Demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Wrangling/Cleaning contest demo code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## In this contest, I cleaned up a huge csv file with 10 million rows of data\n",
    "### Author: Yuan Gao (Rabona)\n",
    "### Date: March 5th, 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from utils.misc_utils import *\n",
    "from utils.Monthly_implementation import CleanerMonthly\n",
    "from utils.RelationExplorer import RelationExplorer\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>wsid</th>\n",
       "      <th>wsnm</th>\n",
       "      <th>elvt</th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>inme</th>\n",
       "      <th>city</th>\n",
       "      <th>prov</th>\n",
       "      <th>mdct</th>\n",
       "      <th>date</th>\n",
       "      <th>...</th>\n",
       "      <th>tmax</th>\n",
       "      <th>dmax</th>\n",
       "      <th>tmin</th>\n",
       "      <th>dmin</th>\n",
       "      <th>hmdy</th>\n",
       "      <th>hmax</th>\n",
       "      <th>hmin</th>\n",
       "      <th>wdsp</th>\n",
       "      <th>wdct</th>\n",
       "      <th>gust</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 00:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>29.7</td>\n",
       "      <td>16.8</td>\n",
       "      <td>25.5</td>\n",
       "      <td>10.8</td>\n",
       "      <td>35.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>101.0</td>\n",
       "      <td>6.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 01:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>29.9</td>\n",
       "      <td>13.6</td>\n",
       "      <td>29.0</td>\n",
       "      <td>12.2</td>\n",
       "      <td>39.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>94.0</td>\n",
       "      <td>6.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 02:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>29.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>27.4</td>\n",
       "      <td>13.6</td>\n",
       "      <td>44.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>93.0</td>\n",
       "      <td>6.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 03:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>27.4</td>\n",
       "      <td>16.9</td>\n",
       "      <td>25.8</td>\n",
       "      <td>14.1</td>\n",
       "      <td>58.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>96.0</td>\n",
       "      <td>5.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 04:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>26.3</td>\n",
       "      <td>17.0</td>\n",
       "      <td>25.3</td>\n",
       "      <td>16.4</td>\n",
       "      <td>57.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>110.0</td>\n",
       "      <td>7.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 05:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>25.4</td>\n",
       "      <td>16.4</td>\n",
       "      <td>23.8</td>\n",
       "      <td>16.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>6.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 06:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>23.8</td>\n",
       "      <td>16.7</td>\n",
       "      <td>22.0</td>\n",
       "      <td>16.2</td>\n",
       "      <td>72.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>93.0</td>\n",
       "      <td>4.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 07:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>22.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>19.5</td>\n",
       "      <td>16.6</td>\n",
       "      <td>86.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>157.0</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 08:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>19.7</td>\n",
       "      <td>17.3</td>\n",
       "      <td>18.3</td>\n",
       "      <td>16.9</td>\n",
       "      <td>93.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 09:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>22.9</td>\n",
       "      <td>18.3</td>\n",
       "      <td>18.2</td>\n",
       "      <td>17.1</td>\n",
       "      <td>75.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>248.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 10:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>25.1</td>\n",
       "      <td>18.4</td>\n",
       "      <td>22.9</td>\n",
       "      <td>17.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>97.0</td>\n",
       "      <td>6.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 11:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 12:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 13:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 14:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>31.8</td>\n",
       "      <td>16.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>14.3</td>\n",
       "      <td>36.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>97.0</td>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 15:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>33.0</td>\n",
       "      <td>15.4</td>\n",
       "      <td>31.0</td>\n",
       "      <td>13.6</td>\n",
       "      <td>32.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>103.0</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 16:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>34.0</td>\n",
       "      <td>15.6</td>\n",
       "      <td>32.5</td>\n",
       "      <td>12.9</td>\n",
       "      <td>31.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>78.0</td>\n",
       "      <td>9.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 17:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>34.7</td>\n",
       "      <td>14.6</td>\n",
       "      <td>33.4</td>\n",
       "      <td>12.2</td>\n",
       "      <td>29.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>102.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 18:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>35.2</td>\n",
       "      <td>14.2</td>\n",
       "      <td>33.9</td>\n",
       "      <td>12.6</td>\n",
       "      <td>27.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>94.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 19:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>35.1</td>\n",
       "      <td>14.5</td>\n",
       "      <td>33.7</td>\n",
       "      <td>12.6</td>\n",
       "      <td>28.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>93.0</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 20:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>34.7</td>\n",
       "      <td>14.5</td>\n",
       "      <td>32.2</td>\n",
       "      <td>12.8</td>\n",
       "      <td>30.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>106.0</td>\n",
       "      <td>5.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 21:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>32.7</td>\n",
       "      <td>15.8</td>\n",
       "      <td>29.9</td>\n",
       "      <td>12.5</td>\n",
       "      <td>40.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>102.0</td>\n",
       "      <td>5.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 22:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>31.7</td>\n",
       "      <td>15.4</td>\n",
       "      <td>29.4</td>\n",
       "      <td>11.3</td>\n",
       "      <td>29.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>123.0</td>\n",
       "      <td>4.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-06 23:00:00</td>\n",
       "      <td>2007-11-06</td>\n",
       "      <td>...</td>\n",
       "      <td>31.5</td>\n",
       "      <td>13.3</td>\n",
       "      <td>29.8</td>\n",
       "      <td>11.4</td>\n",
       "      <td>35.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>112.0</td>\n",
       "      <td>7.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-07 00:00:00</td>\n",
       "      <td>2007-11-07</td>\n",
       "      <td>...</td>\n",
       "      <td>31.0</td>\n",
       "      <td>15.1</td>\n",
       "      <td>30.2</td>\n",
       "      <td>13.4</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>109.0</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-07 01:00:00</td>\n",
       "      <td>2007-11-07</td>\n",
       "      <td>...</td>\n",
       "      <td>30.3</td>\n",
       "      <td>15.1</td>\n",
       "      <td>29.3</td>\n",
       "      <td>13.1</td>\n",
       "      <td>37.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>109.0</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-07 02:00:00</td>\n",
       "      <td>2007-11-07</td>\n",
       "      <td>...</td>\n",
       "      <td>29.3</td>\n",
       "      <td>14.0</td>\n",
       "      <td>28.1</td>\n",
       "      <td>13.1</td>\n",
       "      <td>42.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>120.0</td>\n",
       "      <td>11.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-07 03:00:00</td>\n",
       "      <td>2007-11-07</td>\n",
       "      <td>...</td>\n",
       "      <td>28.1</td>\n",
       "      <td>15.5</td>\n",
       "      <td>26.5</td>\n",
       "      <td>14.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>11.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-07 04:00:00</td>\n",
       "      <td>2007-11-07</td>\n",
       "      <td>...</td>\n",
       "      <td>26.6</td>\n",
       "      <td>16.4</td>\n",
       "      <td>25.1</td>\n",
       "      <td>15.5</td>\n",
       "      <td>58.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>178</td>\n",
       "      <td>SÃO GONÇALO</td>\n",
       "      <td>237.0</td>\n",
       "      <td>-6.835777</td>\n",
       "      <td>-38.311583</td>\n",
       "      <td>A333</td>\n",
       "      <td>São Gonçalo</td>\n",
       "      <td>RJ</td>\n",
       "      <td>2007-11-07 05:00:00</td>\n",
       "      <td>2007-11-07</td>\n",
       "      <td>...</td>\n",
       "      <td>25.2</td>\n",
       "      <td>16.4</td>\n",
       "      <td>23.7</td>\n",
       "      <td>15.3</td>\n",
       "      <td>59.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>111.0</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779138</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-29 18:00:00</td>\n",
       "      <td>2016-09-29</td>\n",
       "      <td>...</td>\n",
       "      <td>24.6</td>\n",
       "      <td>13.0</td>\n",
       "      <td>21.7</td>\n",
       "      <td>11.6</td>\n",
       "      <td>53.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779139</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-29 19:00:00</td>\n",
       "      <td>2016-09-29</td>\n",
       "      <td>...</td>\n",
       "      <td>22.1</td>\n",
       "      <td>12.9</td>\n",
       "      <td>20.0</td>\n",
       "      <td>11.7</td>\n",
       "      <td>61.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779140</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-29 20:00:00</td>\n",
       "      <td>2016-09-29</td>\n",
       "      <td>...</td>\n",
       "      <td>20.2</td>\n",
       "      <td>12.6</td>\n",
       "      <td>16.8</td>\n",
       "      <td>11.7</td>\n",
       "      <td>72.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779141</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-29 21:00:00</td>\n",
       "      <td>2016-09-29</td>\n",
       "      <td>...</td>\n",
       "      <td>16.9</td>\n",
       "      <td>12.1</td>\n",
       "      <td>15.3</td>\n",
       "      <td>11.5</td>\n",
       "      <td>79.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779142</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-29 22:00:00</td>\n",
       "      <td>2016-09-29</td>\n",
       "      <td>...</td>\n",
       "      <td>15.3</td>\n",
       "      <td>12.4</td>\n",
       "      <td>14.2</td>\n",
       "      <td>11.6</td>\n",
       "      <td>84.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779143</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-29 23:00:00</td>\n",
       "      <td>2016-09-29</td>\n",
       "      <td>...</td>\n",
       "      <td>14.7</td>\n",
       "      <td>11.8</td>\n",
       "      <td>14.2</td>\n",
       "      <td>10.2</td>\n",
       "      <td>75.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779144</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 00:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>14.9</td>\n",
       "      <td>11.4</td>\n",
       "      <td>14.5</td>\n",
       "      <td>10.3</td>\n",
       "      <td>81.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779145</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 01:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>14.8</td>\n",
       "      <td>11.4</td>\n",
       "      <td>14.2</td>\n",
       "      <td>9.9</td>\n",
       "      <td>75.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779146</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 02:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>14.7</td>\n",
       "      <td>10.2</td>\n",
       "      <td>14.3</td>\n",
       "      <td>9.2</td>\n",
       "      <td>73.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779147</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 03:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>14.8</td>\n",
       "      <td>11.4</td>\n",
       "      <td>14.3</td>\n",
       "      <td>9.6</td>\n",
       "      <td>80.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779148</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 04:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>14.9</td>\n",
       "      <td>12.3</td>\n",
       "      <td>14.7</td>\n",
       "      <td>11.3</td>\n",
       "      <td>84.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779149</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 05:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>14.9</td>\n",
       "      <td>12.2</td>\n",
       "      <td>14.8</td>\n",
       "      <td>10.9</td>\n",
       "      <td>77.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779150</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 06:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>14.9</td>\n",
       "      <td>11.6</td>\n",
       "      <td>14.6</td>\n",
       "      <td>10.9</td>\n",
       "      <td>81.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779151</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 07:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>14.8</td>\n",
       "      <td>11.8</td>\n",
       "      <td>14.5</td>\n",
       "      <td>11.4</td>\n",
       "      <td>81.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779152</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 08:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>14.9</td>\n",
       "      <td>11.8</td>\n",
       "      <td>14.6</td>\n",
       "      <td>11.3</td>\n",
       "      <td>80.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779153</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 09:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>14.9</td>\n",
       "      <td>11.7</td>\n",
       "      <td>14.2</td>\n",
       "      <td>11.3</td>\n",
       "      <td>82.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779154</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 10:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>15.8</td>\n",
       "      <td>11.4</td>\n",
       "      <td>14.3</td>\n",
       "      <td>11.1</td>\n",
       "      <td>74.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779155</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 11:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>17.7</td>\n",
       "      <td>12.0</td>\n",
       "      <td>15.6</td>\n",
       "      <td>11.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779156</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 12:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>19.3</td>\n",
       "      <td>12.0</td>\n",
       "      <td>17.1</td>\n",
       "      <td>10.6</td>\n",
       "      <td>60.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779157</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 13:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>20.5</td>\n",
       "      <td>12.2</td>\n",
       "      <td>18.2</td>\n",
       "      <td>10.6</td>\n",
       "      <td>58.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779158</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 14:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>21.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>19.4</td>\n",
       "      <td>9.8</td>\n",
       "      <td>55.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779159</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 15:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>21.8</td>\n",
       "      <td>12.1</td>\n",
       "      <td>19.9</td>\n",
       "      <td>10.6</td>\n",
       "      <td>54.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779160</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 16:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>21.4</td>\n",
       "      <td>12.8</td>\n",
       "      <td>20.2</td>\n",
       "      <td>11.5</td>\n",
       "      <td>59.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779161</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 17:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>21.2</td>\n",
       "      <td>12.8</td>\n",
       "      <td>19.3</td>\n",
       "      <td>11.5</td>\n",
       "      <td>64.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779162</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 18:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>19.5</td>\n",
       "      <td>12.8</td>\n",
       "      <td>18.0</td>\n",
       "      <td>11.8</td>\n",
       "      <td>67.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779163</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 19:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>18.2</td>\n",
       "      <td>12.4</td>\n",
       "      <td>16.3</td>\n",
       "      <td>11.8</td>\n",
       "      <td>76.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779164</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 20:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>16.8</td>\n",
       "      <td>12.5</td>\n",
       "      <td>15.3</td>\n",
       "      <td>11.7</td>\n",
       "      <td>80.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779165</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 21:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>15.3</td>\n",
       "      <td>11.9</td>\n",
       "      <td>14.9</td>\n",
       "      <td>11.5</td>\n",
       "      <td>79.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779166</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 22:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>15.0</td>\n",
       "      <td>11.7</td>\n",
       "      <td>14.4</td>\n",
       "      <td>11.4</td>\n",
       "      <td>82.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9779167</th>\n",
       "      <td>423</td>\n",
       "      <td>BARUERI</td>\n",
       "      <td>777.0</td>\n",
       "      <td>-23.523890</td>\n",
       "      <td>-46.869450</td>\n",
       "      <td>A755</td>\n",
       "      <td>Barueri</td>\n",
       "      <td>SP</td>\n",
       "      <td>2016-09-30 23:00:00</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>...</td>\n",
       "      <td>14.6</td>\n",
       "      <td>11.5</td>\n",
       "      <td>14.3</td>\n",
       "      <td>11.2</td>\n",
       "      <td>82.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9779168 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         wsid         wsnm   elvt        lat        lon  inme         city  \\\n",
       "0         178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "1         178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "2         178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "3         178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "4         178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "5         178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "6         178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "7         178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "8         178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "9         178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "10        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "11        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "12        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "13        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "14        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "15        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "16        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "17        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "18        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "19        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "20        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "21        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "22        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "23        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "24        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "25        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "26        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "27        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "28        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "29        178  SÃO GONÇALO  237.0  -6.835777 -38.311583  A333  São Gonçalo   \n",
       "...       ...          ...    ...        ...        ...   ...          ...   \n",
       "9779138   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779139   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779140   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779141   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779142   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779143   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779144   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779145   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779146   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779147   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779148   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779149   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779150   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779151   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779152   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779153   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779154   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779155   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779156   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779157   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779158   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779159   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779160   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779161   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779162   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779163   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779164   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779165   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779166   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "9779167   423      BARUERI  777.0 -23.523890 -46.869450  A755      Barueri   \n",
       "\n",
       "        prov                 mdct        date  ...   tmax  dmax  tmin  dmin  \\\n",
       "0         RJ  2007-11-06 00:00:00  2007-11-06  ...   29.7  16.8  25.5  10.8   \n",
       "1         RJ  2007-11-06 01:00:00  2007-11-06  ...   29.9  13.6  29.0  12.2   \n",
       "2         RJ  2007-11-06 02:00:00  2007-11-06  ...   29.0  14.0  27.4  13.6   \n",
       "3         RJ  2007-11-06 03:00:00  2007-11-06  ...   27.4  16.9  25.8  14.1   \n",
       "4         RJ  2007-11-06 04:00:00  2007-11-06  ...   26.3  17.0  25.3  16.4   \n",
       "5         RJ  2007-11-06 05:00:00  2007-11-06  ...   25.4  16.4  23.8  16.0   \n",
       "6         RJ  2007-11-06 06:00:00  2007-11-06  ...   23.8  16.7  22.0  16.2   \n",
       "7         RJ  2007-11-06 07:00:00  2007-11-06  ...   22.0  17.8  19.5  16.6   \n",
       "8         RJ  2007-11-06 08:00:00  2007-11-06  ...   19.7  17.3  18.3  16.9   \n",
       "9         RJ  2007-11-06 09:00:00  2007-11-06  ...   22.9  18.3  18.2  17.1   \n",
       "10        RJ  2007-11-06 10:00:00  2007-11-06  ...   25.1  18.4  22.9  17.0   \n",
       "11        RJ  2007-11-06 11:00:00  2007-11-06  ...    0.0   0.0   0.0   0.0   \n",
       "12        RJ  2007-11-06 12:00:00  2007-11-06  ...    0.0   0.0   0.0   0.0   \n",
       "13        RJ  2007-11-06 13:00:00  2007-11-06  ...    0.0   0.0   0.0   0.0   \n",
       "14        RJ  2007-11-06 14:00:00  2007-11-06  ...   31.8  16.0  30.0  14.3   \n",
       "15        RJ  2007-11-06 15:00:00  2007-11-06  ...   33.0  15.4  31.0  13.6   \n",
       "16        RJ  2007-11-06 16:00:00  2007-11-06  ...   34.0  15.6  32.5  12.9   \n",
       "17        RJ  2007-11-06 17:00:00  2007-11-06  ...   34.7  14.6  33.4  12.2   \n",
       "18        RJ  2007-11-06 18:00:00  2007-11-06  ...   35.2  14.2  33.9  12.6   \n",
       "19        RJ  2007-11-06 19:00:00  2007-11-06  ...   35.1  14.5  33.7  12.6   \n",
       "20        RJ  2007-11-06 20:00:00  2007-11-06  ...   34.7  14.5  32.2  12.8   \n",
       "21        RJ  2007-11-06 21:00:00  2007-11-06  ...   32.7  15.8  29.9  12.5   \n",
       "22        RJ  2007-11-06 22:00:00  2007-11-06  ...   31.7  15.4  29.4  11.3   \n",
       "23        RJ  2007-11-06 23:00:00  2007-11-06  ...   31.5  13.3  29.8  11.4   \n",
       "24        RJ  2007-11-07 00:00:00  2007-11-07  ...   31.0  15.1  30.2  13.4   \n",
       "25        RJ  2007-11-07 01:00:00  2007-11-07  ...   30.3  15.1  29.3  13.1   \n",
       "26        RJ  2007-11-07 02:00:00  2007-11-07  ...   29.3  14.0  28.1  13.1   \n",
       "27        RJ  2007-11-07 03:00:00  2007-11-07  ...   28.1  15.5  26.5  14.0   \n",
       "28        RJ  2007-11-07 04:00:00  2007-11-07  ...   26.6  16.4  25.1  15.5   \n",
       "29        RJ  2007-11-07 05:00:00  2007-11-07  ...   25.2  16.4  23.7  15.3   \n",
       "...      ...                  ...         ...  ...    ...   ...   ...   ...   \n",
       "9779138   SP  2016-09-29 18:00:00  2016-09-29  ...   24.6  13.0  21.7  11.6   \n",
       "9779139   SP  2016-09-29 19:00:00  2016-09-29  ...   22.1  12.9  20.0  11.7   \n",
       "9779140   SP  2016-09-29 20:00:00  2016-09-29  ...   20.2  12.6  16.8  11.7   \n",
       "9779141   SP  2016-09-29 21:00:00  2016-09-29  ...   16.9  12.1  15.3  11.5   \n",
       "9779142   SP  2016-09-29 22:00:00  2016-09-29  ...   15.3  12.4  14.2  11.6   \n",
       "9779143   SP  2016-09-29 23:00:00  2016-09-29  ...   14.7  11.8  14.2  10.2   \n",
       "9779144   SP  2016-09-30 00:00:00  2016-09-30  ...   14.9  11.4  14.5  10.3   \n",
       "9779145   SP  2016-09-30 01:00:00  2016-09-30  ...   14.8  11.4  14.2   9.9   \n",
       "9779146   SP  2016-09-30 02:00:00  2016-09-30  ...   14.7  10.2  14.3   9.2   \n",
       "9779147   SP  2016-09-30 03:00:00  2016-09-30  ...   14.8  11.4  14.3   9.6   \n",
       "9779148   SP  2016-09-30 04:00:00  2016-09-30  ...   14.9  12.3  14.7  11.3   \n",
       "9779149   SP  2016-09-30 05:00:00  2016-09-30  ...   14.9  12.2  14.8  10.9   \n",
       "9779150   SP  2016-09-30 06:00:00  2016-09-30  ...   14.9  11.6  14.6  10.9   \n",
       "9779151   SP  2016-09-30 07:00:00  2016-09-30  ...   14.8  11.8  14.5  11.4   \n",
       "9779152   SP  2016-09-30 08:00:00  2016-09-30  ...   14.9  11.8  14.6  11.3   \n",
       "9779153   SP  2016-09-30 09:00:00  2016-09-30  ...   14.9  11.7  14.2  11.3   \n",
       "9779154   SP  2016-09-30 10:00:00  2016-09-30  ...   15.8  11.4  14.3  11.1   \n",
       "9779155   SP  2016-09-30 11:00:00  2016-09-30  ...   17.7  12.0  15.6  11.0   \n",
       "9779156   SP  2016-09-30 12:00:00  2016-09-30  ...   19.3  12.0  17.1  10.6   \n",
       "9779157   SP  2016-09-30 13:00:00  2016-09-30  ...   20.5  12.2  18.2  10.6   \n",
       "9779158   SP  2016-09-30 14:00:00  2016-09-30  ...   21.4  12.5  19.4   9.8   \n",
       "9779159   SP  2016-09-30 15:00:00  2016-09-30  ...   21.8  12.1  19.9  10.6   \n",
       "9779160   SP  2016-09-30 16:00:00  2016-09-30  ...   21.4  12.8  20.2  11.5   \n",
       "9779161   SP  2016-09-30 17:00:00  2016-09-30  ...   21.2  12.8  19.3  11.5   \n",
       "9779162   SP  2016-09-30 18:00:00  2016-09-30  ...   19.5  12.8  18.0  11.8   \n",
       "9779163   SP  2016-09-30 19:00:00  2016-09-30  ...   18.2  12.4  16.3  11.8   \n",
       "9779164   SP  2016-09-30 20:00:00  2016-09-30  ...   16.8  12.5  15.3  11.7   \n",
       "9779165   SP  2016-09-30 21:00:00  2016-09-30  ...   15.3  11.9  14.9  11.5   \n",
       "9779166   SP  2016-09-30 22:00:00  2016-09-30  ...   15.0  11.7  14.4  11.4   \n",
       "9779167   SP  2016-09-30 23:00:00  2016-09-30  ...   14.6  11.5  14.3  11.2   \n",
       "\n",
       "         hmdy  hmax  hmin  wdsp   wdct  gust  \n",
       "0        35.0  58.0  32.0   3.2  101.0   6.5  \n",
       "1        39.0  39.0  35.0   3.6   94.0   6.4  \n",
       "2        44.0  44.0  39.0   2.5   93.0   6.9  \n",
       "3        58.0  58.0  44.0   1.7   96.0   5.8  \n",
       "4        57.0  58.0  56.0   3.1  110.0   7.5  \n",
       "5        62.0  62.0  57.0   2.0   99.0   6.8  \n",
       "6        72.0  72.0  62.0   1.3   93.0   4.9  \n",
       "7        86.0  89.0  72.0   0.5  157.0   2.8  \n",
       "8        93.0  94.0  85.0   0.0  141.0   1.5  \n",
       "9        75.0  94.0  75.0   0.0  248.0   0.0  \n",
       "10       61.0  76.0  61.0   3.3   97.0   6.2  \n",
       "11        0.0   0.0   0.0   0.0    0.0   0.0  \n",
       "12        0.0   0.0   0.0   0.0    0.0   0.0  \n",
       "13        0.0   0.0   0.0   0.0    0.0   0.0  \n",
       "14       36.0  42.0  36.0   3.2   97.0   9.1  \n",
       "15       32.0  37.0  31.0   3.8  103.0   8.6  \n",
       "16       31.0  34.0  29.0   3.7   78.0   9.6  \n",
       "17       29.0  31.0  27.0   2.8  102.0   9.0  \n",
       "18       27.0  29.0  26.0   2.5   94.0   9.0  \n",
       "19       28.0  30.0  26.0   2.9   93.0   8.5  \n",
       "20       30.0  33.0  28.0   2.7  106.0   5.8  \n",
       "21       40.0  42.0  30.0   1.5  102.0   5.2  \n",
       "22       29.0  42.0  29.0   2.4  123.0   4.9  \n",
       "23       35.0  35.0  29.0   3.4  112.0   7.8  \n",
       "24       40.0  40.0  35.0   4.2  109.0   8.6  \n",
       "25       37.0  41.0  36.0   5.4  109.0  11.5  \n",
       "26       42.0  42.0  37.0   6.1  120.0  11.6  \n",
       "27       51.0  51.0  42.0   5.0  114.0  11.6  \n",
       "28       58.0  58.0  51.0   3.1  100.0   9.8  \n",
       "29       59.0  59.0  58.0   1.9  111.0   7.2  \n",
       "...       ...   ...   ...   ...    ...   ...  \n",
       "9779138  53.0  55.0  45.0   0.0    0.0   0.0  \n",
       "9779139  61.0  62.0  53.0   0.0    0.0   0.0  \n",
       "9779140  72.0  73.0  61.0   0.0    0.0   0.0  \n",
       "9779141  79.0  79.0  72.0   0.0    0.0   0.0  \n",
       "9779142  84.0  88.0  79.0   0.0    0.0   0.0  \n",
       "9779143  75.0  84.0  75.0   0.0    0.0   0.0  \n",
       "9779144  81.0  81.0  75.0   0.0    0.0   0.0  \n",
       "9779145  75.0  81.0  75.0   0.0    0.0   0.0  \n",
       "9779146  73.0  76.0  70.0   0.0    0.0   0.0  \n",
       "9779147  80.0  80.0  73.0   0.0    0.0   0.0  \n",
       "9779148  84.0  85.0  80.0   0.0    0.0   0.0  \n",
       "9779149  77.0  84.0  77.0   0.0    0.0   0.0  \n",
       "9779150  81.0  81.0  77.0   0.0    0.0   0.0  \n",
       "9779151  81.0  83.0  81.0   0.0    0.0   0.0  \n",
       "9779152  80.0  82.0  79.0   0.0    0.0   0.0  \n",
       "9779153  82.0  83.0  80.0   0.0    0.0   0.0  \n",
       "9779154  74.0  82.0  74.0   0.0    0.0   0.0  \n",
       "9779155  69.0  75.0  67.0   0.0    0.0   0.0  \n",
       "9779156  60.0  69.0  58.0   0.0    0.0   0.0  \n",
       "9779157  58.0  64.0  56.0   0.0    0.0   0.0  \n",
       "9779158  55.0  62.0  51.0   0.0    0.0   0.0  \n",
       "9779159  54.0  58.0  51.0   0.0    0.0   0.0  \n",
       "9779160  59.0  60.0  54.0   0.0    0.0   0.0  \n",
       "9779161  64.0  65.0  57.0   0.0    0.0   0.0  \n",
       "9779162  67.0  68.0  64.0   0.0    0.0   0.0  \n",
       "9779163  76.0  77.0  67.0   0.0    0.0   0.0  \n",
       "9779164  80.0  80.0  75.0   0.0    0.0   0.0  \n",
       "9779165  79.0  81.0  79.0   0.0    0.0   0.0  \n",
       "9779166  82.0  83.0  79.0   0.0    0.0   0.0  \n",
       "9779167  82.0  82.0  81.0   0.0    0.0   0.0  \n",
       "\n",
       "[9779168 rows x 31 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"sudeste.csv\")\n",
    "df.fillna(value = 0, inplace=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filling columns using monthly mean value\n",
    "#### Here we use 4 cleaner objects to fill each targeting columns (temp, stp, hmdy, dewp, and prcp(partially))  in case the np array in case that object gets larger and larger and the code runs slower "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AFONSO CLAUDIO\n",
      "AIMORES\n",
      "ALEGRE\n",
      "ALFREDO CHAVES\n",
      "ALMENARA\n",
      "ARAXÁ\n",
      "ARIRANHA\n",
      "ARRAIAL DO CABO\n",
      "AVARÉ\n",
      "BARBACENA\n",
      "BARRA BONITA\n",
      "BARRA DO TURVO\n",
      "BARRETOS\n",
      "BARUERI\n",
      "BAURU\n",
      "BELO HOR. (PAMPULHA)\n",
      "BELO HORIZONTE - CERCADINHO\n",
      "BURITIS\n",
      "CALDAS\n",
      "CAMBUCÍ\n",
      "CAMPINA VERDE\n",
      "CAMPOS\n",
      "CAMPOS DO JORDÃO\n",
      "CAPELINHA\n",
      "CARATINGA\n",
      "CASA BRANCA\n",
      "CHAPADA GAÚCHA\n",
      "CONC. DAS ALAGOAS\n",
      "CORONEL PACHECO\n",
      "CURVELO\n",
      "DIAMANTINA\n",
      "DORES DO INDAIÁ\n",
      "ECOLOGIA AGRÍCOLA\n",
      "ESPINOSA\n",
      "FLORESTAL\n",
      "FORMIGA\n",
      "FORTE DE COPACABANA\n",
      "FRANCA\n",
      "GOVERNADOR VALADARES\n",
      "GUANHÃES\n",
      "GUARDA-MOR\n",
      "IBIRITÈ (ROLA MOÇA)\n",
      "IBITINGA\n",
      "IGUAPE\n",
      "ITAOBIM\n",
      "ITAPEVA\n",
      "ITAPIRA\n",
      "ITUIUTABA\n",
      "ITUVERAVA\n",
      "JACAREPAGUA\n",
      "JALES\n",
      "JANUARIA\n",
      "JOSÉ BONIFÁCIO\n",
      "JOÃO PINHEIRO\n",
      "JUÍZ DE FORA\n",
      "LINHARES\n",
      "LINS\n",
      "MACAÉ\n",
      "MANHUAÇU\n",
      "MANTENA\n",
      "MARAMBAIA\n",
      "MARIA DA FÉ\n",
      "MOCAMBINHO\n",
      "MOELA\n",
      "MONTALVANIA\n",
      "MONTE VERDE\n",
      "MONTES CLAROS\n",
      "MURIAÉ\n",
      "NOVA FRIBURGO\n",
      "NOVA VENECIA\n",
      "OURINHOS\n",
      "OURO BRANCO\n",
      "PARATÍ\n",
      "PASSA QUATRO\n",
      "PASSOS\n",
      "PATROCÍNIO\n",
      "PICO DO COUTO\n",
      "PIRACICABA\n",
      "PIRAPORA\n",
      "POMPEU\n",
      "PRADÓPOLIS\n",
      "PRES. KENNEDY\n",
      "PRESIDENTE PRUDENTE\n",
      "RANCHARIA\n",
      "RESENDE\n",
      "RIO CLARO\n",
      "RIO PARDO DE MINAS\n",
      "S LUIS DO PARAITINGA\n",
      "S. MIG. ARCANJO\n",
      "S.J.DEL REI\n",
      "SACRAMENTO\n",
      "SALINAS\n",
      "SANTA TERESA\n",
      "SAO PAULO\n",
      "SAQUAREMA\n",
      "SERRA DOS AIMORES\n",
      "SETE LAGOAS\n",
      "SILVA JARDIM\n",
      "SOROCABA\n",
      "SÃO CARLOS\n",
      "SÃO GONÇALO\n",
      "SÃO MATEUS\n",
      "SÃO ROMÃO\n",
      "SÃO SEBASTIAO DO PARAÍSO\n",
      "SÃO TOMÉ\n",
      "TAUBATÉ\n",
      "TERESÓPOLIS\n",
      "TEÓFILO OTONI\n",
      "TIMÓTEO\n",
      "TRÊS MARIAS\n",
      "TRÊS RIOS \n",
      "UBERLÂNDIA\n",
      "UNAI\n",
      "VALENÇA\n",
      "VALPARAISO\n",
      "VARGINHA\n",
      "VILA MILITAR\n",
      "VITÓRIA\n",
      "VIÇOSA\n",
      "VOTUPORANGA\n",
      "XEREM\n",
      "ÁGUAS VERMELHAS\n"
     ]
    }
   ],
   "source": [
    "temp_cleaner1 = CleanerMonthly(df)\n",
    "temp_cleaner2 = CleanerMonthly(df)\n",
    "temp_cleaner3 = CleanerMonthly(df)\n",
    "temp_cleaner4 = CleanerMonthly(df)\n",
    "temp_cleaner1.cleaning_monthly(19, 0, 30)\n",
    "temp_cleaner2.cleaning_monthly(19, 30, 60)\n",
    "temp_cleaner3.cleaning_monthly(19, 60, 90)\n",
    "temp_cleaner4.cleaning_monthly(19, 90, 122)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp_filled = np.concatenate((temp_cleaner1.filled_column[1:], temp_cleaner2.filled_column[1:], temp_cleaner3.filled_column[1:], temp_cleaner4.filled_column[1:]))\n",
    "temp_filled_df = pd.DataFrame(temp_filled, columns = df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Clear memory\n",
    "del temp_cleaner1\n",
    "del temp_cleaner2\n",
    "del temp_cleaner3\n",
    "del temp_cleaner4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AFONSO CLAUDIO\n",
      "AIMORES\n",
      "ALEGRE\n",
      "ALFREDO CHAVES\n",
      "ALMENARA\n",
      "ARAXÁ\n",
      "ARIRANHA\n",
      "ARRAIAL DO CABO\n",
      "AVARÉ\n",
      "BARBACENA\n",
      "BARRA BONITA\n",
      "BARRA DO TURVO\n",
      "BARRETOS\n",
      "BARUERI\n",
      "BAURU\n",
      "BELO HOR. (PAMPULHA)\n",
      "BELO HORIZONTE - CERCADINHO\n",
      "BURITIS\n",
      "CALDAS\n",
      "CAMBUCÍ\n",
      "CAMPINA VERDE\n",
      "CAMPOS\n",
      "CAMPOS DO JORDÃO\n",
      "CAPELINHA\n",
      "CARATINGA\n",
      "CASA BRANCA\n",
      "CHAPADA GAÚCHA\n",
      "CONC. DAS ALAGOAS\n",
      "CORONEL PACHECO\n",
      "CURVELO\n",
      "DIAMANTINA\n",
      "DORES DO INDAIÁ\n",
      "ECOLOGIA AGRÍCOLA\n",
      "ESPINOSA\n",
      "FLORESTAL\n",
      "FORMIGA\n",
      "FORTE DE COPACABANA\n",
      "FRANCA\n",
      "GOVERNADOR VALADARES\n",
      "GUANHÃES\n",
      "GUARDA-MOR\n",
      "IBIRITÈ (ROLA MOÇA)\n",
      "IBITINGA\n",
      "IGUAPE\n",
      "ITAOBIM\n",
      "ITAPEVA\n",
      "ITAPIRA\n",
      "ITUIUTABA\n",
      "ITUVERAVA\n",
      "JACAREPAGUA\n",
      "JALES\n",
      "JANUARIA\n",
      "JOSÉ BONIFÁCIO\n",
      "JOÃO PINHEIRO\n",
      "JUÍZ DE FORA\n",
      "LINHARES\n",
      "LINS\n",
      "MACAÉ\n",
      "MANHUAÇU\n",
      "MANTENA\n",
      "MARAMBAIA\n",
      "MARIA DA FÉ\n",
      "MOCAMBINHO\n",
      "MOELA\n",
      "MONTALVANIA\n",
      "MONTE VERDE\n",
      "MONTES CLAROS\n",
      "MURIAÉ\n",
      "NOVA FRIBURGO\n",
      "NOVA VENECIA\n",
      "OURINHOS\n",
      "OURO BRANCO\n",
      "PARATÍ\n",
      "PASSA QUATRO\n",
      "PASSOS\n",
      "PATROCÍNIO\n",
      "PICO DO COUTO\n",
      "PIRACICABA\n",
      "PIRAPORA\n",
      "POMPEU\n",
      "PRADÓPOLIS\n",
      "PRES. KENNEDY\n",
      "PRESIDENTE PRUDENTE\n",
      "RANCHARIA\n",
      "RESENDE\n",
      "RIO CLARO\n",
      "RIO PARDO DE MINAS\n",
      "S LUIS DO PARAITINGA\n",
      "S. MIG. ARCANJO\n",
      "S.J.DEL REI\n",
      "SACRAMENTO\n",
      "SALINAS\n",
      "SANTA TERESA\n",
      "SAO PAULO\n",
      "SAQUAREMA\n",
      "SERRA DOS AIMORES\n",
      "SETE LAGOAS\n",
      "SILVA JARDIM\n",
      "SOROCABA\n",
      "SÃO CARLOS\n",
      "SÃO GONÇALO\n",
      "SÃO MATEUS\n",
      "SÃO ROMÃO\n",
      "SÃO SEBASTIAO DO PARAÍSO\n",
      "SÃO TOMÉ\n",
      "TAUBATÉ\n",
      "TERESÓPOLIS\n",
      "TEÓFILO OTONI\n",
      "TIMÓTEO\n",
      "TRÊS MARIAS\n",
      "TRÊS RIOS \n",
      "UBERLÂNDIA\n",
      "UNAI\n",
      "VALENÇA\n",
      "VALPARAISO\n",
      "VARGINHA\n",
      "VILA MILITAR\n",
      "VITÓRIA\n",
      "VIÇOSA\n",
      "VOTUPORANGA\n",
      "XEREM\n",
      "ÁGUAS VERMELHAS\n"
     ]
    }
   ],
   "source": [
    "# Cleaning stp\n",
    "stp_cleaner1 = CleanerMonthly(temp_filled_df)\n",
    "stp_cleaner2 = CleanerMonthly(temp_filled_df)\n",
    "stp_cleaner3 = CleanerMonthly(temp_filled_df)\n",
    "stp_cleaner4 = CleanerMonthly(temp_filled_df)\n",
    "stp_cleaner1.cleaning_monthly(15, 0, 30)\n",
    "stp_cleaner2.cleaning_monthly(15, 30, 60)\n",
    "stp_cleaner3.cleaning_monthly(15, 60, 90)\n",
    "stp_cleaner4.cleaning_monthly(15, 90, 122)\n",
    "stp_filled = np.concatenate((stp_cleaner1.filled_column[1:], stp_cleaner2.filled_column[1:], stp_cleaner3.filled_column[1:], stp_cleaner4.filled_column[1:]))\n",
    "stp_filled_df = pd.DataFrame(stp_filled, columns = df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Clear memory\n",
    "del stp_cleaner1\n",
    "del stp_cleaner2\n",
    "del stp_cleaner3\n",
    "del stp_cleaner4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9779168, 31)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stp_filled_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AFONSO CLAUDIO\n",
      "AIMORES\n",
      "ALEGRE\n",
      "ALFREDO CHAVES\n",
      "ALMENARA\n",
      "ARAXÁ\n",
      "ARIRANHA\n",
      "ARRAIAL DO CABO\n",
      "AVARÉ\n",
      "BARBACENA\n",
      "BARRA BONITA\n",
      "BARRA DO TURVO\n",
      "BARRETOS\n",
      "BARUERI\n",
      "BAURU\n",
      "BELO HOR. (PAMPULHA)\n",
      "BELO HORIZONTE - CERCADINHO\n",
      "BURITIS\n",
      "CALDAS\n",
      "CAMBUCÍ\n",
      "CAMPINA VERDE\n",
      "CAMPOS\n",
      "CAMPOS DO JORDÃO\n",
      "CAPELINHA\n",
      "CARATINGA\n",
      "CASA BRANCA\n",
      "CHAPADA GAÚCHA\n",
      "CONC. DAS ALAGOAS\n",
      "CORONEL PACHECO\n",
      "CURVELO\n",
      "DIAMANTINA\n",
      "DORES DO INDAIÁ\n",
      "ECOLOGIA AGRÍCOLA\n",
      "ESPINOSA\n",
      "FLORESTAL\n",
      "FORMIGA\n",
      "FORTE DE COPACABANA\n",
      "FRANCA\n",
      "GOVERNADOR VALADARES\n",
      "GUANHÃES\n",
      "GUARDA-MOR\n",
      "IBIRITÈ (ROLA MOÇA)\n",
      "IBITINGA\n",
      "IGUAPE\n",
      "ITAOBIM\n",
      "ITAPEVA\n",
      "ITAPIRA\n",
      "ITUIUTABA\n",
      "ITUVERAVA\n",
      "JACAREPAGUA\n",
      "JALES\n",
      "JANUARIA\n",
      "JOSÉ BONIFÁCIO\n",
      "JOÃO PINHEIRO\n",
      "JUÍZ DE FORA\n",
      "LINHARES\n",
      "LINS\n",
      "MACAÉ\n",
      "MANHUAÇU\n",
      "MANTENA\n",
      "MARAMBAIA\n",
      "MARIA DA FÉ\n",
      "MOCAMBINHO\n",
      "MOELA\n",
      "MONTALVANIA\n",
      "MONTE VERDE\n",
      "MONTES CLAROS\n",
      "MURIAÉ\n",
      "NOVA FRIBURGO\n",
      "NOVA VENECIA\n",
      "OURINHOS\n",
      "OURO BRANCO\n",
      "PARATÍ\n",
      "PASSA QUATRO\n",
      "PASSOS\n",
      "PATROCÍNIO\n",
      "PICO DO COUTO\n",
      "PIRACICABA\n",
      "PIRAPORA\n",
      "POMPEU\n",
      "PRADÓPOLIS\n",
      "PRES. KENNEDY\n",
      "PRESIDENTE PRUDENTE\n",
      "RANCHARIA\n",
      "RESENDE\n",
      "RIO CLARO\n",
      "RIO PARDO DE MINAS\n",
      "S LUIS DO PARAITINGA\n",
      "S. MIG. ARCANJO\n",
      "S.J.DEL REI\n",
      "SACRAMENTO\n",
      "SALINAS\n",
      "SANTA TERESA\n",
      "SAO PAULO\n",
      "SAQUAREMA\n",
      "SERRA DOS AIMORES\n",
      "SETE LAGOAS\n",
      "SILVA JARDIM\n",
      "SOROCABA\n",
      "SÃO CARLOS\n",
      "SÃO GONÇALO\n",
      "SÃO MATEUS\n",
      "SÃO ROMÃO\n",
      "SÃO SEBASTIAO DO PARAÍSO\n",
      "SÃO TOMÉ\n",
      "TAUBATÉ\n",
      "TERESÓPOLIS\n",
      "TEÓFILO OTONI\n",
      "TIMÓTEO\n",
      "TRÊS MARIAS\n",
      "TRÊS RIOS \n",
      "UBERLÂNDIA\n",
      "UNAI\n",
      "VALENÇA\n",
      "VALPARAISO\n",
      "VARGINHA\n",
      "VILA MILITAR\n",
      "VITÓRIA\n",
      "VIÇOSA\n",
      "VOTUPORANGA\n",
      "XEREM\n",
      "ÁGUAS VERMELHAS\n"
     ]
    }
   ],
   "source": [
    "# Cleaning hmdy\n",
    "hmdy_cleaner1 = CleanerMonthly(stp_filled_df)\n",
    "hmdy_cleaner2 = CleanerMonthly(stp_filled_df)\n",
    "hmdy_cleaner3 = CleanerMonthly(stp_filled_df)\n",
    "hmdy_cleaner4 = CleanerMonthly(stp_filled_df)\n",
    "hmdy_cleaner1.cleaning_monthly(25, 0, 30)\n",
    "hmdy_cleaner2.cleaning_monthly(25, 30, 60)\n",
    "hmdy_cleaner3.cleaning_monthly(25, 60, 90)\n",
    "hmdy_cleaner4.cleaning_monthly(25, 90, 122)\n",
    "hmdy_filled = np.concatenate((hmdy_cleaner1.filled_column[1:], hmdy_cleaner2.filled_column[1:], hmdy_cleaner3.filled_column[1:], hmdy_cleaner4.filled_column[1:]))\n",
    "hmdy_filled_df = pd.DataFrame(hmdy_filled, columns = df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "del hmdy_cleaner1\n",
    "del hmdy_cleaner2\n",
    "del hmdy_cleaner3\n",
    "del hmdy_cleaner4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AFONSO CLAUDIO\n",
      "AIMORES\n",
      "ALEGRE\n",
      "ALFREDO CHAVES\n",
      "ALMENARA\n",
      "ARAXÁ\n",
      "ARIRANHA\n",
      "ARRAIAL DO CABO\n",
      "AVARÉ\n",
      "BARBACENA\n",
      "BARRA BONITA\n",
      "BARRA DO TURVO\n",
      "BARRETOS\n",
      "BARUERI\n",
      "BAURU\n",
      "BELO HOR. (PAMPULHA)\n",
      "BELO HORIZONTE - CERCADINHO\n",
      "BURITIS\n",
      "CALDAS\n",
      "CAMBUCÍ\n",
      "CAMPINA VERDE\n",
      "CAMPOS\n",
      "CAMPOS DO JORDÃO\n",
      "CAPELINHA\n",
      "CARATINGA\n",
      "CASA BRANCA\n",
      "CHAPADA GAÚCHA\n",
      "CONC. DAS ALAGOAS\n",
      "CORONEL PACHECO\n",
      "CURVELO\n",
      "DIAMANTINA\n",
      "DORES DO INDAIÁ\n",
      "ECOLOGIA AGRÍCOLA\n",
      "ESPINOSA\n",
      "FLORESTAL\n",
      "FORMIGA\n",
      "FORTE DE COPACABANA\n",
      "FRANCA\n",
      "GOVERNADOR VALADARES\n",
      "GUANHÃES\n",
      "GUARDA-MOR\n",
      "IBIRITÈ (ROLA MOÇA)\n",
      "IBITINGA\n",
      "IGUAPE\n",
      "ITAOBIM\n",
      "ITAPEVA\n",
      "ITAPIRA\n",
      "ITUIUTABA\n",
      "ITUVERAVA\n",
      "JACAREPAGUA\n",
      "JALES\n",
      "JANUARIA\n",
      "JOSÉ BONIFÁCIO\n",
      "JOÃO PINHEIRO\n",
      "JUÍZ DE FORA\n",
      "LINHARES\n",
      "LINS\n",
      "MACAÉ\n",
      "MANHUAÇU\n",
      "MANTENA\n",
      "MARAMBAIA\n",
      "MARIA DA FÉ\n",
      "MOCAMBINHO\n",
      "MOELA\n",
      "MONTALVANIA\n",
      "MONTE VERDE\n",
      "MONTES CLAROS\n",
      "MURIAÉ\n",
      "NOVA FRIBURGO\n",
      "NOVA VENECIA\n",
      "OURINHOS\n",
      "OURO BRANCO\n",
      "PARATÍ\n",
      "PASSA QUATRO\n",
      "PASSOS\n",
      "PATROCÍNIO\n",
      "PICO DO COUTO\n",
      "PIRACICABA\n",
      "PIRAPORA\n",
      "POMPEU\n",
      "PRADÓPOLIS\n",
      "PRES. KENNEDY\n",
      "PRESIDENTE PRUDENTE\n",
      "RANCHARIA\n",
      "RESENDE\n",
      "RIO CLARO\n",
      "RIO PARDO DE MINAS\n",
      "S LUIS DO PARAITINGA\n",
      "S. MIG. ARCANJO\n",
      "S.J.DEL REI\n",
      "SACRAMENTO\n",
      "SALINAS\n",
      "SANTA TERESA\n",
      "SAO PAULO\n",
      "SAQUAREMA\n",
      "SERRA DOS AIMORES\n",
      "SETE LAGOAS\n",
      "SILVA JARDIM\n",
      "SOROCABA\n",
      "SÃO CARLOS\n",
      "SÃO GONÇALO\n",
      "SÃO MATEUS\n",
      "SÃO ROMÃO\n",
      "SÃO SEBASTIAO DO PARAÍSO\n",
      "SÃO TOMÉ\n",
      "TAUBATÉ\n",
      "TERESÓPOLIS\n",
      "TEÓFILO OTONI\n",
      "TIMÓTEO\n",
      "TRÊS MARIAS\n",
      "TRÊS RIOS \n",
      "UBERLÂNDIA\n",
      "UNAI\n",
      "VALENÇA\n",
      "VALPARAISO\n",
      "VARGINHA\n",
      "VILA MILITAR\n",
      "VITÓRIA\n",
      "VIÇOSA\n",
      "VOTUPORANGA\n",
      "XEREM\n",
      "ÁGUAS VERMELHAS\n"
     ]
    }
   ],
   "source": [
    "# Cleaning dewp\n",
    "dewp_cleaner1 = CleanerMonthly(hmdy_filled_df)\n",
    "dewp_cleaner2 = CleanerMonthly(hmdy_filled_df)\n",
    "dewp_cleaner3 = CleanerMonthly(hmdy_filled_df)\n",
    "dewp_cleaner4 = CleanerMonthly(hmdy_filled_df)\n",
    "dewp_cleaner1.cleaning_monthly(20, 0, 30)\n",
    "dewp_cleaner2.cleaning_monthly(20, 30, 60)\n",
    "dewp_cleaner3.cleaning_monthly(20, 60, 90)\n",
    "dewp_cleaner4.cleaning_monthly(20, 90, 122)\n",
    "dewp_filled = np.concatenate((dewp_cleaner1.filled_column[1:], dewp_cleaner2.filled_column[1:], dewp_cleaner3.filled_column[1:], dewp_cleaner4.filled_column[1:]))\n",
    "dewp_filled_df = pd.DataFrame(dewp_filled, columns = df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "del dewp_cleaner1\n",
    "del dewp_cleaner2\n",
    "del dewp_cleaner3\n",
    "del dewp_cleaner4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AFONSO CLAUDIO\n",
      "AIMORES\n",
      "ALEGRE\n",
      "ALFREDO CHAVES\n",
      "ALMENARA\n",
      "ARAXÁ\n",
      "ARIRANHA\n",
      "ARRAIAL DO CABO\n",
      "AVARÉ\n",
      "BARBACENA\n",
      "BARRA BONITA\n",
      "BARRA DO TURVO\n",
      "BARRETOS\n",
      "BARUERI\n",
      "BAURU\n",
      "BELO HOR. (PAMPULHA)\n",
      "BELO HORIZONTE - CERCADINHO\n",
      "BURITIS\n",
      "CALDAS\n",
      "CAMBUCÍ\n",
      "CAMPINA VERDE\n",
      "CAMPOS\n",
      "CAMPOS DO JORDÃO\n",
      "CAPELINHA\n",
      "CARATINGA\n",
      "CASA BRANCA\n",
      "CHAPADA GAÚCHA\n",
      "CONC. DAS ALAGOAS\n",
      "CORONEL PACHECO\n",
      "CURVELO\n",
      "DIAMANTINA\n",
      "DORES DO INDAIÁ\n",
      "ECOLOGIA AGRÍCOLA\n",
      "ESPINOSA\n",
      "FLORESTAL\n",
      "FORMIGA\n",
      "FORTE DE COPACABANA\n",
      "FRANCA\n",
      "GOVERNADOR VALADARES\n",
      "GUANHÃES\n",
      "GUARDA-MOR\n",
      "IBIRITÈ (ROLA MOÇA)\n",
      "IBITINGA\n",
      "IGUAPE\n",
      "ITAOBIM\n",
      "ITAPEVA\n",
      "ITAPIRA\n",
      "ITUIUTABA\n",
      "ITUVERAVA\n",
      "JACAREPAGUA\n",
      "JALES\n",
      "JANUARIA\n",
      "JOSÉ BONIFÁCIO\n",
      "JOÃO PINHEIRO\n",
      "JUÍZ DE FORA\n",
      "LINHARES\n",
      "LINS\n",
      "MACAÉ\n",
      "MANHUAÇU\n",
      "MANTENA\n",
      "MARAMBAIA\n",
      "MARIA DA FÉ\n",
      "MOCAMBINHO\n",
      "MOELA\n",
      "MONTALVANIA\n",
      "MONTE VERDE\n",
      "MONTES CLAROS\n",
      "MURIAÉ\n",
      "NOVA FRIBURGO\n",
      "NOVA VENECIA\n",
      "OURINHOS\n",
      "OURO BRANCO\n",
      "PARATÍ\n",
      "PASSA QUATRO\n",
      "PASSOS\n",
      "PATROCÍNIO\n",
      "PICO DO COUTO\n",
      "PIRACICABA\n",
      "PIRAPORA\n",
      "POMPEU\n",
      "PRADÓPOLIS\n",
      "PRES. KENNEDY\n",
      "PRESIDENTE PRUDENTE\n",
      "RANCHARIA\n",
      "RESENDE\n",
      "RIO CLARO\n",
      "RIO PARDO DE MINAS\n",
      "S LUIS DO PARAITINGA\n",
      "S. MIG. ARCANJO\n",
      "S.J.DEL REI\n",
      "SACRAMENTO\n",
      "SALINAS\n",
      "SANTA TERESA\n",
      "SAO PAULO\n",
      "SAQUAREMA\n",
      "SERRA DOS AIMORES\n",
      "SETE LAGOAS\n",
      "SILVA JARDIM\n",
      "SOROCABA\n",
      "SÃO CARLOS\n",
      "SÃO GONÇALO\n",
      "SÃO MATEUS\n",
      "SÃO ROMÃO\n",
      "SÃO SEBASTIAO DO PARAÍSO\n",
      "SÃO TOMÉ\n",
      "TAUBATÉ\n",
      "TERESÓPOLIS\n",
      "TEÓFILO OTONI\n",
      "TIMÓTEO\n",
      "TRÊS MARIAS\n",
      "TRÊS RIOS \n",
      "UBERLÂNDIA\n",
      "UNAI\n",
      "VALENÇA\n",
      "VALPARAISO\n",
      "VARGINHA\n",
      "VILA MILITAR\n",
      "VITÓRIA\n",
      "VIÇOSA\n",
      "VOTUPORANGA\n",
      "XEREM\n",
      "ÁGUAS VERMELHAS\n"
     ]
    }
   ],
   "source": [
    "# Cleaning prcp\n",
    "prcp_cleaner1 = CleanerMonthly(dewp_filled_df)\n",
    "prcp_cleaner2 = CleanerMonthly(dewp_filled_df)\n",
    "prcp_cleaner3 = CleanerMonthly(dewp_filled_df)\n",
    "prcp_cleaner4 = CleanerMonthly(dewp_filled_df)\n",
    "prcp_cleaner1.cleaning_monthly(14, 0, 30)\n",
    "prcp_cleaner2.cleaning_monthly(14, 30, 60)\n",
    "prcp_cleaner3.cleaning_monthly(14, 60, 90)\n",
    "prcp_cleaner4.cleaning_monthly(14, 90, 122)\n",
    "prcp_filled = np.concatenate((prcp_cleaner1.filled_column[1:], prcp_cleaner2.filled_column[1:], prcp_cleaner3.filled_column[1:], prcp_cleaner4.filled_column[1:]))\n",
    "prcp_filled_df = pd.DataFrame(prcp_filled, columns = df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "del prcp_cleaner1\n",
    "del prcp_cleaner2\n",
    "del prcp_cleaner3\n",
    "del prcp_cleaner4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## For some rows, fillna with previous n values works"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "filled_wdsp = fillna_mean_prev_n(np.array(prcp_filled_df['wdsp']), 5, 0.3)\n",
    "prcp_filled_df['wdsp'] = filled_wdsp\n",
    "filled_gust = fillna_mean_prev_n(np.array(prcp_filled_df['gust']), 5, 0.3)\n",
    "prcp_filled_df['gust'] = filled_gust\n",
    "filled_wdct = fillna_mean_prev_n(np.array(prcp_filled_df['wdct']), 5, 1.0)\n",
    "prcp_filled_df['wdct'] = filled_wdct"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## For a specific wsnm (Moela), its lat, lon, and elevation is missing, so we simply use google to find these data and plug in"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"\n",
      "/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n",
      "/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "lat_for_moela = -24.0081332\n",
    "lon_for_moela = -46.3280574\n",
    "ele_for_moela = 120\n",
    "moela = prcp_filled_df[prcp_filled_df['wsnm'] == 'MOELA']\n",
    "moela['elvt'] = ele_for_moela\n",
    "moela['lat'] = lat_for_moela\n",
    "moela['lon'] = lon_for_moela\n",
    "prcp_filled_df.update(moela)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "empty = prcp_filled_df[prcp_filled_df['wsnm'] == 'JACAREPAGUA']\n",
    "dropped_null = prcp_filled_df.drop(index = empty.index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## As column gbrd is missing a lot of rows (50 percent), LinearRegression is a good imputer if the confidence is not too low\n",
    "#### Let explore which columns to choose as features, which are related to gbrd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/rabona/Documents/DataWranglingContest/utils/RelationExplorer.py:15: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  sampled = self.df[self.df[self.x]!=0][self.df[self.y]!=0].sample(sample_size)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hr_vs_gbrd = RelationExplorer(prcp_filled_df, 'hr', 'gbrd')\n",
    "hr_vs_gbrd.plot_scatter(2000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/rabona/Documents/DataWranglingContest/utils/RelationExplorer.py:15: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  sampled = self.df[self.df[self.x]!=0][self.df[self.y]!=0].sample(sample_size)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "temp_vs_gbrd = RelationExplorer(prcp_filled_df, 'hr', 'temp')\n",
    "temp_vs_gbrd.plot_scatter(2000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# In case any thing crush, we save this df as csv first\n",
    "dropped_null.to_csv('partially_done.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Likewise, we found some other rows might be related to gbrd. So then we can make training and prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dropped_null = pd.read_csv('partially_done.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5508178727015569\n"
     ]
    }
   ],
   "source": [
    "#Training and testing\n",
    "train_test_df = dropped_null[dropped_null['gbrd']!=0][['gbrd', 'hr', 'mo', 'hmdy', 'temp','wdsp', 'lat', 'lon']]\n",
    "train_test_df['mo'] = cat_to_num(np.array(train_test_df['mo']), 6, 13)\n",
    "train_test_df['hr'] = cat_to_num(np.array(train_test_df['hr']), 12, 24)\n",
    "X = np.array(train_test_df.drop(['gbrd'], 1))\n",
    "y = np.array(train_test_df['gbrd'])\n",
    "X = preprocessing.scale(X)\n",
    "X_train, X_test, y_train, y_test = cross_validation.train_test_split(X, y, test_size=0.1)\n",
    "clf = LinearRegression()\n",
    "clf.fit(X_train, y_train)\n",
    "confidence = clf.score(X_test, y_test)\n",
    "print(confidence)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1467.67846652, 1672.84303379, 1895.68400705, ...,  698.82541643,\n",
       "       1112.65382275, 4261.46523076])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#predicting\n",
    "predicted_gbrd = predict(dropped_null[dropped_null['gbrd']==0][['gbrd', 'hr', 'mo', 'hmdy', 'temp','wdsp', 'lat', 'lon']], ['hr', 'mo', 'hmdy', 'temp','wdsp', 'lat', 'lon'], clf)\n",
    "predicted_gbrd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    }
   ],
   "source": [
    "#updating df\n",
    "predicted_df = dropped_null[dropped_null['gbrd']==0]\n",
    "predicted_df['gbrd'] = predicted_gbrd\n",
    "dropped_null.update(predicted_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'wsid', 'wsnm', 'elvt', 'lat', 'lon', 'inme', 'city',\n",
       "       'prov', 'mdct', 'date', 'yr', 'mo', 'da', 'hr', 'prcp', 'stp', 'smax',\n",
       "       'smin', 'gbrd', 'temp', 'dewp', 'tmax', 'dmax', 'tmin', 'dmin', 'hmdy',\n",
       "       'hmax', 'hmin', 'wdsp', 'wdct', 'gust'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dropped_null.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### For the rest of prcp, we do the same thing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:12: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  if sys.path[0] == '':\n"
     ]
    }
   ],
   "source": [
    "train_test_df = dropped_null[dropped_null['prcp']!=0][['prcp', 'stp', 'temp', 'dewp',  'hmdy','wdsp', 'mo', 'lon', 'lat', 'gust']]\n",
    "train_test_df['mo'] = cat_to_num(np.array(train_test_df['mo']), 7, 14)\n",
    "train_test_df['temp'] = cat_to_num(np.array(train_test_df['temp']), 20, 40)\n",
    "X = np.array(train_test_df.drop(['prcp'], 1))\n",
    "y = np.array(train_test_df['prcp'])\n",
    "X = preprocessing.scale(X)\n",
    "X_train, X_test, y_train, y_test = cross_validation.train_test_split(X, y, test_size=0.1)\n",
    "clf = LinearRegression()\n",
    "clf.fit(X_train, y_train)\n",
    "predicted_prcp = predict(dropped_null[dropped_null['prcp']==0][['prcp', 'stp', 'temp', 'dewp',  'hmdy','wdsp', 'mo', 'lon', 'lat', 'gust']], ['stp', 'temp', 'dewp',  'hmdy','wdsp', 'mo', 'lon', 'lat', 'gust'], clf)\n",
    "predicted_df = dropped_null[dropped_null['prcp']==0]\n",
    "predicted_df['prcp'] = predicted_prcp\n",
    "dropped_null.update(predicted_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Now we dealing with the last part, max and min"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6814801710699646"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmax_diff = np.mean(dropped_null[dropped_null['tmax']!=0]['tmax']-dropped_null[dropped_null['tmax']!=0]['temp'])\n",
    "tmin_diff = -np.mean(dropped_null[dropped_null['tmin']!=0]['tmin']-dropped_null[dropped_null['tmin']!=0]['temp'])\n",
    "tmax_diff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "tmax = to_max(dropped_null, 'tmax', 'temp', tmax_diff)\n",
    "tmin = to_max(dropped_null, 'tmin', 'temp', tmin_diff)\n",
    "dropped_null['tmax'] = tmax\n",
    "dropped_null['tmin'] = tmin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#smax, smin\n",
    "smax_diff = np.mean(dropped_null[dropped_null['smax']!=0]['smax']-dropped_null[dropped_null['smax']!=0]['stp'])\n",
    "smin_diff = -np.mean(dropped_null[dropped_null['smin']!=0]['smin']-dropped_null[dropped_null['smin']!=0]['stp'])\n",
    "smax = to_max(dropped_null, 'smax', 'stp', smax_diff)\n",
    "smin = to_max(dropped_null, 'smin', 'stp', smin_diff)\n",
    "dropped_null['smax'] = smax\n",
    "dropped_null['smin'] = smin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#dmax, dmin\n",
    "dmax_diff = np.mean(dropped_null[dropped_null['dmax']!=0]['dmax']-dropped_null[dropped_null['dmax']!=0]['dewp'])\n",
    "dmin_diff = -np.mean(dropped_null[dropped_null['dmin']!=0]['dmin']-dropped_null[dropped_null['dmin']!=0]['dewp'])\n",
    "dmax = to_max(dropped_null, 'dmax', 'dewp', dmax_diff)\n",
    "dmin = to_max(dropped_null, 'dmin', 'dewp', dmin_diff)\n",
    "dropped_null['dmax'] = dmax\n",
    "dropped_null['dmin'] = dmin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#hmax, hmin\n",
    "hmax_diff = np.mean(dropped_null[dropped_null['hmax']!=0]['hmax']-dropped_null[dropped_null['hmax']!=0]['hmdy'])\n",
    "hmin_diff = -np.mean(dropped_null[dropped_null['hmin']!=0]['hmin']-dropped_null[dropped_null['hmin']!=0]['hmdy'])\n",
    "hmax = to_max(dropped_null, 'hmax', 'hmdy', hmax_diff)\n",
    "hmin = to_max(dropped_null, 'hmin', 'hmdy', hmin_diff)\n",
    "dropped_null['hmax'] = hmax\n",
    "dropped_null['hmin'] = hmin"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Finished!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "dropped_null.to_csv('cleaned_sudeste.csv')"
   ]
  }
 ],
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