yearly_running_stats_from_strava_file.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing data from the csv file downloaded from strava"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "        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>Activity ID</th>\n",
       "      <th>Activity Date</th>\n",
       "      <th>Activity Name</th>\n",
       "      <th>Activity Type</th>\n",
       "      <th>Activity Description</th>\n",
       "      <th>Elapsed Time</th>\n",
       "      <th>Distance</th>\n",
       "      <th>Max Heart Rate</th>\n",
       "      <th>Relative Effort</th>\n",
       "      <th>Commute</th>\n",
       "      <th>...</th>\n",
       "      <th>UV Index</th>\n",
       "      <th>Weather Ozone</th>\n",
       "      <th>&lt;span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.jump_count\"&gt;Jump Count&lt;/span&gt;</th>\n",
       "      <th>&lt;span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.total_grit\"&gt;Total Grit&lt;/span&gt;</th>\n",
       "      <th>&lt;span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.avg_flow\"&gt;Avg Flow&lt;/span&gt;</th>\n",
       "      <th>&lt;span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.flagged\"&gt;Flagged&lt;/span&gt;</th>\n",
       "      <th>&lt;span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.avg_elapsed_speed\"&gt;Avg Elapsed Speed&lt;/span&gt;</th>\n",
       "      <th>&lt;span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.dirt_distance\"&gt;Dirt Distance&lt;/span&gt;</th>\n",
       "      <th>&lt;span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.newly_explored_distance\"&gt;Newly Explored Distance&lt;/span&gt;</th>\n",
       "      <th>&lt;span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.newly_explored_dirt_distance\"&gt;Newly Explored Dirt Distance&lt;/span&gt;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2054158879</td>\n",
       "      <td>Jan 4, 2019, 3:32:42 AM</td>\n",
       "      <td>Morning Run</td>\n",
       "      <td>Run</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2079</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2058715900</td>\n",
       "      <td>Jan 6, 2019, 4:26:21 AM</td>\n",
       "      <td>Morning Ride</td>\n",
       "      <td>Ride</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5848</td>\n",
       "      <td>25.63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2063418848</td>\n",
       "      <td>Jan 8, 2019, 3:45:17 AM</td>\n",
       "      <td>Morning Run</td>\n",
       "      <td>Run</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1896</td>\n",
       "      <td>4.02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 83 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Activity ID            Activity Date Activity Name Activity Type  \\\n",
       "0   2054158879  Jan 4, 2019, 3:32:42 AM   Morning Run           Run   \n",
       "1   2058715900  Jan 6, 2019, 4:26:21 AM  Morning Ride          Ride   \n",
       "2   2063418848  Jan 8, 2019, 3:45:17 AM   Morning Run           Run   \n",
       "\n",
       "  Activity Description  Elapsed Time  Distance  Max Heart Rate  \\\n",
       "0                  NaN          2079      5.00             NaN   \n",
       "1                  NaN          5848     25.63             NaN   \n",
       "2                  NaN          1896      4.02             NaN   \n",
       "\n",
       "   Relative Effort  Commute  ...  UV Index Weather Ozone  \\\n",
       "0              NaN    False  ...       NaN           NaN   \n",
       "1              NaN    False  ...       NaN           NaN   \n",
       "2              NaN    False  ...       NaN           NaN   \n",
       "\n",
       "   <span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.jump_count\">Jump Count</span>  \\\n",
       "0                                                NaN                                                                                                            \n",
       "1                                                NaN                                                                                                            \n",
       "2                                                NaN                                                                                                            \n",
       "\n",
       "   <span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.total_grit\">Total Grit</span>  \\\n",
       "0                                                NaN                                                                                                            \n",
       "1                                                NaN                                                                                                            \n",
       "2                                                NaN                                                                                                            \n",
       "\n",
       "   <span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.avg_flow\">Avg Flow</span>  \\\n",
       "0                                                NaN                                                                                                        \n",
       "1                                                NaN                                                                                                        \n",
       "2                                                NaN                                                                                                        \n",
       "\n",
       "   <span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.flagged\">Flagged</span>  \\\n",
       "0                                                NaN                                                                                                      \n",
       "1                                                NaN                                                                                                      \n",
       "2                                                NaN                                                                                                      \n",
       "\n",
       "   <span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.avg_elapsed_speed\">Avg Elapsed Speed</span>  \\\n",
       "0                                                NaN                                                                                                                          \n",
       "1                                                NaN                                                                                                                          \n",
       "2                                                NaN                                                                                                                          \n",
       "\n",
       "   <span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.dirt_distance\">Dirt Distance</span>  \\\n",
       "0                                                NaN                                                                                                                  \n",
       "1                                                NaN                                                                                                                  \n",
       "2                                                NaN                                                                                                                  \n",
       "\n",
       "   <span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.newly_explored_distance\">Newly Explored Distance</span>  \\\n",
       "0                                                NaN                                                                                                                                      \n",
       "1                                                NaN                                                                                                                                      \n",
       "2                                                NaN                                                                                                                                      \n",
       "\n",
       "   <span class=\"translation_missing\" title=\"translation missing: en-US.lib.export.portability_exporter.activities.horton_values.newly_explored_dirt_distance\">Newly Explored Dirt Distance</span>  \n",
       "0                                                NaN                                                                                                                                               \n",
       "1                                                NaN                                                                                                                                               \n",
       "2                                                NaN                                                                                                                                               \n",
       "\n",
       "[3 rows x 83 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "path = '/Users/sapnasharma/Downloads/export_37140684/activities.csv'\n",
    "df = pd.read_csv(path)\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Renaming the columns and converting Activity_Date to datetime object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Activity_Date</th>\n",
       "      <th>Distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-04 03:32:42</td>\n",
       "      <td>5.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-06 04:26:21</td>\n",
       "      <td>25.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-08 03:45:17</td>\n",
       "      <td>4.02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Activity_Date  Distance\n",
       "0 2019-01-04 03:32:42      5.00\n",
       "1 2019-01-06 04:26:21     25.63\n",
       "2 2019-01-08 03:45:17      4.02"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.rename(columns = {\"Activity Date\":\"Activity_Date\",'Activity Name':'Activity_Name','Activity Type':'Activity_Type','Elapsed Time':'Duration'},inplace = True)\n",
    "df = df[['Activity_Date', 'Distance']]\n",
    "# converting to date\n",
    "df['Activity_Date'] = pd.to_datetime(df['Activity_Date'])\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting the data for the year 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Activity_Date</th>\n",
       "      <th>Distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>326</th>\n",
       "      <td>2021-01-10 00:44:02</td>\n",
       "      <td>10.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>327</th>\n",
       "      <td>2021-01-21 16:50:31</td>\n",
       "      <td>10.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>2021-01-25 00:24:45</td>\n",
       "      <td>6.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>329</th>\n",
       "      <td>2021-01-26 00:44:04</td>\n",
       "      <td>7.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330</th>\n",
       "      <td>2021-01-27 02:08:50</td>\n",
       "      <td>3.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464</th>\n",
       "      <td>2021-12-23 21:24:29</td>\n",
       "      <td>4.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>465</th>\n",
       "      <td>2021-12-27 21:24:29</td>\n",
       "      <td>4.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>466</th>\n",
       "      <td>2021-12-28 21:24:29</td>\n",
       "      <td>6.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>467</th>\n",
       "      <td>2021-12-29 21:24:29</td>\n",
       "      <td>8.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>468</th>\n",
       "      <td>2021-12-31 21:24:29</td>\n",
       "      <td>5.48</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>143 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Activity_Date  Distance\n",
       "326 2021-01-10 00:44:02     10.10\n",
       "327 2021-01-21 16:50:31     10.10\n",
       "328 2021-01-25 00:24:45      6.45\n",
       "329 2021-01-26 00:44:04      7.15\n",
       "330 2021-01-27 02:08:50      3.38\n",
       "..                  ...       ...\n",
       "464 2021-12-23 21:24:29      4.57\n",
       "465 2021-12-27 21:24:29      4.66\n",
       "466 2021-12-28 21:24:29      6.73\n",
       "467 2021-12-29 21:24:29      8.81\n",
       "468 2021-12-31 21:24:29      5.48\n",
       "\n",
       "[143 rows x 2 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[df['Activity_Date'].dt.year == 2021]\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Converting the Activity_Date to date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Activity_Date</th>\n",
       "      <th>Distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>326</th>\n",
       "      <td>2021-01-10</td>\n",
       "      <td>10.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>327</th>\n",
       "      <td>2021-01-21</td>\n",
       "      <td>10.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>2021-01-25</td>\n",
       "      <td>6.45</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Activity_Date  Distance\n",
       "326    2021-01-10     10.10\n",
       "327    2021-01-21     10.10\n",
       "328    2021-01-25      6.45"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Activity_Date'] = pd.to_datetime(df['Activity_Date']).dt.date\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Grouping by date to sum all the activities done in day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
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       "      <th></th>\n",
       "      <th>Activity_Date</th>\n",
       "      <th>Distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-01-10</td>\n",
       "      <td>10.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-01-21</td>\n",
       "      <td>10.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-01-25</td>\n",
       "      <td>6.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-01-26</td>\n",
       "      <td>7.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-01-27</td>\n",
       "      <td>3.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>2021-12-23</td>\n",
       "      <td>4.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>2021-12-27</td>\n",
       "      <td>4.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>2021-12-28</td>\n",
       "      <td>6.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>2021-12-29</td>\n",
       "      <td>8.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>2021-12-31</td>\n",
       "      <td>5.48</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>125 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Activity_Date  Distance\n",
       "0      2021-01-10     10.10\n",
       "1      2021-01-21     10.10\n",
       "2      2021-01-25      6.45\n",
       "3      2021-01-26      7.15\n",
       "4      2021-01-27      3.38\n",
       "..            ...       ...\n",
       "120    2021-12-23      4.57\n",
       "121    2021-12-27      4.66\n",
       "122    2021-12-28      6.73\n",
       "123    2021-12-29      8.81\n",
       "124    2021-12-31      5.48\n",
       "\n",
       "[125 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = df.groupby(['Activity_Date'],as_index = False).sum(['Distance'])\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 143 entries, 326 to 468\n",
      "Data columns (total 2 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Activity_Date  143 non-null    object \n",
      " 1   Distance       143 non-null    float64\n",
      "dtypes: float64(1), object(1)\n",
      "memory usage: 3.4+ KB\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 125 entries, 0 to 124\n",
      "Data columns (total 2 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Activity_Date  125 non-null    object \n",
      " 1   Distance       125 non-null    float64\n",
      "dtypes: float64(1), object(1)\n",
      "memory usage: 2.9+ KB\n",
      "None None\n"
     ]
    }
   ],
   "source": [
    "print(df.info(),df1.info())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating a dataframe with all the dates in the year 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "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>Activity_Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-01-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-01-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-01-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>360</th>\n",
       "      <td>2021-12-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>2021-12-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>2021-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>2021-12-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>2021-12-31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>365 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Activity_Date\n",
       "0      2021-01-01\n",
       "1      2021-01-02\n",
       "2      2021-01-03\n",
       "3      2021-01-04\n",
       "4      2021-01-05\n",
       "..            ...\n",
       "360    2021-12-27\n",
       "361    2021-12-28\n",
       "362    2021-12-29\n",
       "363    2021-12-30\n",
       "364    2021-12-31\n",
       "\n",
       "[365 rows x 1 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "from datetime import datetime, timedelta\n",
    "\n",
    "def date_range(start, end):\n",
    "    delta = end - start  # as timedelta\n",
    "    days = [start + timedelta(days=i) for i in range(delta.days + 1)]\n",
    "    return days\n",
    "\n",
    "start_date = datetime(2021, 1, 1)\n",
    "end_date = datetime(2021, 12, 31)\n",
    "    \n",
    "complete_year = pd.DataFrame(date_range(start_date, end_date))\n",
    "complete_year.rename(columns = {0:'Activity_Date'},inplace =True)\n",
    "complete_year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "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>Activity_Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-01-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-01-03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Activity_Date\n",
       "0    2021-01-01\n",
       "1    2021-01-02\n",
       "2    2021-01-03"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "complete_year['Activity_Date'] = pd.to_datetime(complete_year['Activity_Date']).dt.date\n",
    "complete_year.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 365 entries, 0 to 364\n",
      "Data columns (total 1 columns):\n",
      " #   Column         Non-Null Count  Dtype \n",
      "---  ------         --------------  ----- \n",
      " 0   Activity_Date  365 non-null    object\n",
      "dtypes: object(1)\n",
      "memory usage: 3.0+ KB\n"
     ]
    }
   ],
   "source": [
    "complete_year.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Joining the activity file with the all dates dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "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>Activity_Date</th>\n",
       "      <th>Distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-01-02</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-01-03</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-01-04</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-01-05</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2021-01-06</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021-01-07</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021-01-08</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2021-01-09</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021-01-10</td>\n",
       "      <td>10.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2021-01-11</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Activity_Date  Distance\n",
       "0     2021-01-01       NaN\n",
       "1     2021-01-02       NaN\n",
       "2     2021-01-03       NaN\n",
       "3     2021-01-04       NaN\n",
       "4     2021-01-05       NaN\n",
       "5     2021-01-06       NaN\n",
       "6     2021-01-07       NaN\n",
       "7     2021-01-08       NaN\n",
       "8     2021-01-09       NaN\n",
       "9     2021-01-10      10.1\n",
       "10    2021-01-11       NaN"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df = complete_year.merge(df1, on='Activity_Date', how='left')\n",
    "merged_df.head(11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_df.to_csv('stats.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### We will use turtle do draw the graphics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import turtle\n",
    "import pandas as pd\n",
    "from datetime import datetime\n",
    "import calendar\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = merged_df.copy()\n",
    "df['dt'] = pd.to_datetime(df['Activity_Date'])\n",
    "my_window = turtle.Screen()\n",
    "my_window. bgcolor(\"black\")\n",
    "tur = turtle.Turtle()\n",
    "n=52 # total weeks in a year\n",
    "k = 0\n",
    "tur.speed(800)\n",
    "tur.hideturtle() # we do not want to display the turtle icon\n",
    "tur.width(0.01)\n",
    "\n",
    "for i in range(n):\n",
    "    tur.pencolor('grey')\n",
    "    for j in range(7):                           # for each week\n",
    "\n",
    "        tur.forward(30)\n",
    "        if (df.Distance[k]) > 0:\n",
    "            tur.dot(df.Distance[k],'cyan')       # when an activity is observed\n",
    "        else:\n",
    "            tur.dot(2,'red')                     # when no activity is performed\n",
    "        k+=1\n",
    "    tur.penup()\n",
    "    tur.forward(40)\n",
    "    tur.pencolor('cyan')\n",
    "    s = calendar.month_name[df.dt[k].month][0:3] # Extracing first three alphabets of the month\n",
    "    tur.pendown()\n",
    "    tur.write(s,font = (\"Calibri\",8,\"bold\"))     # prints the month around the perifery\n",
    "    tur.penup()\n",
    "    tur.backward(250)\n",
    "    tur.pendown()\n",
    "    tur.left(360/n)                              # setting the angle to accomodate 52 weeks, n= 52\n",
    "tur.penup()\n",
    "active_days = df[df.Distance >0]['Distance'].count()\n",
    "tur.setpos(-250,300)\n",
    "tur.pendown()\n",
    "tur.pencolor('cyan')\n",
    "tur.write(\"Active Days : \"+ str(active_days),font=(\"Calibri\", 20, \"bold\")) # title display of active days\n",
    "tur.penup()\n",
    "tur.setpos(-250,270)\n",
    "tur.pendown()\n",
    "tur.pencolor('cyan')\n",
    "tur.write(\"Total Distance : \"+ str(int(df.Distance.sum()))+\" Kms\",font=(\"Calibri\", 20, \"bold\")) # title display of total distance\n",
    "tur.penup()\n",
    "\n",
    "tur.setpos(-250,-300)\n",
    "tur.pendown()\n",
    "tur.pencolor('cyan')\n",
    "tur.write(\"My Walk / Run / Bike /Hike Highlights of 2021\",font=(\"Calibri\", 20, \"bold\")) # title display of total distance\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "turtle.done()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](https://github.com/sharmasapna/fun_projects/blob/main/data/my_stats.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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