      0.000     -12.485     -11.790\n",
              "hh_pickup             3.7298      0.054     68.843      0.000       3.624       3.836\n",
              "mm_pickup            17.4253      0.234     74.358      0.000      16.966      17.885\n",
              "==============================================================================\n",
              "Omnibus:                   331673.305   Durbin-Watson:                   1.999\n",
              "Prob(Omnibus):                  0.000   Jarque-Bera (JB):          1241328.891\n",
              "Skew:                           1.326   Prob(JB):                         0.00\n",
              "Kurtosis:                       7.164   Cond. No.                     4.94e+05\n",
              "==============================================================================\n",
              "\n",
              "Warnings:\n",
              "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
              "[2] The condition number is large, 4.94e+05. This might indicate that there are\n",
              "strong multicollinearity or other numerical problems.\n",
              "\"\"\""
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "_uuid": "852c879ba282b7e490b645f88556710d49c33f9d",
        "_cell_guid": "4fd72e10-5db4-4675-87e0-81e23f5239c0",
        "id": "LgfxQeU9kEwJ"
      },
      "source": [
        "We won't be including those variables whose p-values are greater than 0.5 as they are not statistically significant or in other terms they aren't capable of making an impact on dependent variable."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "0dd2b6bdfe96e020ef53ae55e664dd760996817c",
        "_cell_guid": "31d927eb-84c7-499f-9e3d-47674fdee75c",
        "id": "L5LOLygfkEwK"
      },
      "source": [
        "features=['distance_km','pickup_longitude','pickup_latitude','yday','dropoff_longitude','dropoff_latitude','dow_pickup','hh_pickup'] \n",
        "X_train=train[features]\n",
        "y_train=train['trip_duration']\n",
        "feature_cols=['distance_km','pickup_longitude','pickup_latitude','yday','dropoff_longitude','dropoff_latitude','dow_pickup','hh_pickup'] \n",
        "X_test=test[feature_cols]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hc3KevJ_XTeh"
      },
      "source": [
        "# Task: Feature Scaling"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_iOkb88BXW1t"
      },
      "source": [
        "While the feature selection for the model has been done. There's one step remaining which is feature scaling. In order to overcome the issue of large MSE values we need to normalize the values in each column. Refer to [this](https://sebastianraschka.com/Articles/2014_about_feature_scaling.html) article to learn more about feature scaling. \n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "4f61797c2571ade27d90200b01e1562de747c692",
        "_cell_guid": "d76207a0-f3c7-4455-a5e0-03484aef9189",
        "id": "OQ6YGNckkEwO"
      },
      "source": [
        "X_Train,X_test,Y_train,Y_test=train_test_split(X_train,y_train,test_size=0.2,random_state=42)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "_uuid": "cb49f5aaaf613737f6123586f0a45a2d88774bff",
        "_cell_guid": "3253a14c-2662-4617-9491-d82a998cf65b",
        "id": "j35G7UPRkEwY",
        "outputId": "d149e27e-3abc-43ce-ab14-66bda34b9a6d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "linreg = LinearRegression()\n",
        "linreg.fit(X_train, y_train)\n",
        "scores = cross_val_score(linreg, X_train, y_train, cv=10, scoring='neg_mean_squared_error')\n",
        "print (scores)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[-145478.92872301 -145228.16680895 -143652.78338549 -144041.09685527\n",
            " -143860.94406364 -141470.92308561 -143413.44716107 -143730.93566008\n",
            " -142939.72184606 -145287.10239242]\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}