AnaliseV3-Final.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import datetime as dt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import datetime as dt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IMPORTANDO  E TRATANDO DADOS DE SEGMENTOS DO STRAVA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dados obtidos da api do strava https://developers.strava.com/docs/reference/\n",
    "# por meio de um app em python que foi desenvolvido para obter os dados, trasnformar e \n",
    "# gravar em csv separado por ';'\n",
    "\n",
    "df = pd.read_csv(\"stravaWSDetalhe.csv\", delimiter=';', parse_dates=['start_date', 'start_date_local'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      -20.392717\n",
       "1      -20.393215\n",
       "2      -20.393521\n",
       "3      -20.395038\n",
       "4      -20.396506\n",
       "          ...    \n",
       "5507   -20.352329\n",
       "5508   -20.352351\n",
       "5509   -20.353519\n",
       "5510   -20.352351\n",
       "5511   -20.353519\n",
       "Name: vse_start_latitude, Length: 5512, dtype: float64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['start_date'] = pd.to_datetime(df['start_date'],  format='%Y%m%d', utc=False).dt.date\n",
    "df['start_date'] = df['start_date'].astype('datetime64[ns]')\n",
    "\n",
    "df['vse_start_latitude'].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['vse_average_watts'] != 0]\n",
    "df = df[df['vse_average_heartrate'] != 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1697, 33)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>distance</th>\n",
       "      <th>moving_time</th>\n",
       "      <th>elapsed_time</th>\n",
       "      <th>total_elevation_gain</th>\n",
       "      <th>id</th>\n",
       "      <th>kudos_count</th>\n",
       "      <th>average_speed</th>\n",
       "      <th>max_speed</th>\n",
       "      <th>average_watts</th>\n",
       "      <th>kilojoules</th>\n",
       "      <th>...</th>\n",
       "      <th>vse_distance</th>\n",
       "      <th>vse_elapsed_time</th>\n",
       "      <th>vse_max_heartrate</th>\n",
       "      <th>vse_moving_time</th>\n",
       "      <th>vse_elevation_high</th>\n",
       "      <th>vse_elevation_low</th>\n",
       "      <th>vse_start_latitude</th>\n",
       "      <th>vse_start_longitude</th>\n",
       "      <th>vse_end_latitude</th>\n",
       "      <th>vse_end_longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1.697000e+03</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "      <td>1697.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>28317.918562</td>\n",
       "      <td>5467.386565</td>\n",
       "      <td>6477.428992</td>\n",
       "      <td>163.821096</td>\n",
       "      <td>1.922782e+09</td>\n",
       "      <td>14.631703</td>\n",
       "      <td>5.211740</td>\n",
       "      <td>10.486152</td>\n",
       "      <td>161.015439</td>\n",
       "      <td>875.935887</td>\n",
       "      <td>...</td>\n",
       "      <td>3640.712434</td>\n",
       "      <td>714.414260</td>\n",
       "      <td>141.825575</td>\n",
       "      <td>636.748969</td>\n",
       "      <td>11.244255</td>\n",
       "      <td>0.220153</td>\n",
       "      <td>-20.419028</td>\n",
       "      <td>-40.324213</td>\n",
       "      <td>-20.421825</td>\n",
       "      <td>-40.325318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>3537.800249</td>\n",
       "      <td>768.825245</td>\n",
       "      <td>1107.527661</td>\n",
       "      <td>66.949740</td>\n",
       "      <td>4.794097e+08</td>\n",
       "      <td>7.001466</td>\n",
       "      <td>0.491769</td>\n",
       "      <td>1.450688</td>\n",
       "      <td>14.136780</td>\n",
       "      <td>111.505645</td>\n",
       "      <td>...</td>\n",
       "      <td>4110.950159</td>\n",
       "      <td>883.981422</td>\n",
       "      <td>13.666478</td>\n",
       "      <td>717.683239</td>\n",
       "      <td>7.004403</td>\n",
       "      <td>4.218716</td>\n",
       "      <td>0.045122</td>\n",
       "      <td>0.022400</td>\n",
       "      <td>0.045907</td>\n",
       "      <td>0.023047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>12331.500000</td>\n",
       "      <td>2214.000000</td>\n",
       "      <td>2302.000000</td>\n",
       "      <td>44.800000</td>\n",
       "      <td>1.281568e+09</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.728000</td>\n",
       "      <td>6.700000</td>\n",
       "      <td>123.500000</td>\n",
       "      <td>368.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>166.600000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>-3.200000</td>\n",
       "      <td>-8.800000</td>\n",
       "      <td>-20.486974</td>\n",
       "      <td>-40.360662</td>\n",
       "      <td>-20.486917</td>\n",
       "      <td>-40.360624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>27588.900000</td>\n",
       "      <td>5156.000000</td>\n",
       "      <td>5884.000000</td>\n",
       "      <td>134.800000</td>\n",
       "      <td>1.468609e+09</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>5.078000</td>\n",
       "      <td>9.500000</td>\n",
       "      <td>153.100000</td>\n",
       "      <td>829.100000</td>\n",
       "      <td>...</td>\n",
       "      <td>995.400000</td>\n",
       "      <td>162.000000</td>\n",
       "      <td>134.000000</td>\n",
       "      <td>162.000000</td>\n",
       "      <td>7.600000</td>\n",
       "      <td>-2.900000</td>\n",
       "      <td>-20.456570</td>\n",
       "      <td>-40.340167</td>\n",
       "      <td>-20.454327</td>\n",
       "      <td>-40.337981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>29068.700000</td>\n",
       "      <td>5465.000000</td>\n",
       "      <td>6268.000000</td>\n",
       "      <td>144.300000</td>\n",
       "      <td>1.994719e+09</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>5.397000</td>\n",
       "      <td>10.700000</td>\n",
       "      <td>164.200000</td>\n",
       "      <td>889.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>2664.400000</td>\n",
       "      <td>479.000000</td>\n",
       "      <td>144.000000</td>\n",
       "      <td>464.000000</td>\n",
       "      <td>9.800000</td>\n",
       "      <td>-0.400000</td>\n",
       "      <td>-20.427257</td>\n",
       "      <td>-40.329905</td>\n",
       "      <td>-20.438855</td>\n",
       "      <td>-40.332232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>30516.300000</td>\n",
       "      <td>5810.000000</td>\n",
       "      <td>6780.000000</td>\n",
       "      <td>159.800000</td>\n",
       "      <td>2.204492e+09</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>5.555000</td>\n",
       "      <td>11.400000</td>\n",
       "      <td>171.700000</td>\n",
       "      <td>960.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>5078.600000</td>\n",
       "      <td>935.000000</td>\n",
       "      <td>152.000000</td>\n",
       "      <td>899.000000</td>\n",
       "      <td>16.400000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-20.393521</td>\n",
       "      <td>-40.317364</td>\n",
       "      <td>-20.396368</td>\n",
       "      <td>-40.319373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>34719.800000</td>\n",
       "      <td>7390.000000</td>\n",
       "      <td>9964.000000</td>\n",
       "      <td>377.400000</td>\n",
       "      <td>2.802778e+09</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>5.791000</td>\n",
       "      <td>14.600000</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>1060.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>22479.900000</td>\n",
       "      <td>5028.000000</td>\n",
       "      <td>173.000000</td>\n",
       "      <td>4345.000000</td>\n",
       "      <td>43.400000</td>\n",
       "      <td>31.200000</td>\n",
       "      <td>-20.321809</td>\n",
       "      <td>-40.268613</td>\n",
       "      <td>-20.321643</td>\n",
       "      <td>-40.268728</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           distance  moving_time  elapsed_time  total_elevation_gain  \\\n",
       "count   1697.000000  1697.000000   1697.000000           1697.000000   \n",
       "mean   28317.918562  5467.386565   6477.428992            163.821096   \n",
       "std     3537.800249   768.825245   1107.527661             66.949740   \n",
       "min    12331.500000  2214.000000   2302.000000             44.800000   \n",
       "25%    27588.900000  5156.000000   5884.000000            134.800000   \n",
       "50%    29068.700000  5465.000000   6268.000000            144.300000   \n",
       "75%    30516.300000  5810.000000   6780.000000            159.800000   \n",
       "max    34719.800000  7390.000000   9964.000000            377.400000   \n",
       "\n",
       "                 id  kudos_count  average_speed    max_speed  average_watts  \\\n",
       "count  1.697000e+03  1697.000000    1697.000000  1697.000000    1697.000000   \n",
       "mean   1.922782e+09    14.631703       5.211740    10.486152     161.015439   \n",
       "std    4.794097e+08     7.001466       0.491769     1.450688      14.136780   \n",
       "min    1.281568e+09     0.000000       3.728000     6.700000     123.500000   \n",
       "25%    1.468609e+09     9.000000       5.078000     9.500000     153.100000   \n",
       "50%    1.994719e+09    14.000000       5.397000    10.700000     164.200000   \n",
       "75%    2.204492e+09    19.000000       5.555000    11.400000     171.700000   \n",
       "max    2.802778e+09    32.000000       5.791000    14.600000     183.000000   \n",
       "\n",
       "        kilojoules  ...  vse_distance  vse_elapsed_time  vse_max_heartrate  \\\n",
       "count  1697.000000  ...   1697.000000       1697.000000        1697.000000   \n",
       "mean    875.935887  ...   3640.712434        714.414260         141.825575   \n",
       "std     111.505645  ...   4110.950159        883.981422          13.666478   \n",
       "min     368.800000  ...    166.600000         30.000000          68.000000   \n",
       "25%     829.100000  ...    995.400000        162.000000         134.000000   \n",
       "50%     889.800000  ...   2664.400000        479.000000         144.000000   \n",
       "75%     960.800000  ...   5078.600000        935.000000         152.000000   \n",
       "max    1060.600000  ...  22479.900000       5028.000000         173.000000   \n",
       "\n",
       "       vse_moving_time  vse_elevation_high  vse_elevation_low  \\\n",
       "count      1697.000000         1697.000000        1697.000000   \n",
       "mean        636.748969           11.244255           0.220153   \n",
       "std         717.683239            7.004403           4.218716   \n",
       "min          30.000000           -3.200000          -8.800000   \n",
       "25%         162.000000            7.600000          -2.900000   \n",
       "50%         464.000000            9.800000          -0.400000   \n",
       "75%         899.000000           16.400000           2.000000   \n",
       "max        4345.000000           43.400000          31.200000   \n",
       "\n",
       "       vse_start_latitude  vse_start_longitude  vse_end_latitude  \\\n",
       "count         1697.000000          1697.000000       1697.000000   \n",
       "mean           -20.419028           -40.324213        -20.421825   \n",
       "std              0.045122             0.022400          0.045907   \n",
       "min            -20.486974           -40.360662        -20.486917   \n",
       "25%            -20.456570           -40.340167        -20.454327   \n",
       "50%            -20.427257           -40.329905        -20.438855   \n",
       "75%            -20.393521           -40.317364        -20.396368   \n",
       "max            -20.321809           -40.268613        -20.321643   \n",
       "\n",
       "       vse_end_longitude  \n",
       "count        1697.000000  \n",
       "mean          -40.325318  \n",
       "std             0.023047  \n",
       "min           -40.360624  \n",
       "25%           -40.337981  \n",
       "50%           -40.332232  \n",
       "75%           -40.319373  \n",
       "max           -40.268728  \n",
       "\n",
       "[8 rows x 28 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math \n",
    "\n",
    "def calculate_initial_compass_bearing(pointA, pointB):\n",
    "    \"\"\"\n",
    "    Calculates the bearing between two points.\n",
    "    The formulae used is the following:\n",
    "        θ = atan2(sin(Δlong).cos(lat2),\n",
    "                  cos(lat1).sin(lat2) − sin(lat1).cos(lat2).cos(Δlong))\n",
    "    :Parameters:\n",
    "      - `pointA: The tuple representing the latitude/longitude for the\n",
    "        first point. Latitude and longitude must be in decimal degrees\n",
    "      - `pointB: The tuple representing the latitude/longitude for the\n",
    "        second point. Latitude and longitude must be in decimal degrees\n",
    "    :Returns:\n",
    "      The bearing in degrees\n",
    "    :Returns Type:\n",
    "      float\n",
    "    \"\"\"\n",
    "    if (type(pointA) != tuple) or (type(pointB) != tuple):\n",
    "        raise TypeError(\"Only tuples are supported as arguments\")\n",
    "\n",
    "    lat1 = math.radians(pointA[0])\n",
    "    lat2 = math.radians(pointB[0])\n",
    "\n",
    "    diffLong = math.radians(pointB[1] - pointA[1])\n",
    "\n",
    "    x = math.sin(diffLong) * math.cos(lat2)\n",
    "    y = math.cos(lat1) * math.sin(lat2) - (math.sin(lat1)\n",
    "            * math.cos(lat2) * math.cos(diffLong))\n",
    "\n",
    "    initial_bearing = math.atan2(x, y)\n",
    "\n",
    "    # Now we have the initial bearing but math.atan2 return values\n",
    "    # from -180° to + 180° which is not what we want for a compass bearing\n",
    "    # The solution is to normalize the initial bearing as shown below\n",
    "    initial_bearing = math.degrees(initial_bearing)\n",
    "    compass_bearing = (initial_bearing + 360) % 360\n",
    "\n",
    "    return compass_bearing\n",
    "\n",
    "\n",
    "# Determinando angulo do vento em função doa lat e long\n",
    "\n",
    "df['angulo_vento_segmento'] = df.apply(lambda x: calculate_initial_compass_bearing( (x['vse_start_latitude'],x['vse_start_longitude']), (x['vse_end_latitude'],x['vse_end_longitude']) ), axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def conv_dir_vento(gdirvento):\n",
    "    pt = \"\"\n",
    "    if gdirvento >= 0 and gdirvento < 22.5:\n",
    "        pt = 'N'\n",
    "    elif gdirvento >= 22.5 and gdirvento < 67.5:\n",
    "        pt = 'NE'\n",
    "    elif gdirvento >= 67.5 and gdirvento < 112.5:\n",
    "        pt = 'E'\n",
    "    elif gdirvento >= 112.5 and gdirvento < 157.5:\n",
    "        pt = 'SE'\n",
    "    elif gdirvento >= 157.5 and gdirvento < 202.5:\n",
    "        pt = 'S'\n",
    "    elif gdirvento >= 202.5 and gdirvento < 247.5:\n",
    "        pt = 'SW'\n",
    "    elif gdirvento >= 247.5 and gdirvento < 292.5:\n",
    "        pt = 'W'\n",
    "    elif gdirvento >= 292.5 and gdirvento < 337.5:\n",
    "        pt = 'NW'\n",
    "    elif gdirvento >= 337.5:\n",
    "        pt = 'N'\n",
    "        \n",
    "    return pt\n",
    "\n",
    "# Determinando a direção do vento do segmento em função do angulo\n",
    "\n",
    "df['direcao_do_vento_segmento'] = df['angulo_vento_segmento'].apply(lambda x: conv_dir_vento(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert kj para calorias\n",
    "# https://stagescycling.com/de/news/what-it-means-watts-to-kjs-to-kcals/\n",
    "\n",
    "df['burn_calories'] = ((df['kilojoules'] / 4.186) / 0.22)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x114ef828308>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Explorando a distribuição da direção dos ventos nos segmentos\n",
    "\n",
    "df.groupby(df['direcao_do_vento_segmento'])['id'].count().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removendo colunas desnecessárias \n",
    "\n",
    "df = df.drop(['id', 'name', 'kudos_count', 'vse_name', 'vse_id', 'vse_split_segmento', 'angulo_vento_segmento', 'type', 'distance','moving_time','elapsed_time','total_elevation_gain','start_date_local','max_speed','average_watts','kilojoules','average_heartrate','max_heartrate','elev_high','elev_low', 'vse_start_latitude','vse_start_longitude','vse_end_latitude','vse_end_longitude'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x114ef64a808>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1260x1260 with 56 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Explorando rapidamente a distribuição e tendencias de vários dados dos segmentos sem levar \n",
    "# em conta a direção do segmento vs a direção do vento, mas o mais importante neste momemtno \n",
    "# é entender os dados para gerar insignts\n",
    "\n",
    "sns.pairplot(df[['vse_average_heartrate','burn_calories', 'vse_average_watts', 'vse_distance', 'vse_elapsed_time', 'vse_max_heartrate', 'vse_moving_time']], kind='reg', plot_kws={'line_kws':{'color':'red'}})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# nota: as variaveis vse_distance, vse_elapsed_time e vse_moving_time tem um comportamento \n",
    "# tendencional similar quando comparado as demais variaveis\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>start_date</th>\n",
       "      <th>average_speed</th>\n",
       "      <th>vse_average_heartrate</th>\n",
       "      <th>vse_average_watts</th>\n",
       "      <th>vse_distance</th>\n",
       "      <th>vse_elapsed_time</th>\n",
       "      <th>vse_max_heartrate</th>\n",
       "      <th>vse_moving_time</th>\n",
       "      <th>vse_elevation_high</th>\n",
       "      <th>vse_elevation_low</th>\n",
       "      <th>direcao_do_vento_segmento</th>\n",
       "      <th>burn_calories</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1737</td>\n",
       "      <td>2017-11-19</td>\n",
       "      <td>3.993</td>\n",
       "      <td>106.4</td>\n",
       "      <td>139.0</td>\n",
       "      <td>3126.6</td>\n",
       "      <td>1150.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>752.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>SW</td>\n",
       "      <td>678.234809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1738</td>\n",
       "      <td>2017-11-19</td>\n",
       "      <td>3.993</td>\n",
       "      <td>107.9</td>\n",
       "      <td>125.5</td>\n",
       "      <td>6510.7</td>\n",
       "      <td>1648.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>1568.0</td>\n",
       "      <td>22.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>SW</td>\n",
       "      <td>678.234809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1739</td>\n",
       "      <td>2017-11-19</td>\n",
       "      <td>3.993</td>\n",
       "      <td>106.3</td>\n",
       "      <td>127.3</td>\n",
       "      <td>651.1</td>\n",
       "      <td>158.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>158.0</td>\n",
       "      <td>15.1</td>\n",
       "      <td>7.1</td>\n",
       "      <td>SW</td>\n",
       "      <td>678.234809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1740</td>\n",
       "      <td>2017-11-19</td>\n",
       "      <td>3.993</td>\n",
       "      <td>105.5</td>\n",
       "      <td>126.0</td>\n",
       "      <td>197.6</td>\n",
       "      <td>45.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>S</td>\n",
       "      <td>678.234809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1741</td>\n",
       "      <td>2017-11-19</td>\n",
       "      <td>3.993</td>\n",
       "      <td>109.9</td>\n",
       "      <td>108.0</td>\n",
       "      <td>2238.7</td>\n",
       "      <td>631.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>551.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>SW</td>\n",
       "      <td>678.234809</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     start_date  average_speed  vse_average_heartrate  vse_average_watts  \\\n",
       "1737 2017-11-19          3.993                  106.4              139.0   \n",
       "1738 2017-11-19          3.993                  107.9              125.5   \n",
       "1739 2017-11-19          3.993                  106.3              127.3   \n",
       "1740 2017-11-19          3.993                  105.5              126.0   \n",
       "1741 2017-11-19          3.993                  109.9              108.0   \n",
       "\n",
       "      vse_distance  vse_elapsed_time  vse_max_heartrate  vse_moving_time  \\\n",
       "1737        3126.6            1150.0              113.0            752.0   \n",
       "1738        6510.7            1648.0              116.0           1568.0   \n",
       "1739         651.1             158.0              111.0            158.0   \n",
       "1740         197.6              45.0              110.0             45.0   \n",
       "1741        2238.7             631.0              116.0            551.0   \n",
       "\n",
       "      vse_elevation_high  vse_elevation_low direcao_do_vento_segmento  \\\n",
       "1737                22.0                0.0                        SW   \n",
       "1738                22.8                0.0                        SW   \n",
       "1739                15.1                7.1                        SW   \n",
       "1740                 4.7                0.0                         S   \n",
       "1741                16.0                0.0                        SW   \n",
       "\n",
       "      burn_calories  \n",
       "1737     678.234809  \n",
       "1738     678.234809  \n",
       "1739     678.234809  \n",
       "1740     678.234809  \n",
       "1741     678.234809  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IMPORTANDO E TRATANDO DADOS ATMOSFÉRICOS / VENTOS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fonte: http://www.rodosol.com.br/_util/anemometro/index.html\n",
    "\n",
    "dfm = pd.read_csv(\"previsao_meteorologica.csv\", encoding='utf-8', delimiter=';', parse_dates=[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfm = dfm.drop('Unnamed: 6', axis=1)\n",
    "dfm = dfm[dfm['velocidade_atual_kmh_vento'] != '??']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfm['data_vento'] = pd.to_datetime(dfm['data_vento'], format='%Y%m%d', utc=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "data_vento                     datetime64[ns]\n",
       "time_vento                             object\n",
       "velocidade_atual_kmh_vento             object\n",
       "velocidade_minima_kmh_vento            object\n",
       "velocidade_maxima_kmh_vento            object\n",
       "grau_direcao_atual_vento               object\n",
       "dtype: object"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfm.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfm['velocidade_minima_kmh_vento'] = dfm['velocidade_minima_kmh_vento'].astype('float')\n",
    "dfm['velocidade_maxima_kmh_vento'] = dfm['velocidade_maxima_kmh_vento'].astype('float')\n",
    "dfm['grau_direcao_atual_vento'] = dfm['grau_direcao_atual_vento'].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfm = dfm[dfm['velocidade_minima_kmh_vento'] > 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>velocidade_minima_kmh_vento</th>\n",
       "      <th>velocidade_maxima_kmh_vento</th>\n",
       "      <th>grau_direcao_atual_vento</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>524261.000000</td>\n",
       "      <td>524261.000000</td>\n",
       "      <td>524261.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>13.426243</td>\n",
       "      <td>31.896178</td>\n",
       "      <td>129.439945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>10.916279</td>\n",
       "      <td>13.102978</td>\n",
       "      <td>118.705298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>1.050000</td>\n",
       "      <td>2.630000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>4.410000</td>\n",
       "      <td>22.090000</td>\n",
       "      <td>28.840000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>10.810000</td>\n",
       "      <td>29.970000</td>\n",
       "      <td>78.510000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>19.130000</td>\n",
       "      <td>39.790000</td>\n",
       "      <td>198.580000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>58.890000</td>\n",
       "      <td>90.430000</td>\n",
       "      <td>359.900000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       velocidade_minima_kmh_vento  velocidade_maxima_kmh_vento  \\\n",
       "count                524261.000000                524261.000000   \n",
       "mean                     13.426243                    31.896178   \n",
       "std                      10.916279                    13.102978   \n",
       "min                       1.050000                     2.630000   \n",
       "25%                       4.410000                    22.090000   \n",
       "50%                      10.810000                    29.970000   \n",
       "75%                      19.130000                    39.790000   \n",
       "max                      58.890000                    90.430000   \n",
       "\n",
       "       grau_direcao_atual_vento  \n",
       "count             524261.000000  \n",
       "mean                 129.439945  \n",
       "std                  118.705298  \n",
       "min                    0.000000  \n",
       "25%                   28.840000  \n",
       "50%                   78.510000  \n",
       "75%                  198.580000  \n",
       "max                  359.900000  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfm.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Criando um novo DS baseado no agrupamento dos dados do tempo por data e trazendo para a média as variáveis de interesse\n",
    "\n",
    "dfmG = dfm.groupby(dfm['data_vento']).agg({'velocidade_minima_kmh_vento': 'mean',\n",
    "                                     'velocidade_maxima_kmh_vento': 'mean',\n",
    "                                     'grau_direcao_atual_vento':'mean'}).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define a rosa dos ventos em função do grau \n",
    "\n",
    "def conv_dir_vento(gdirvento):\n",
    "    pt = \"\"\n",
    "    if gdirvento >= 0 and gdirvento < 22.5:\n",
    "        pt = 'N'\n",
    "    elif gdirvento >= 22.5 and gdirvento < 67.5:\n",
    "        pt = 'NE'\n",
    "    elif gdirvento >= 67.5 and gdirvento < 112.5:\n",
    "        pt = 'E'\n",
    "    elif gdirvento >= 112.5 and gdirvento < 157.5:\n",
    "        pt = 'SE'\n",
    "    elif gdirvento >= 157.5 and gdirvento < 202.5:\n",
    "        pt = 'S'\n",
    "    elif gdirvento >= 202.5 and gdirvento < 247.5:\n",
    "        pt = 'SW'\n",
    "    elif gdirvento >= 247.5 and gdirvento < 292.5:\n",
    "        pt = 'W'\n",
    "    elif gdirvento >= 292.5 and gdirvento < 337.5:\n",
    "        pt = 'NW'\n",
    "    elif gdirvento >= 337.5:\n",
    "        pt = 'N'\n",
    "        \n",
    "    return pt\n",
    "       \n",
    "\n",
    "dfmG['direcao_do_vento_biruta'] = dfmG['grau_direcao_atual_vento'].apply(lambda x:conv_dir_vento(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfmG['velocidade_media_vento'] = dfmG[['velocidade_maxima_kmh_vento','velocidade_minima_kmh_vento']].mean(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def conv_escala_vento(kmvento):\n",
    "    ept = ''\n",
    "    if kmvento < 1:\n",
    "        ept = '0'\n",
    "    elif kmvento > 1 and kmvento <= 5:\n",
    "        ept = '1'\n",
    "    elif kmvento > 5 and kmvento <= 11:\n",
    "        ept = '2'\n",
    "    elif kmvento > 11 and kmvento <= 19:\n",
    "        ept = '3'\n",
    "    elif kmvento > 10 and kmvento <= 28:\n",
    "        ept = '4'\n",
    "    elif kmvento > 28 and kmvento <= 38:\n",
    "        ept = '5'\n",
    "    elif kmvento > 38 and kmvento <= 49:\n",
    "        ept = '6'\n",
    "    elif kmvento > 49 and kmvento <= 61:\n",
    "        ept = '7'\n",
    "    elif kmvento > 61 and kmvento <= 74:\n",
    "        ept = '8'\n",
    "    elif kmvento > 74 and kmvento <= 88:\n",
    "        ept = '9'\n",
    "    elif kmvento > 88 and kmvento <= 102:\n",
    "        ept = '10'\n",
    "    elif kmvento > 102 and kmvento <= 117:\n",
    "        ept = '11'\n",
    "    elif kmvento > 117:\n",
    "        ept = '12'\n",
    "        \n",
    "    return ept\n",
    "\n",
    "# Definindo a escala Beaufort ( pode ser interessante no futuro)\n",
    "\n",
    "dfmG['escala_baufort_vento'] = dfmG['velocidade_media_vento'].apply(lambda x: conv_escala_vento(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>velocidade_minima_kmh_vento</th>\n",
       "      <th>velocidade_maxima_kmh_vento</th>\n",
       "      <th>grau_direcao_atual_vento</th>\n",
       "      <th>velocidade_media_vento</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>1043.000000</td>\n",
       "      <td>1043.000000</td>\n",
       "      <td>1043.000000</td>\n",
       "      <td>1043.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>11.511352</td>\n",
       "      <td>29.745883</td>\n",
       "      <td>137.333252</td>\n",
       "      <td>20.628617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>6.785435</td>\n",
       "      <td>8.784347</td>\n",
       "      <td>47.582799</td>\n",
       "      <td>6.998883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>1.624500</td>\n",
       "      <td>11.087097</td>\n",
       "      <td>24.795000</td>\n",
       "      <td>6.647688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>4.803239</td>\n",
       "      <td>22.678289</td>\n",
       "      <td>98.600927</td>\n",
       "      <td>15.040087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>10.963210</td>\n",
       "      <td>28.845367</td>\n",
       "      <td>134.879067</td>\n",
       "      <td>19.569707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>17.462018</td>\n",
       "      <td>36.231421</td>\n",
       "      <td>180.939871</td>\n",
       "      <td>25.682382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>28.639900</td>\n",
       "      <td>58.666724</td>\n",
       "      <td>331.537185</td>\n",
       "      <td>43.653312</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       velocidade_minima_kmh_vento  velocidade_maxima_kmh_vento  \\\n",
       "count                  1043.000000                  1043.000000   \n",
       "mean                     11.511352                    29.745883   \n",
       "std                       6.785435                     8.784347   \n",
       "min                       1.624500                    11.087097   \n",
       "25%                       4.803239                    22.678289   \n",
       "50%                      10.963210                    28.845367   \n",
       "75%                      17.462018                    36.231421   \n",
       "max                      28.639900                    58.666724   \n",
       "\n",
       "       grau_direcao_atual_vento  velocidade_media_vento  \n",
       "count               1043.000000             1043.000000  \n",
       "mean                 137.333252               20.628617  \n",
       "std                   47.582799                6.998883  \n",
       "min                   24.795000                6.647688  \n",
       "25%                   98.600927               15.040087  \n",
       "50%                  134.879067               19.569707  \n",
       "75%                  180.939871               25.682382  \n",
       "max                  331.537185               43.653312  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfmG.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x114ee633a88>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Explorando a predominancia da direção dos ventos da biruta (anemometro)\n",
    "\n",
    "dfmG.groupby(dfmG['direcao_do_vento_biruta'])['velocidade_media_vento'].mean().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x00000114F84D8CC8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x00000114F374D088>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x00000114F84E8788>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x00000114F6F88248>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Explorando a distribuição alguns dados da biruta\n",
    "\n",
    "dfmG[['velocidade_minima_kmh_vento', 'velocidade_maxima_kmh_vento', 'velocidade_media_vento']].hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MERGE ENTRE O DS DE SEGMENTOS DO STRAVA E DE VENTOS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfG = pd.merge(df, dfmG, left_on='start_date', right_on='data_vento')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>average_speed</th>\n",
       "      <th>vse_average_heartrate</th>\n",
       "      <th>vse_average_watts</th>\n",
       "      <th>vse_distance</th>\n",
       "      <th>vse_elapsed_time</th>\n",
       "      <th>vse_max_heartrate</th>\n",
       "      <th>vse_moving_time</th>\n",
       "      <th>vse_elevation_high</th>\n",
       "      <th>vse_elevation_low</th>\n",
       "      <th>burn_calories</th>\n",
       "      <th>velocidade_minima_kmh_vento</th>\n",
       "      <th>velocidade_maxima_kmh_vento</th>\n",
       "      <th>grau_direcao_atual_vento</th>\n",
       "      <th>velocidade_media_vento</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>1666.000000</td>\n",
       "      <td>1666.000000</td>\n",
       "      <td>1666.000000</td>\n",
       "      <td>1666.000000</td>\n",
       "      <td>1666.000000</td>\n",
       "      <td>1666.000000</td>\n",
       "      <td>1666.000000</td>\n",
       "      <td>1666.000000</td>\n",
       "      <td>1666.000000</td>\n",
       "      <td>1666.000000</td>\n",
       "      <td>1666.000000</td>\n",
       "      <td>1666.000000</td>\n",
       "      <td>1666.000000</td>\n",
       "      <td>1666.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>5.207344</td>\n",
       "      <td>131.801200</td>\n",
       "      <td>180.261405</td>\n",
       "      <td>3652.779652</td>\n",
       "      <td>718.091236</td>\n",
       "      <td>141.692677</td>\n",
       "      <td>639.357743</td>\n",
       "      <td>11.267647</td>\n",
       "      <td>0.227611</td>\n",
       "      <td>949.438369</td>\n",
       "      <td>14.007845</td>\n",
       "      <td>30.487358</td>\n",
       "      <td>119.909352</td>\n",
       "      <td>22.247601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>0.495258</td>\n",
       "      <td>13.529626</td>\n",
       "      <td>35.749873</td>\n",
       "      <td>4136.893154</td>\n",
       "      <td>889.812058</td>\n",
       "      <td>13.696861</td>\n",
       "      <td>722.281791</td>\n",
       "      <td>7.017325</td>\n",
       "      <td>4.222088</td>\n",
       "      <td>121.541957</td>\n",
       "      <td>6.291035</td>\n",
       "      <td>8.452482</td>\n",
       "      <td>47.015990</td>\n",
       "      <td>6.951614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>3.728000</td>\n",
       "      <td>67.700000</td>\n",
       "      <td>18.500000</td>\n",
       "      <td>166.600000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>-3.200000</td>\n",
       "      <td>-8.800000</td>\n",
       "      <td>400.469096</td>\n",
       "      <td>3.262412</td>\n",
       "      <td>13.813793</td>\n",
       "      <td>39.234750</td>\n",
       "      <td>8.591034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>5.078000</td>\n",
       "      <td>124.025000</td>\n",
       "      <td>159.825000</td>\n",
       "      <td>995.325000</td>\n",
       "      <td>162.000000</td>\n",
       "      <td>134.000000</td>\n",
       "      <td>162.000000</td>\n",
       "      <td>7.600000</td>\n",
       "      <td>-2.900000</td>\n",
       "      <td>900.295357</td>\n",
       "      <td>8.525996</td>\n",
       "      <td>23.601043</td>\n",
       "      <td>81.574457</td>\n",
       "      <td>17.154261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>5.388000</td>\n",
       "      <td>134.100000</td>\n",
       "      <td>183.600000</td>\n",
       "      <td>2664.150000</td>\n",
       "      <td>480.000000</td>\n",
       "      <td>144.000000</td>\n",
       "      <td>466.500000</td>\n",
       "      <td>9.800000</td>\n",
       "      <td>-0.400000</td>\n",
       "      <td>966.207705</td>\n",
       "      <td>15.197530</td>\n",
       "      <td>31.041186</td>\n",
       "      <td>115.224889</td>\n",
       "      <td>21.972383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>5.555000</td>\n",
       "      <td>141.800000</td>\n",
       "      <td>201.175000</td>\n",
       "      <td>5079.650000</td>\n",
       "      <td>940.750000</td>\n",
       "      <td>151.750000</td>\n",
       "      <td>906.750000</td>\n",
       "      <td>16.400000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1034.617556</td>\n",
       "      <td>19.195347</td>\n",
       "      <td>37.016748</td>\n",
       "      <td>149.338448</td>\n",
       "      <td>28.188496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>5.791000</td>\n",
       "      <td>159.400000</td>\n",
       "      <td>325.500000</td>\n",
       "      <td>22479.900000</td>\n",
       "      <td>5028.000000</td>\n",
       "      <td>173.000000</td>\n",
       "      <td>4345.000000</td>\n",
       "      <td>43.400000</td>\n",
       "      <td>31.200000</td>\n",
       "      <td>1151.674413</td>\n",
       "      <td>25.990889</td>\n",
       "      <td>49.309806</td>\n",
       "      <td>235.880624</td>\n",
       "      <td>37.650347</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       average_speed  vse_average_heartrate  vse_average_watts  vse_distance  \\\n",
       "count    1666.000000            1666.000000        1666.000000   1666.000000   \n",
       "mean        5.207344             131.801200         180.261405   3652.779652   \n",
       "std         0.495258              13.529626          35.749873   4136.893154   \n",
       "min         3.728000              67.700000          18.500000    166.600000   \n",
       "25%         5.078000             124.025000         159.825000    995.325000   \n",
       "50%         5.388000             134.100000         183.600000   2664.150000   \n",
       "75%         5.555000             141.800000         201.175000   5079.650000   \n",
       "max         5.791000             159.400000         325.500000  22479.900000   \n",
       "\n",
       "       vse_elapsed_time  vse_max_heartrate  vse_moving_time  \\\n",
       "count       1666.000000        1666.000000      1666.000000   \n",
       "mean         718.091236         141.692677       639.357743   \n",
       "std          889.812058          13.696861       722.281791   \n",
       "min           30.000000          68.000000        30.000000   \n",
       "25%          162.000000         134.000000       162.000000   \n",
       "50%          480.000000         144.000000       466.500000   \n",
       "75%          940.750000         151.750000       906.750000   \n",
       "max         5028.000000         173.000000      4345.000000   \n",
       "\n",
       "       vse_elevation_high  vse_elevation_low  burn_calories  \\\n",
       "count         1666.000000        1666.000000    1666.000000   \n",
       "mean            11.267647           0.227611     949.438369   \n",
       "std              7.017325           4.222088     121.541957   \n",
       "min             -3.200000          -8.800000     400.469096   \n",
       "25%              7.600000          -2.900000     900.295357   \n",
       "50%              9.800000          -0.400000     966.207705   \n",
       "75%             16.400000           2.000000    1034.617556   \n",
       "max             43.400000          31.200000    1151.674413   \n",
       "\n",
       "       velocidade_minima_kmh_vento  velocidade_maxima_kmh_vento  \\\n",
       "count                  1666.000000                  1666.000000   \n",
       "mean                     14.007845                    30.487358   \n",
       "std                       6.291035                     8.452482   \n",
       "min                       3.262412                    13.813793   \n",
       "25%                       8.525996                    23.601043   \n",
       "50%                      15.197530                    31.041186   \n",
       "75%                      19.195347                    37.016748   \n",
       "max                      25.990889                    49.309806   \n",
       "\n",
       "       grau_direcao_atual_vento  velocidade_media_vento  \n",
       "count               1666.000000             1666.000000  \n",
       "mean                 119.909352               22.247601  \n",
       "std                   47.015990                6.951614  \n",
       "min                   39.234750                8.591034  \n",
       "25%                   81.574457               17.154261  \n",
       "50%                  115.224889               21.972383  \n",
       "75%                  149.338448               28.188496  \n",
       "max                  235.880624               37.650347  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfG.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Definindo a adversidade dos ventos da burita em função do segmento, por questões de prticidade estabeleci apenas\n",
    "# a adversidade do Norte para o Sul e do Sul para o Norte\n",
    "\n",
    "# 0 - Biruta para o Norte e segmento para o Sul\n",
    "# 1 - Biruta para o Sul e segmento para o Norte\n",
    "# NaN - Biuruta e segmento apontam para a mesma direção\n",
    "\n",
    "def define_adverso(vBiruta, vSegmeto):\n",
    "    if (vBiruta == 'NE' or vBiruta == 'N' or vBiruta == 'NW') and (vSegmeto == 'S' or vSegmeto == 'SE' or vSegmeto == 'SW'):\n",
    "        return 0\n",
    "    elif (vBiruta == 'SE' or vBiruta == 'S' or  vBiruta == 'SW') and (vSegmeto == 'NE' or vSegmeto == 'N' or vSegmeto == 'SW' or vSegmeto == 'NW'):\n",
    "        return 1\n",
    "    else:\n",
    "        return 'NaN'\n",
    "    \n",
    "    \n",
    "dfG['vento_adverso'] = dfG.apply(lambda x: define_adverso(x.direcao_do_vento_biruta, x.direcao_do_vento_segmento), axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">average_speed</th>\n",
       "      <th colspan=\"2\" halign=\"left\">vse_average_heartrate</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">grau_direcao_atual_vento</th>\n",
       "      <th colspan=\"8\" halign=\"left\">velocidade_media_vento</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>...</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vento_adverso</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>5.377662</td>\n",
       "      <td>0.299938</td>\n",
       "      <td>4.281</td>\n",
       "      <td>5.283</td>\n",
       "      <td>5.422</td>\n",
       "      <td>5.524</td>\n",
       "      <td>5.675</td>\n",
       "      <td>136.0</td>\n",
       "      <td>130.255147</td>\n",
       "      <td>...</td>\n",
       "      <td>55.653985</td>\n",
       "      <td>59.959199</td>\n",
       "      <td>136.0</td>\n",
       "      <td>29.234902</td>\n",
       "      <td>4.302166</td>\n",
       "      <td>22.555513</td>\n",
       "      <td>27.531100</td>\n",
       "      <td>28.565487</td>\n",
       "      <td>34.069791</td>\n",
       "      <td>36.269736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>599.0</td>\n",
       "      <td>5.139873</td>\n",
       "      <td>0.535510</td>\n",
       "      <td>3.733</td>\n",
       "      <td>4.877</td>\n",
       "      <td>5.388</td>\n",
       "      <td>5.567</td>\n",
       "      <td>5.791</td>\n",
       "      <td>599.0</td>\n",
       "      <td>131.896828</td>\n",
       "      <td>...</td>\n",
       "      <td>185.824243</td>\n",
       "      <td>235.880624</td>\n",
       "      <td>599.0</td>\n",
       "      <td>19.690552</td>\n",
       "      <td>6.135449</td>\n",
       "      <td>8.591034</td>\n",
       "      <td>14.683796</td>\n",
       "      <td>19.466805</td>\n",
       "      <td>22.974577</td>\n",
       "      <td>37.650347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NaN</td>\n",
       "      <td>931.0</td>\n",
       "      <td>5.225874</td>\n",
       "      <td>0.483899</td>\n",
       "      <td>3.728</td>\n",
       "      <td>5.120</td>\n",
       "      <td>5.388</td>\n",
       "      <td>5.555</td>\n",
       "      <td>5.791</td>\n",
       "      <td>931.0</td>\n",
       "      <td>131.965521</td>\n",
       "      <td>...</td>\n",
       "      <td>127.739718</td>\n",
       "      <td>235.880624</td>\n",
       "      <td>931.0</td>\n",
       "      <td>22.872090</td>\n",
       "      <td>6.919811</td>\n",
       "      <td>8.591034</td>\n",
       "      <td>17.557656</td>\n",
       "      <td>23.062811</td>\n",
       "      <td>28.188496</td>\n",
       "      <td>37.650347</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 112 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              average_speed                                                  \\\n",
       "                      count      mean       std    min    25%    50%    75%   \n",
       "vento_adverso                                                                 \n",
       "0                     136.0  5.377662  0.299938  4.281  5.283  5.422  5.524   \n",
       "1                     599.0  5.139873  0.535510  3.733  4.877  5.388  5.567   \n",
       "NaN                   931.0  5.225874  0.483899  3.728  5.120  5.388  5.555   \n",
       "\n",
       "                     vse_average_heartrate              ...  \\\n",
       "                 max                 count        mean  ...   \n",
       "vento_adverso                                           ...   \n",
       "0              5.675                 136.0  130.255147  ...   \n",
       "1              5.791                 599.0  131.896828  ...   \n",
       "NaN            5.791                 931.0  131.965521  ...   \n",
       "\n",
       "              grau_direcao_atual_vento             velocidade_media_vento  \\\n",
       "                                   75%         max                  count   \n",
       "vento_adverso                                                               \n",
       "0                            55.653985   59.959199                  136.0   \n",
       "1                           185.824243  235.880624                  599.0   \n",
       "NaN                         127.739718  235.880624                  931.0   \n",
       "\n",
       "                                                                     \\\n",
       "                    mean       std        min        25%        50%   \n",
       "vento_adverso                                                         \n",
       "0              29.234902  4.302166  22.555513  27.531100  28.565487   \n",
       "1              19.690552  6.135449   8.591034  14.683796  19.466805   \n",
       "NaN            22.872090  6.919811   8.591034  17.557656  23.062811   \n",
       "\n",
       "                                     \n",
       "                     75%        max  \n",
       "vento_adverso                        \n",
       "0              34.069791  36.269736  \n",
       "1              22.974577  37.650347  \n",
       "NaN            28.188496  37.650347  \n",
       "\n",
       "[3 rows x 112 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfG.groupby('vento_adverso').describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removendo os dados cujo os segmentos e direção dos ventos seja igual\n",
    "\n",
    "dfG = dfG[dfG['vento_adverso'] != 'NaN']\n",
    "dfG['vento_adverso'] = dfG['vento_adverso'].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(735, 20)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfG.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# agrupando por data, apenas as variaveis alvo para a correlação\n",
    "\n",
    "dfG2 = dfG.groupby(dfG['start_date']).agg({'vse_average_heartrate':'mean',\n",
    "                'vse_average_watts':'mean',\n",
    "                'vse_distance':'mean',\n",
    "                'vse_elapsed_time' : 'mean',\n",
    "                'vse_max_heartrate':'mean',\n",
    "                'vse_moving_time' : 'mean',\n",
    "                'velocidade_media_vento' : 'mean',\n",
    "                'average_speed':'mean'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(42, 8)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfG2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vse_average_heartrate</th>\n",
       "      <th>vse_average_watts</th>\n",
       "      <th>vse_distance</th>\n",
       "      <th>vse_elapsed_time</th>\n",
       "      <th>vse_max_heartrate</th>\n",
       "      <th>vse_moving_time</th>\n",
       "      <th>velocidade_media_vento</th>\n",
       "      <th>average_speed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>42.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>129.592704</td>\n",
       "      <td>182.668643</td>\n",
       "      <td>3058.439738</td>\n",
       "      <td>611.429772</td>\n",
       "      <td>139.283935</td>\n",
       "      <td>546.886457</td>\n",
       "      <td>21.829827</td>\n",
       "      <td>5.096024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>13.740838</td>\n",
       "      <td>20.873538</td>\n",
       "      <td>1320.308745</td>\n",
       "      <td>246.886623</td>\n",
       "      <td>12.439718</td>\n",
       "      <td>209.577073</td>\n",
       "      <td>7.133907</td>\n",
       "      <td>0.570674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>97.331250</td>\n",
       "      <td>126.837500</td>\n",
       "      <td>1663.233333</td>\n",
       "      <td>323.238095</td>\n",
       "      <td>105.583333</td>\n",
       "      <td>323.238095</td>\n",
       "      <td>8.591034</td>\n",
       "      <td>3.733000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>121.722500</td>\n",
       "      <td>168.250000</td>\n",
       "      <td>2256.848958</td>\n",
       "      <td>471.965909</td>\n",
       "      <td>129.783333</td>\n",
       "      <td>438.600758</td>\n",
       "      <td>15.335847</td>\n",
       "      <td>4.655250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>131.826389</td>\n",
       "      <td>185.920455</td>\n",
       "      <td>2604.992727</td>\n",
       "      <td>560.977273</td>\n",
       "      <td>142.449495</td>\n",
       "      <td>499.161818</td>\n",
       "      <td>21.932109</td>\n",
       "      <td>5.335500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>139.674574</td>\n",
       "      <td>196.348438</td>\n",
       "      <td>3037.384818</td>\n",
       "      <td>623.948052</td>\n",
       "      <td>148.022727</td>\n",
       "      <td>565.505625</td>\n",
       "      <td>27.139632</td>\n",
       "      <td>5.539000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>151.737500</td>\n",
       "      <td>223.560000</td>\n",
       "      <td>6435.022222</td>\n",
       "      <td>1250.388889</td>\n",
       "      <td>159.062500</td>\n",
       "      <td>1114.555556</td>\n",
       "      <td>37.650347</td>\n",
       "      <td>5.791000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       vse_average_heartrate  vse_average_watts  vse_distance  \\\n",
       "count              42.000000          42.000000     42.000000   \n",
       "mean              129.592704         182.668643   3058.439738   \n",
       "std                13.740838          20.873538   1320.308745   \n",
       "min                97.331250         126.837500   1663.233333   \n",
       "25%               121.722500         168.250000   2256.848958   \n",
       "50%               131.826389         185.920455   2604.992727   \n",
       "75%               139.674574         196.348438   3037.384818   \n",
       "max               151.737500         223.560000   6435.022222   \n",
       "\n",
       "       vse_elapsed_time  vse_max_heartrate  vse_moving_time  \\\n",
       "count         42.000000          42.000000        42.000000   \n",
       "mean         611.429772         139.283935       546.886457   \n",
       "std          246.886623          12.439718       209.577073   \n",
       "min          323.238095         105.583333       323.238095   \n",
       "25%          471.965909         129.783333       438.600758   \n",
       "50%          560.977273         142.449495       499.161818   \n",
       "75%          623.948052         148.022727       565.505625   \n",
       "max         1250.388889         159.062500      1114.555556   \n",
       "\n",
       "       velocidade_media_vento  average_speed  \n",
       "count               42.000000      42.000000  \n",
       "mean                21.829827       5.096024  \n",
       "std                  7.133907       0.570674  \n",
       "min                  8.591034       3.733000  \n",
       "25%                 15.335847       4.655250  \n",
       "50%                 21.932109       5.335500  \n",
       "75%                 27.139632       5.539000  \n",
       "max                 37.650347       5.791000  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfG2.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col1 {\n",
       "            background-color:  #d2dbe8;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col2 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col3 {\n",
       "            background-color:  #445acc;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col4 {\n",
       "            background-color:  #c32e31;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col5 {\n",
       "            background-color:  #4055c8;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col6 {\n",
       "            background-color:  #6b8df0;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col7 {\n",
       "            background-color:  #f2c9b4;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col0 {\n",
       "            background-color:  #d3dbe7;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col1 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col2 {\n",
       "            background-color:  #b3cdfb;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col3 {\n",
       "            background-color:  #90b2fe;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col4 {\n",
       "            background-color:  #efcebd;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col5 {\n",
       "            background-color:  #93b5fe;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col7 {\n",
       "            background-color:  #f6a586;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col0 {\n",
       "            background-color:  #7a9df8;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col1 {\n",
       "            background-color:  #d8dce2;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col2 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col3 {\n",
       "            background-color:  #cc403a;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col4 {\n",
       "            background-color:  #8badfd;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col5 {\n",
       "            background-color:  #c0282f;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col6 {\n",
       "            background-color:  #dddcdc;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col7 {\n",
       "            background-color:  #aac7fd;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col1 {\n",
       "            background-color:  #84a7fc;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col2 {\n",
       "            background-color:  #d24b40;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col3 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col5 {\n",
       "            background-color:  #b8122a;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col6 {\n",
       "            background-color:  #e2dad5;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col0 {\n",
       "            background-color:  #c32e31;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col1 {\n",
       "            background-color:  #edd2c3;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col2 {\n",
       "            background-color:  #4257c9;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col3 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col4 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col6 {\n",
       "            background-color:  #5a78e4;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col7 {\n",
       "            background-color:  #f59f80;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col0 {\n",
       "            background-color:  #4f69d9;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col1 {\n",
       "            background-color:  #9ebeff;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col2 {\n",
       "            background-color:  #c32e31;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col3 {\n",
       "            background-color:  #b8122a;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col4 {\n",
       "            background-color:  #536edd;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col5 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col6 {\n",
       "            background-color:  #e4d9d2;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col7 {\n",
       "            background-color:  #5a78e4;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col0 {\n",
       "            background-color:  #6e90f2;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col1 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col2 {\n",
       "            background-color:  #bad0f8;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col3 {\n",
       "            background-color:  #e7d7ce;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col4 {\n",
       "            background-color:  #6788ee;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col5 {\n",
       "            background-color:  #dfdbd9;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col6 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col7 {\n",
       "            background-color:  #4358cb;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col0 {\n",
       "            background-color:  #f5c0a7;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col1 {\n",
       "            background-color:  #f59d7e;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col2 {\n",
       "            background-color:  #86a9fc;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col3 {\n",
       "            background-color:  #5b7ae5;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col4 {\n",
       "            background-color:  #f39475;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col5 {\n",
       "            background-color:  #6384eb;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col6 {\n",
       "            background-color:  #5977e3;\n",
       "            color:  #000000;\n",
       "        }    #T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col7 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }</style><table id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >vse_average_heartrate</th>        <th class=\"col_heading level0 col1\" >vse_average_watts</th>        <th class=\"col_heading level0 col2\" >vse_distance</th>        <th class=\"col_heading level0 col3\" >vse_elapsed_time</th>        <th class=\"col_heading level0 col4\" >vse_max_heartrate</th>        <th class=\"col_heading level0 col5\" >vse_moving_time</th>        <th class=\"col_heading level0 col6\" >velocidade_media_vento</th>        <th class=\"col_heading level0 col7\" >average_speed</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347level0_row0\" class=\"row_heading level0 row0\" >vse_average_heartrate</th>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col0\" class=\"data row0 col0\" >1</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col1\" class=\"data row0 col1\" >0.4</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col2\" class=\"data row0 col2\" >0.1</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col3\" class=\"data row0 col3\" >-0.12</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col4\" class=\"data row0 col4\" >0.95</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col5\" class=\"data row0 col5\" >-0.045</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col6\" class=\"data row0 col6\" >0.061</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row0_col7\" class=\"data row0 col7\" >0.59</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347level0_row1\" class=\"row_heading level0 row1\" >vse_average_watts</th>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col0\" class=\"data row1 col0\" >0.4</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col1\" class=\"data row1 col1\" >1</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col2\" class=\"data row1 col2\" >0.43</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col3\" class=\"data row1 col3\" >0.14</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col4\" class=\"data row1 col4\" >0.52</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col5\" class=\"data row1 col5\" >0.22</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col6\" class=\"data row1 col6\" >-0.11</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row1_col7\" class=\"data row1 col7\" >0.71</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347level0_row2\" class=\"row_heading level0 row2\" >vse_distance</th>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col0\" class=\"data row2 col0\" >0.1</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col1\" class=\"data row2 col1\" >0.43</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col2\" class=\"data row2 col2\" >1</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col3\" class=\"data row2 col3\" >0.92</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col4\" class=\"data row2 col4\" >0.12</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col5\" class=\"data row2 col5\" >0.96</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col6\" class=\"data row2 col6\" >0.45</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row2_col7\" class=\"data row2 col7\" >0.31</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347level0_row3\" class=\"row_heading level0 row3\" >vse_elapsed_time</th>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col0\" class=\"data row3 col0\" >-0.12</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col1\" class=\"data row3 col1\" >0.14</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col2\" class=\"data row3 col2\" >0.92</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col3\" class=\"data row3 col3\" >1</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col4\" class=\"data row3 col4\" >-0.16</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col5\" class=\"data row3 col5\" >0.99</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col6\" class=\"data row3 col6\" >0.47</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row3_col7\" class=\"data row3 col7\" >-0.033</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347level0_row4\" class=\"row_heading level0 row4\" >vse_max_heartrate</th>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col0\" class=\"data row4 col0\" >0.95</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col1\" class=\"data row4 col1\" >0.52</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col2\" class=\"data row4 col2\" >0.12</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col3\" class=\"data row4 col3\" >-0.16</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col4\" class=\"data row4 col4\" >1</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col5\" class=\"data row4 col5\" >-0.066</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col6\" class=\"data row4 col6\" >0.0063</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row4_col7\" class=\"data row4 col7\" >0.73</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347level0_row5\" class=\"row_heading level0 row5\" >vse_moving_time</th>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col0\" class=\"data row5 col0\" >-0.045</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col1\" class=\"data row5 col1\" >0.22</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col2\" class=\"data row5 col2\" >0.96</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col3\" class=\"data row5 col3\" >0.99</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col4\" class=\"data row5 col4\" >-0.066</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col5\" class=\"data row5 col5\" >1</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col6\" class=\"data row5 col6\" >0.48</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row5_col7\" class=\"data row5 col7\" >0.074</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347level0_row6\" class=\"row_heading level0 row6\" >velocidade_media_vento</th>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col0\" class=\"data row6 col0\" >0.061</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col1\" class=\"data row6 col1\" >-0.11</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col2\" class=\"data row6 col2\" >0.45</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col3\" class=\"data row6 col3\" >0.47</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col4\" class=\"data row6 col4\" >0.0063</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col5\" class=\"data row6 col5\" >0.48</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col6\" class=\"data row6 col6\" >1</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row6_col7\" class=\"data row6 col7\" >-0.0018</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347level0_row7\" class=\"row_heading level0 row7\" >average_speed</th>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col0\" class=\"data row7 col0\" >0.59</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col1\" class=\"data row7 col1\" >0.71</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col2\" class=\"data row7 col2\" >0.31</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col3\" class=\"data row7 col3\" >-0.033</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col4\" class=\"data row7 col4\" >0.73</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col5\" class=\"data row7 col5\" >0.074</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col6\" class=\"data row7 col6\" >-0.0018</td>\n",
       "                        <td id=\"T_bf76351c_1adf_11ea_b2e7_e454e8092347row7_col7\" class=\"data row7 col7\" >1</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x114f8b54fc8>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfG2.corr(method='pearson').style.background_gradient(cmap='coolwarm').set_precision(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x114f2d492c8>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x='vse_average_heartrate', y='velocidade_media_vento', data=dfG2)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}