MTABT_Preprocessing.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MTABT Preprocessing Step\n",
    "I will replace values that are 2 standard deviations away from the norms with null values and fill in using FBProphet."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "import holidays\n",
    "\n",
    "# For SARIMAX\n",
    "from tqdm import tqdm\n",
    "from pmdarima import auto_arima\n",
    "from statsmodels.tsa.statespace.sarimax import SARIMAX\n",
    "import statsmodels.api as sm\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.preprocessing import OneHotEncoder, LabelEncoder\n",
    "\n",
    "# For FBProphet\n",
    "from fbprophet import Prophet\n",
    "\n",
    "# For LightGBM\n",
    "import lightgbm as lgb\n",
    "from sklearn.model_selection import train_test_split\n",
    "import optuna"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "holidays_2010_2020 = []\n",
    "for year in range(2010,2022):\n",
    "    for date in holidays.UnitedStates(years=year).items():\n",
    "        holidays_2010_2020.append(date[0])\n",
    "        \n",
    "\n",
    "        \n",
    "crossing_rates = {('Brooklyn Battery', 'cash'):9.50,\n",
    "                 ('Brooklyn Battery', 'ezpass'):6.12,\n",
    "                 ('Cross Bay', 'cash'):4.75,\n",
    "                 ('Cross Bay', 'ezpass'):2.29,\n",
    "                 ('Henry Hudson','cash'):7.00,\n",
    "                 ('Henry Hudson','ezpass'):2.80,\n",
    "                 ('Marine Parkway','cash'):4.75,\n",
    "                 ('Marine Parkway','ezpass'):2.29,\n",
    "                 ('Queens Midtown','cash'):9.50,\n",
    "                 ('Queens Midtown','ezpass'):6.12,\n",
    "                 ('Throgs Neck','cash'): 9.50,\n",
    "                 ('Throgs Neck','ezpass'): 6.12,\n",
    "                 ('Triboro','cash'): 9.50,\n",
    "                 ('Triboro','ezpass'):6.12,\n",
    "                 ('Verrazano','cash'):19.00,\n",
    "                 ('Verrazano','ezpass'):12.24,\n",
    "                 ('Whitestone','cash'):9.50,\n",
    "                 ('Whitestone','ezpass'):6.12}\n",
    "\n",
    "bridges_joined = []\n",
    "for i,x in crossing_rates.keys():\n",
    "    bridges_joined.append(i + ' ' + x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mean Percentage error\n",
    "After I have fit with FBProphet, I calculate the mean percentage errors of the values that were not missing(2 std away). \n",
    "I will then multiply the predicted amounts by its error weight (1 + mean_percentage_error)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def mean_percentage_error(actual, yhat):\n",
    "    \"\"\"\n",
    "    actual, yhat: list or numpy array\n",
    "    length of listlike arrays must be same\n",
    "    \n",
    "    returns the mean percentage error\n",
    "    \"\"\"\n",
    "    # converting list to array\n",
    "    if type(actual) == 'list':\n",
    "        actual = np.array(actual)\n",
    "    if type(yhat) == 'list':\n",
    "        yhat = np.array(yhat)\n",
    "        \n",
    "        \n",
    "    _mean = (actual - yhat)/actual\n",
    "    \n",
    "    return _mean.sum()/len(_mean)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def return_series(csv_path):\n",
    "    \"\"\"\n",
    "    \n",
    "    \"\"\"\n",
    "    \n",
    "    def parse(x):\n",
    "        return datetime.datetime.strptime(x, '%m/%d/%Y %H')\n",
    "    \n",
    "    df = pd.read_csv(csv_path, parse_dates=[['Date','Hour']], date_parser=parse)\n",
    "    df = df.loc[~df.duplicated()]\n",
    "    \n",
    "    \n",
    "    conditions = [\n",
    "    df['Plaza ID'].eq(21) | df['Plaza ID'].eq(1),\n",
    "    df['Plaza ID'].eq(22) | df['Plaza ID'].eq(2),\n",
    "    df['Plaza ID'].eq(23) | df['Plaza ID'].eq(3),\n",
    "    df['Plaza ID'].eq(24) | df['Plaza ID'].eq(4),\n",
    "    df['Plaza ID'].eq(25) | df['Plaza ID'].eq(5),\n",
    "    df['Plaza ID'].eq(26) | df['Plaza ID'].eq(6),\n",
    "    df['Plaza ID'].eq(27) | df['Plaza ID'].eq(7),\n",
    "    df['Plaza ID'].eq(28) | df['Plaza ID'].eq(8),\n",
    "    df['Plaza ID'].eq(29) | df['Plaza ID'].eq(9),\n",
    "    df['Plaza ID'].eq(30) | df['Plaza ID'].eq(11)\n",
    "    ]\n",
    "    choices = [\n",
    "        'Triboro',\n",
    "        'Triboro',\n",
    "        'Whitestone',\n",
    "        'Henry Hudson',\n",
    "        'Marine Parkway',\n",
    "        'Cross Bay',\n",
    "        'Queens Midtown',\n",
    "        'Brooklyn Battery',\n",
    "        'Throgs Neck',\n",
    "        'Verrazano'\n",
    "    ]\n",
    "    df['plaza_id'] = np.select(conditions, choices, 0)\n",
    "    \n",
    "    df.rename(columns={'# Vehicles - E-ZPass': 'ezpass', '# Vehicles - VToll': 'cash', 'Date_Hour': 'datetime'}, inplace=True)\n",
    "    \n",
    "    df.drop(columns=['Plaza ID', 'Direction'], inplace=True)\n",
    "    \n",
    "    \n",
    "    _df = df.melt(id_vars=['datetime','plaza_id'], value_vars=['ezpass', 'cash'])\n",
    "    _df.set_index('datetime', inplace=True)\n",
    "    _df = _df.groupby(['plaza_id', 'variable'])['value'].resample('1D').sum()\n",
    "    \n",
    "    \n",
    "    return _df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = return_series('mta.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Unstacking dataframe to impute values that are 2 standard deviations away to be np.nan."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1ee3b748>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_df = df.unstack().T\n",
    "_df.columns = [' '.join(column).strip() for column in _df.columns.values]\n",
    "fig, ax = plt.subplots(figsize=(14,10))\n",
    "_df.plot(ax = ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "del df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature Engineering: datetime extraction\n",
    "In addition to datetime extraction, I will add holidays, post-covid phases and post cashless toll installation phases."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def date_features(_df):\n",
    "    _df['month'] = _df.index.month\n",
    "    _df['dayofweek'] = _df.index.dayofweek\n",
    "    _df['year'] = _df.index.year\n",
    "    _df['week'] = _df.index.isocalendar().week\n",
    "    _df['day'] = _df.index.day\n",
    "    _df['quarter'] = _df.index.quarter\n",
    "    _df['dayofyear'] = _df.index.dayofyear\n",
    "\n",
    "    # NYC lockdown phases\n",
    "    conditions = [\n",
    "        (_df.index >= '2020-03-12') & (_df.index < '2020-03-22'),\n",
    "        (_df.index >= '2020-03-22') & (_df.index < '2020-04-16'),\n",
    "        (_df.index >= '2020-04-16') & (_df.index < '2020-05-15'),\n",
    "        (_df.index >= '2020-05-15') & (_df.index < '2020-06-08'),\n",
    "        (_df.index >= '2020-06-08') & (_df.index < '2020-06-22'),\n",
    "        (_df.index >= '2020-06-22') & (_df.index < '2020-07-06'),\n",
    "        (_df.index >= '2020-07-06') & (_df.index < '2020-07-19'),\n",
    "        (_df.index >= '2020-07-19')\n",
    "    ]\n",
    "\n",
    "    choices = [\n",
    "        0,\n",
    "        1,\n",
    "        2,\n",
    "        3,\n",
    "        4,\n",
    "        5,\n",
    "        6,\n",
    "        7,\n",
    "    ]\n",
    "\n",
    "    _df['Phase'] = np.select(conditions, choices, -1)\n",
    "    \n",
    "    # On 2018, MTA announces their completion of cashless tolls\n",
    "    _df['Cashless'] = np.where(_df.index >= '2018-01-01', 1, 0)\n",
    "    \n",
    "    _df['weekend'] = (_df.index.dayofweek>4).astype(int)\n",
    "    _df['holiday'] = np.where(_df.index.isin(holidays_2010_2020), 1, 0)\n",
    "    return _df\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "_df = date_features(_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature Engineering: Average Temperature\n",
    "Adding average temperature calculated by FBProphet. <br>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "temperature = pd.read_csv('weather.csv', sep ='\\t', engine ='python')\n",
    "temperature['datetime'] = pd.to_datetime(temperature['datetime'])\n",
    "plt.plot(temperature['datetime'], temperature['temp_average'])\n",
    "plt.title('Average Daily Temperature for JFK, NY');\n",
    "plt.ylabel('in Farenheits');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-01</td>\n",
       "      <td>36.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-02</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-03</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-05</td>\n",
       "      <td>26.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          ds     y\n",
       "0 2010-01-01  36.5\n",
       "1 2010-01-02  25.0\n",
       "2 2010-01-03  21.0\n",
       "3 2010-01-04  26.0\n",
       "4 2010-01-05  26.5"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_temperature = date_features(temperature.set_index('datetime')[['temp_average']])\n",
    "_fb_weather = _temperature.reset_index()[['datetime', 'temp_average']]\n",
    "_fb_weather.columns = ['ds', 'y']\n",
    "_fb_weather.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x1ee237c8>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = Prophet(\n",
    "           changepoint_prior_scale= 0.1,\n",
    "                      holidays_prior_scale = 0.1,\n",
    "                      n_changepoints = 300,\n",
    "                      seasonality_mode = 'additive',\n",
    "                      weekly_seasonality=True,\n",
    "                      daily_seasonality = True,\n",
    "                      yearly_seasonality = True,\n",
    "                      interval_width=0.95)\n",
    "m.fit(_fb_weather)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "future = m.make_future_dataframe(periods = 365*2)\n",
    "forecast = m.predict(future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "sliced_forecast = forecast.loc[forecast['ds'].isin(pd.date_range(start='2010-01-01', end='2020-2-29'))]\n",
    "sliced_forecast.reset_index(drop=True, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>temp_average</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>36.372828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-02</th>\n",
       "      <td>35.877365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-03</th>\n",
       "      <td>35.874707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>35.631358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>36.069875</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temp_average\n",
       "datetime                \n",
       "2010-01-01     36.372828\n",
       "2010-01-02     35.877365\n",
       "2010-01-03     35.874707\n",
       "2010-01-04     35.631358\n",
       "2010-01-05     36.069875"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sliced_forecast = sliced_forecast[['ds', 'yhat']]\n",
    "sliced_forecast.columns = ['datetime', 'temp_average']\n",
    "sliced_forecast.set_index('datetime', inplace=True)\n",
    "sliced_forecast.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "_df['temp_average'] = sliced_forecast['temp_average']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Brooklyn Battery ezpass</th>\n",
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       "      <td>0</td>\n",
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       "      <th>2010-01-02</th>\n",
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       "      <td>3508</td>\n",
       "      <td>11673</td>\n",
       "      <td>9396</td>\n",
       "      <td>37110</td>\n",
       "      <td>3053</td>\n",
       "      <td>11552</td>\n",
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       "      <td>40597</td>\n",
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       "      <td>53</td>\n",
       "      <td>2</td>\n",
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       "      <td>2</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>35.877365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-03</th>\n",
       "      <td>4957</td>\n",
       "      <td>21605</td>\n",
       "      <td>3030</td>\n",
       "      <td>9983</td>\n",
       "      <td>7959</td>\n",
       "      <td>34720</td>\n",
       "      <td>2674</td>\n",
       "      <td>10155</td>\n",
       "      <td>12846</td>\n",
       "      <td>40411</td>\n",
       "      <td>...</td>\n",
       "      <td>2010</td>\n",
       "      <td>53</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>-1</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>35.874707</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>5759</td>\n",
       "      <td>35557</td>\n",
       "      <td>3494</td>\n",
       "      <td>16032</td>\n",
       "      <td>8653</td>\n",
       "      <td>45846</td>\n",
       "      <td>3341</td>\n",
       "      <td>16503</td>\n",
       "      <td>12441</td>\n",
       "      <td>55307</td>\n",
       "      <td>...</td>\n",
       "      <td>2010</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>6096</td>\n",
       "      <td>38810</td>\n",
       "      <td>3647</td>\n",
       "      <td>16821</td>\n",
       "      <td>8818</td>\n",
       "      <td>49009</td>\n",
       "      <td>3285</td>\n",
       "      <td>17418</td>\n",
       "      <td>12443</td>\n",
       "      <td>59430</td>\n",
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       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Brooklyn Battery cash  Brooklyn Battery ezpass  Cross Bay cash  \\\n",
       "datetime                                                                     \n",
       "2010-01-01                   4902                    17043            3577   \n",
       "2010-01-02                   5347                    20799            3508   \n",
       "2010-01-03                   4957                    21605            3030   \n",
       "2010-01-04                   5759                    35557            3494   \n",
       "2010-01-05                   6096                    38810            3647   \n",
       "\n",
       "            Cross Bay ezpass  Henry Hudson cash  Henry Hudson ezpass  \\\n",
       "datetime                                                               \n",
       "2010-01-01              9760               7491                27175   \n",
       "2010-01-02             11673               9396                37110   \n",
       "2010-01-03              9983               7959                34720   \n",
       "2010-01-04             16032               8653                45846   \n",
       "2010-01-05             16821               8818                49009   \n",
       "\n",
       "            Marine Parkway cash  Marine Parkway ezpass  Queens Midtown cash  \\\n",
       "datetime                                                                      \n",
       "2010-01-01                 2899                  10243                12295   \n",
       "2010-01-02                 3053                  11552                14182   \n",
       "2010-01-03                 2674                  10155                12846   \n",
       "2010-01-04                 3341                  16503                12441   \n",
       "2010-01-05                 3285                  17418                12443   \n",
       "\n",
       "            Queens Midtown ezpass  ...  year  week  day  quarter  dayofyear  \\\n",
       "datetime                           ...                                        \n",
       "2010-01-01                  31460  ...  2010    53    1        1          1   \n",
       "2010-01-02                  40597  ...  2010    53    2        1          2   \n",
       "2010-01-03                  40411  ...  2010    53    3        1          3   \n",
       "2010-01-04                  55307  ...  2010     1    4        1          4   \n",
       "2010-01-05                  59430  ...  2010     1    5        1          5   \n",
       "\n",
       "            Phase  Cashless  weekend  holiday  temp_average  \n",
       "datetime                                                     \n",
       "2010-01-01     -1         0        0        1     36.372828  \n",
       "2010-01-02     -1         0        1        0     35.877365  \n",
       "2010-01-03     -1         0        1        0     35.874707  \n",
       "2010-01-04     -1         0        0        0     35.631358  \n",
       "2010-01-05     -1         0        0        0     36.069875  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Imputing 2 standard deviations with np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "_to_replace = _df[:'2020-02'].copy(deep=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2</td>\n",
       "      <td>-1</td>\n",
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       "      <td>35.877365</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-03</th>\n",
       "      <td>4957</td>\n",
       "      <td>21605</td>\n",
       "      <td>3030</td>\n",
       "      <td>9983</td>\n",
       "      <td>7959</td>\n",
       "      <td>34720</td>\n",
       "      <td>2674</td>\n",
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       "      <td>12846</td>\n",
       "      <td>40411</td>\n",
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       "      <td>3</td>\n",
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       "      <td>-1</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>5759</td>\n",
       "      <td>35557</td>\n",
       "      <td>3494</td>\n",
       "      <td>16032</td>\n",
       "      <td>8653</td>\n",
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       "      <td>3341</td>\n",
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       "      <td>12441</td>\n",
       "      <td>55307</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>-1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35.631358</td>\n",
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       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>6096</td>\n",
       "      <td>38810</td>\n",
       "      <td>3647</td>\n",
       "      <td>16821</td>\n",
       "      <td>8818</td>\n",
       "      <td>49009</td>\n",
       "      <td>3285</td>\n",
       "      <td>17418</td>\n",
       "      <td>12443</td>\n",
       "      <td>59430</td>\n",
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       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>-1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2020-02-25</th>\n",
       "      <td>5180</td>\n",
       "      <td>52130</td>\n",
       "      <td>2713</td>\n",
       "      <td>20166</td>\n",
       "      <td>5979</td>\n",
       "      <td>62776</td>\n",
       "      <td>1853</td>\n",
       "      <td>19577</td>\n",
       "      <td>9882</td>\n",
       "      <td>71677</td>\n",
       "      <td>...</td>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>56</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>37.694789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-26</th>\n",
       "      <td>5070</td>\n",
       "      <td>51882</td>\n",
       "      <td>2851</td>\n",
       "      <td>20887</td>\n",
       "      <td>5979</td>\n",
       "      <td>61826</td>\n",
       "      <td>1997</td>\n",
       "      <td>20495</td>\n",
       "      <td>10161</td>\n",
       "      <td>74159</td>\n",
       "      <td>...</td>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>57</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>37.977923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-27</th>\n",
       "      <td>5551</td>\n",
       "      <td>56336</td>\n",
       "      <td>2859</td>\n",
       "      <td>20936</td>\n",
       "      <td>6451</td>\n",
       "      <td>66178</td>\n",
       "      <td>1751</td>\n",
       "      <td>19326</td>\n",
       "      <td>10880</td>\n",
       "      <td>77537</td>\n",
       "      <td>...</td>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>58</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>37.989528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-28</th>\n",
       "      <td>5687</td>\n",
       "      <td>53574</td>\n",
       "      <td>3052</td>\n",
       "      <td>21369</td>\n",
       "      <td>7816</td>\n",
       "      <td>69597</td>\n",
       "      <td>1933</td>\n",
       "      <td>20215</td>\n",
       "      <td>11880</td>\n",
       "      <td>79386</td>\n",
       "      <td>...</td>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>38.036018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-29</th>\n",
       "      <td>4884</td>\n",
       "      <td>40018</td>\n",
       "      <td>2160</td>\n",
       "      <td>15921</td>\n",
       "      <td>7353</td>\n",
       "      <td>57927</td>\n",
       "      <td>1725</td>\n",
       "      <td>15854</td>\n",
       "      <td>11333</td>\n",
       "      <td>64783</td>\n",
       "      <td>...</td>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>38.180910</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3712 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Brooklyn Battery cash  Brooklyn Battery ezpass  Cross Bay cash  \\\n",
       "datetime                                                                     \n",
       "2010-01-01                   4902                    17043            3577   \n",
       "2010-01-02                   5347                    20799            3508   \n",
       "2010-01-03                   4957                    21605            3030   \n",
       "2010-01-04                   5759                    35557            3494   \n",
       "2010-01-05                   6096                    38810            3647   \n",
       "...                           ...                      ...             ...   \n",
       "2020-02-25                   5180                    52130            2713   \n",
       "2020-02-26                   5070                    51882            2851   \n",
       "2020-02-27                   5551                    56336            2859   \n",
       "2020-02-28                   5687                    53574            3052   \n",
       "2020-02-29                   4884                    40018            2160   \n",
       "\n",
       "            Cross Bay ezpass  Henry Hudson cash  Henry Hudson ezpass  \\\n",
       "datetime                                                               \n",
       "2010-01-01              9760               7491                27175   \n",
       "2010-01-02             11673               9396                37110   \n",
       "2010-01-03              9983               7959                34720   \n",
       "2010-01-04             16032               8653                45846   \n",
       "2010-01-05             16821               8818                49009   \n",
       "...                      ...                ...                  ...   \n",
       "2020-02-25             20166               5979                62776   \n",
       "2020-02-26             20887               5979                61826   \n",
       "2020-02-27             20936               6451                66178   \n",
       "2020-02-28             21369               7816                69597   \n",
       "2020-02-29             15921               7353                57927   \n",
       "\n",
       "            Marine Parkway cash  Marine Parkway ezpass  Queens Midtown cash  \\\n",
       "datetime                                                                      \n",
       "2010-01-01                 2899                  10243                12295   \n",
       "2010-01-02                 3053                  11552                14182   \n",
       "2010-01-03                 2674                  10155                12846   \n",
       "2010-01-04                 3341                  16503                12441   \n",
       "2010-01-05                 3285                  17418                12443   \n",
       "...                         ...                    ...                  ...   \n",
       "2020-02-25                 1853                  19577                 9882   \n",
       "2020-02-26                 1997                  20495                10161   \n",
       "2020-02-27                 1751                  19326                10880   \n",
       "2020-02-28                 1933                  20215                11880   \n",
       "2020-02-29                 1725                  15854                11333   \n",
       "\n",
       "            Queens Midtown ezpass  ...  year  week  day  quarter  dayofyear  \\\n",
       "datetime                           ...                                        \n",
       "2010-01-01                  31460  ...  2010    53    1        1          1   \n",
       "2010-01-02                  40597  ...  2010    53    2        1          2   \n",
       "2010-01-03                  40411  ...  2010    53    3        1          3   \n",
       "2010-01-04                  55307  ...  2010     1    4        1          4   \n",
       "2010-01-05                  59430  ...  2010     1    5        1          5   \n",
       "...                           ...  ...   ...   ...  ...      ...        ...   \n",
       "2020-02-25                  71677  ...  2020     9   25        1         56   \n",
       "2020-02-26                  74159  ...  2020     9   26        1         57   \n",
       "2020-02-27                  77537  ...  2020     9   27        1         58   \n",
       "2020-02-28                  79386  ...  2020     9   28        1         59   \n",
       "2020-02-29                  64783  ...  2020     9   29        1         60   \n",
       "\n",
       "            Phase  Cashless  weekend  holiday  temp_average  \n",
       "datetime                                                     \n",
       "2010-01-01     -1         0        0        1     36.372828  \n",
       "2010-01-02     -1         0        1        0     35.877365  \n",
       "2010-01-03     -1         0        1        0     35.874707  \n",
       "2010-01-04     -1         0        0        0     35.631358  \n",
       "2010-01-05     -1         0        0        0     36.069875  \n",
       "...           ...       ...      ...      ...           ...  \n",
       "2020-02-25     -1         1        0        0     37.694789  \n",
       "2020-02-26     -1         1        0        0     37.977923  \n",
       "2020-02-27     -1         1        0        0     37.989528  \n",
       "2020-02-28     -1         1        0        0     38.036018  \n",
       "2020-02-29     -1         1        1        0     38.180910  \n",
       "\n",
       "[3712 rows x 30 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_to_replace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Brooklyn Battery cash 1064.4675187552316 8972.619226934425\n",
      "Brooklyn Battery ezpass 9431.270599655913 69255.04513310271\n",
      "Cross Bay cash 293.7279581169719 6384.422903951994\n",
      "Cross Bay ezpass 6587.71548581645 27905.75326418355\n",
      "Henry Hudson cash 1334.0785876519158 13710.892317520498\n",
      "Henry Hudson ezpass 12834.290998501187 88624.12333339537\n",
      "Marine Parkway cash 80.91117516288568 5163.887855009529\n",
      "Marine Parkway ezpass 6543.046640777544 28691.764242843143\n",
      "Queens Midtown cash 1681.8596376783744 17238.92861663197\n",
      "Queens Midtown ezpass 18269.325562113758 106062.75471805866\n",
      "Throgs Neck cash 7549.813624375727 30516.845858382898\n",
      "Throgs Neck ezpass 54114.71124818096 131961.71816992247\n",
      "Triboro cash 9362.213367438908 53436.96174031972\n",
      "Triboro ezpass 59690.65270054083 203353.64794601087\n",
      "Verrazano cash 3794.890055666572 22388.070612436877\n",
      "Verrazano ezpass 40225.15998202289 116069.48603090816\n",
      "Whitestone cash 9763.738216563777 37710.747774815536\n",
      "Whitestone ezpass 47200.66783880152 134922.84724740539\n"
     ]
    }
   ],
   "source": [
    "for i in bridges_joined:\n",
    "    print(i, \n",
    "          _to_replace[i].mean() - _to_replace[i].std() * 2, \n",
    "          _to_replace[i].mean() + _to_replace[i].std() * 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in bridges_joined:\n",
    "    conditions = [\n",
    "        _to_replace[i] < _to_replace[i].mean() - _to_replace[i].std() * 2,\n",
    "        _to_replace[i] > _to_replace[i].mean() + _to_replace[i].std() * 2\n",
    "    ]\n",
    "    choices = [\n",
    "        np.nan,\n",
    "        np.nan\n",
    "    ]\n",
    "    _to_replace[i] = np.select(conditions, choices, _to_replace[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1eea0608>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_to_replace[bridges_joined].plot(figsize=(14,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Brooklyn Battery cash      363\n",
       "Brooklyn Battery ezpass    338\n",
       "Cross Bay cash             368\n",
       "Cross Bay ezpass           213\n",
       "Henry Hudson cash          379\n",
       "Henry Hudson ezpass        368\n",
       "Marine Parkway cash        361\n",
       "Marine Parkway ezpass      227\n",
       "Queens Midtown cash        355\n",
       "Queens Midtown ezpass      324\n",
       "Throgs Neck cash           196\n",
       "Throgs Neck ezpass         117\n",
       "Triboro cash               259\n",
       "Triboro ezpass             172\n",
       "Verrazano cash             251\n",
       "Verrazano ezpass           154\n",
       "Whitestone cash            193\n",
       "Whitestone ezpass          105\n",
       "month                        0\n",
       "dayofweek                    0\n",
       "year                         0\n",
       "week                         0\n",
       "day                          0\n",
       "quarter                      0\n",
       "dayofyear                    0\n",
       "Phase                        0\n",
       "Cashless                     0\n",
       "weekend                      0\n",
       "holiday                      0\n",
       "temp_average                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_to_replace.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4743"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_to_replace.isna().sum().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are 4743 values I need to replace."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# _fb_exog will be used for additional independent features\n",
    "_fb_exog = _to_replace[['month', 'dayofweek', 'quarter', 'year',\n",
    "           'Phase', 'weekend', 'holiday', 'temp_average', 'Cashless']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# yhat results will be predicted from _fb_exog_reset\n",
    "_test_set = _fb_exog.reset_index()\n",
    "_test_set.rename(columns={'datetime':'ds'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fb_prophet_yhat(bridge):\n",
    "    \"\"\"\n",
    "    returns y_hat values for bridge adjusted based off of mean_percentage_error\n",
    "    ex: if mean percentage error is -0.01, adjust yhat by multiplying 0.99 (1 + (-0.01))\n",
    "    \n",
    "    \"\"\"\n",
    "    _training = _to_replace[[bridge]].copy(deep=True)\n",
    "    _training = _training.join(_fb_exog)\n",
    "    _training.reset_index(inplace=True)\n",
    "    _training.rename(columns = {bridge:'y', 'datetime': 'ds'}, inplace=True)\n",
    "    \n",
    "    # hyperparameters assisted from: https://towardsdatascience.com/implementing-facebook-prophet-efficiently-c241305405a3\n",
    "    m = Prophet(\n",
    "        changepoint_prior_scale= 30,\n",
    "        holidays_prior_scale = 20,\n",
    "        seasonality_prior_scale = 35,\n",
    "        n_changepoints = 300,\n",
    "        seasonality_mode = 'additive',\n",
    "        daily_seasonality = False,\n",
    "        weekly_seasonality=False,\n",
    "        yearly_seasonality = False\n",
    "            ).add_seasonality(name = 'monthly', period = 30.5, fourier_order=12\n",
    "            ).add_seasonality(name = 'weekly', period = 7, fourier_order = 20\n",
    "            ).add_seasonality(name = 'yearly', period = 365.25, fourier_order = 20\n",
    "            ).add_seasonality(name = 'quarterly', period = 365.25/4, fourier_order = 5, prior_scale=15)\n",
    "    for i in _fb_exog.columns:\n",
    "        m.add_regressor(i)\n",
    "        \n",
    "        \n",
    "    m.fit(_training)\n",
    "        \n",
    "    \n",
    "    forecast = m.predict(_test_set)\n",
    "    \n",
    "\n",
    "    _mult = 1 + mean_percentage_error(_training[~_training['y'].isna()]['y'],\n",
    "                     forecast.loc[forecast['ds'].isin(_training[~_training['y'].isna()]['ds'])]['yhat'])\n",
    "    \n",
    "    forecast.set_index('ds', inplace=True)\n",
    "    \n",
    "    return forecast['yhat'] * _mult"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Creating results dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "_yhat_results = pd.DataFrame()\n",
    "_yhat_results['ds'] = _to_replace.index\n",
    "_yhat_results.set_index('ds', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 18/18 [1:12:43<00:00, 242.41s/it]\n"
     ]
    }
   ],
   "source": [
    "for i in tqdm(bridges_joined):\n",
    "    _yhat_results[i] = fb_prophet_yhat(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Replacing null values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "_to_replace_copy = _to_replace.copy(deep=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "_to_replace_copy.reset_index(inplace=True)\n",
    "_to_replace_copy.rename(columns={'datetime':'ds'}, inplace=True)\n",
    "_to_replace_copy.set_index('ds', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in bridges_joined:\n",
    "    _to_replace_copy[i].fillna(_yhat_results[i], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "#concatting dataframe post March 2020\n",
    "_concat = return_series('mta.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "_concat_unstack = _concat.unstack().T\n",
    "# unstacking multi-index to single for easability\n",
    "_concat_unstack.columns = [' '.join(column).strip() for column in _concat_unstack.columns.values]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Brooklyn Battery cash</th>\n",
       "      <th>Brooklyn Battery ezpass</th>\n",
       "      <th>Cross Bay cash</th>\n",
       "      <th>Cross Bay ezpass</th>\n",
       "      <th>Henry Hudson cash</th>\n",
       "      <th>Henry Hudson ezpass</th>\n",
       "      <th>Marine Parkway cash</th>\n",
       "      <th>Marine Parkway ezpass</th>\n",
       "      <th>Queens Midtown cash</th>\n",
       "      <th>Queens Midtown ezpass</th>\n",
       "      <th>Throgs Neck cash</th>\n",
       "      <th>Throgs Neck ezpass</th>\n",
       "      <th>Triboro cash</th>\n",
       "      <th>Triboro ezpass</th>\n",
       "      <th>Verrazano cash</th>\n",
       "      <th>Verrazano ezpass</th>\n",
       "      <th>Whitestone cash</th>\n",
       "      <th>Whitestone ezpass</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ds</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",
       "      <th>2020-03-01</th>\n",
       "      <td>4373</td>\n",
       "      <td>37462</td>\n",
       "      <td>2070</td>\n",
       "      <td>14440</td>\n",
       "      <td>6606</td>\n",
       "      <td>53701</td>\n",
       "      <td>1527</td>\n",
       "      <td>13531</td>\n",
       "      <td>10237</td>\n",
       "      <td>63461</td>\n",
       "      <td>16962</td>\n",
       "      <td>95155</td>\n",
       "      <td>22076</td>\n",
       "      <td>134756</td>\n",
       "      <td>10192</td>\n",
       "      <td>79973</td>\n",
       "      <td>19582</td>\n",
       "      <td>102766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-02</th>\n",
       "      <td>5276</td>\n",
       "      <td>51256</td>\n",
       "      <td>2761</td>\n",
       "      <td>19899</td>\n",
       "      <td>6331</td>\n",
       "      <td>62316</td>\n",
       "      <td>1887</td>\n",
       "      <td>19261</td>\n",
       "      <td>10385</td>\n",
       "      <td>71096</td>\n",
       "      <td>13086</td>\n",
       "      <td>94732</td>\n",
       "      <td>21739</td>\n",
       "      <td>151823</td>\n",
       "      <td>9142</td>\n",
       "      <td>91803</td>\n",
       "      <td>17998</td>\n",
       "      <td>113977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-03</th>\n",
       "      <td>5315</td>\n",
       "      <td>53495</td>\n",
       "      <td>2803</td>\n",
       "      <td>20373</td>\n",
       "      <td>6155</td>\n",
       "      <td>63889</td>\n",
       "      <td>1851</td>\n",
       "      <td>20370</td>\n",
       "      <td>10369</td>\n",
       "      <td>71948</td>\n",
       "      <td>12445</td>\n",
       "      <td>95345</td>\n",
       "      <td>21727</td>\n",
       "      <td>154621</td>\n",
       "      <td>8542</td>\n",
       "      <td>93210</td>\n",
       "      <td>17323</td>\n",
       "      <td>111666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-04</th>\n",
       "      <td>5488</td>\n",
       "      <td>53585</td>\n",
       "      <td>2950</td>\n",
       "      <td>20866</td>\n",
       "      <td>6486</td>\n",
       "      <td>65572</td>\n",
       "      <td>2036</td>\n",
       "      <td>20770</td>\n",
       "      <td>10557</td>\n",
       "      <td>73724</td>\n",
       "      <td>12840</td>\n",
       "      <td>99001</td>\n",
       "      <td>22556</td>\n",
       "      <td>159497</td>\n",
       "      <td>8825</td>\n",
       "      <td>95187</td>\n",
       "      <td>18087</td>\n",
       "      <td>114377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-05</th>\n",
       "      <td>5521</td>\n",
       "      <td>54494</td>\n",
       "      <td>2856</td>\n",
       "      <td>21032</td>\n",
       "      <td>6804</td>\n",
       "      <td>66928</td>\n",
       "      <td>2003</td>\n",
       "      <td>20506</td>\n",
       "      <td>10871</td>\n",
       "      <td>75097</td>\n",
       "      <td>13671</td>\n",
       "      <td>102022</td>\n",
       "      <td>23911</td>\n",
       "      <td>168128</td>\n",
       "      <td>9085</td>\n",
       "      <td>96822</td>\n",
       "      <td>18436</td>\n",
       "      <td>115873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-27</th>\n",
       "      <td>7017</td>\n",
       "      <td>48686</td>\n",
       "      <td>3119</td>\n",
       "      <td>18489</td>\n",
       "      <td>7327</td>\n",
       "      <td>49382</td>\n",
       "      <td>2504</td>\n",
       "      <td>18027</td>\n",
       "      <td>10890</td>\n",
       "      <td>54152</td>\n",
       "      <td>14575</td>\n",
       "      <td>83780</td>\n",
       "      <td>25680</td>\n",
       "      <td>132213</td>\n",
       "      <td>10768</td>\n",
       "      <td>83895</td>\n",
       "      <td>19322</td>\n",
       "      <td>96509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-28</th>\n",
       "      <td>7169</td>\n",
       "      <td>49697</td>\n",
       "      <td>2964</td>\n",
       "      <td>18280</td>\n",
       "      <td>7682</td>\n",
       "      <td>53050</td>\n",
       "      <td>2203</td>\n",
       "      <td>17072</td>\n",
       "      <td>11612</td>\n",
       "      <td>57293</td>\n",
       "      <td>14343</td>\n",
       "      <td>83983</td>\n",
       "      <td>26030</td>\n",
       "      <td>135054</td>\n",
       "      <td>10720</td>\n",
       "      <td>84472</td>\n",
       "      <td>19636</td>\n",
       "      <td>97112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-29</th>\n",
       "      <td>6817</td>\n",
       "      <td>48263</td>\n",
       "      <td>2902</td>\n",
       "      <td>17012</td>\n",
       "      <td>7623</td>\n",
       "      <td>52082</td>\n",
       "      <td>2198</td>\n",
       "      <td>16172</td>\n",
       "      <td>11002</td>\n",
       "      <td>56973</td>\n",
       "      <td>13741</td>\n",
       "      <td>78270</td>\n",
       "      <td>24863</td>\n",
       "      <td>129996</td>\n",
       "      <td>10724</td>\n",
       "      <td>82194</td>\n",
       "      <td>19328</td>\n",
       "      <td>95198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-30</th>\n",
       "      <td>7225</td>\n",
       "      <td>46641</td>\n",
       "      <td>3380</td>\n",
       "      <td>19998</td>\n",
       "      <td>8879</td>\n",
       "      <td>54020</td>\n",
       "      <td>2069</td>\n",
       "      <td>14614</td>\n",
       "      <td>14757</td>\n",
       "      <td>55082</td>\n",
       "      <td>16237</td>\n",
       "      <td>84717</td>\n",
       "      <td>28425</td>\n",
       "      <td>139396</td>\n",
       "      <td>12198</td>\n",
       "      <td>86893</td>\n",
       "      <td>21923</td>\n",
       "      <td>100435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-31</th>\n",
       "      <td>5953</td>\n",
       "      <td>32686</td>\n",
       "      <td>2942</td>\n",
       "      <td>16319</td>\n",
       "      <td>8464</td>\n",
       "      <td>45459</td>\n",
       "      <td>2239</td>\n",
       "      <td>14049</td>\n",
       "      <td>10535</td>\n",
       "      <td>46169</td>\n",
       "      <td>17256</td>\n",
       "      <td>79355</td>\n",
       "      <td>27852</td>\n",
       "      <td>122710</td>\n",
       "      <td>13182</td>\n",
       "      <td>79934</td>\n",
       "      <td>23245</td>\n",
       "      <td>94154</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>245 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Brooklyn Battery cash  Brooklyn Battery ezpass  Cross Bay cash  \\\n",
       "ds                                                                           \n",
       "2020-03-01                   4373                    37462            2070   \n",
       "2020-03-02                   5276                    51256            2761   \n",
       "2020-03-03                   5315                    53495            2803   \n",
       "2020-03-04                   5488                    53585            2950   \n",
       "2020-03-05                   5521                    54494            2856   \n",
       "...                           ...                      ...             ...   \n",
       "2020-10-27                   7017                    48686            3119   \n",
       "2020-10-28                   7169                    49697            2964   \n",
       "2020-10-29                   6817                    48263            2902   \n",
       "2020-10-30                   7225                    46641            3380   \n",
       "2020-10-31                   5953                    32686            2942   \n",
       "\n",
       "            Cross Bay ezpass  Henry Hudson cash  Henry Hudson ezpass  \\\n",
       "ds                                                                     \n",
       "2020-03-01             14440               6606                53701   \n",
       "2020-03-02             19899               6331                62316   \n",
       "2020-03-03             20373               6155                63889   \n",
       "2020-03-04             20866               6486                65572   \n",
       "2020-03-05             21032               6804                66928   \n",
       "...                      ...                ...                  ...   \n",
       "2020-10-27             18489               7327                49382   \n",
       "2020-10-28             18280               7682                53050   \n",
       "2020-10-29             17012               7623                52082   \n",
       "2020-10-30             19998               8879                54020   \n",
       "2020-10-31             16319               8464                45459   \n",
       "\n",
       "            Marine Parkway cash  Marine Parkway ezpass  Queens Midtown cash  \\\n",
       "ds                                                                            \n",
       "2020-03-01                 1527                  13531                10237   \n",
       "2020-03-02                 1887                  19261                10385   \n",
       "2020-03-03                 1851                  20370                10369   \n",
       "2020-03-04                 2036                  20770                10557   \n",
       "2020-03-05                 2003                  20506                10871   \n",
       "...                         ...                    ...                  ...   \n",
       "2020-10-27                 2504                  18027                10890   \n",
       "2020-10-28                 2203                  17072                11612   \n",
       "2020-10-29                 2198                  16172                11002   \n",
       "2020-10-30                 2069                  14614                14757   \n",
       "2020-10-31                 2239                  14049                10535   \n",
       "\n",
       "            Queens Midtown ezpass  Throgs Neck cash  Throgs Neck ezpass  \\\n",
       "ds                                                                        \n",
       "2020-03-01                  63461             16962               95155   \n",
       "2020-03-02                  71096             13086               94732   \n",
       "2020-03-03                  71948             12445               95345   \n",
       "2020-03-04                  73724             12840               99001   \n",
       "2020-03-05                  75097             13671              102022   \n",
       "...                           ...               ...                 ...   \n",
       "2020-10-27                  54152             14575               83780   \n",
       "2020-10-28                  57293             14343               83983   \n",
       "2020-10-29                  56973             13741               78270   \n",
       "2020-10-30                  55082             16237               84717   \n",
       "2020-10-31                  46169             17256               79355   \n",
       "\n",
       "            Triboro cash  Triboro ezpass  Verrazano cash  Verrazano ezpass  \\\n",
       "ds                                                                           \n",
       "2020-03-01         22076          134756           10192             79973   \n",
       "2020-03-02         21739          151823            9142             91803   \n",
       "2020-03-03         21727          154621            8542             93210   \n",
       "2020-03-04         22556          159497            8825             95187   \n",
       "2020-03-05         23911          168128            9085             96822   \n",
       "...                  ...             ...             ...               ...   \n",
       "2020-10-27         25680          132213           10768             83895   \n",
       "2020-10-28         26030          135054           10720             84472   \n",
       "2020-10-29         24863          129996           10724             82194   \n",
       "2020-10-30         28425          139396           12198             86893   \n",
       "2020-10-31         27852          122710           13182             79934   \n",
       "\n",
       "            Whitestone cash  Whitestone ezpass  \n",
       "ds                                              \n",
       "2020-03-01            19582             102766  \n",
       "2020-03-02            17998             113977  \n",
       "2020-03-03            17323             111666  \n",
       "2020-03-04            18087             114377  \n",
       "2020-03-05            18436             115873  \n",
       "...                     ...                ...  \n",
       "2020-10-27            19322              96509  \n",
       "2020-10-28            19636              97112  \n",
       "2020-10-29            19328              95198  \n",
       "2020-10-30            21923             100435  \n",
       "2020-10-31            23245              94154  \n",
       "\n",
       "[245 rows x 18 columns]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_concat_unstack = _concat_unstack['2020-03':].copy(deep=True)\n",
    "_concat_unstack.reset_index(inplace=True)\n",
    "_concat_unstack.rename(columns = {'datetime': 'ds'}, inplace=True)\n",
    "_concat_unstack.set_index('ds', inplace=True)\n",
    "_concat_unstack"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "_concat_unstack = date_features(_concat_unstack)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "_to_tableau = pd.concat([_to_replace_copy, _concat_unstack])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "_to_tableau.drop(columns='temp_average', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Brooklyn Battery cash</th>\n",
       "      <th>Brooklyn Battery ezpass</th>\n",
       "      <th>Cross Bay cash</th>\n",
       "      <th>Cross Bay ezpass</th>\n",
       "      <th>Henry Hudson cash</th>\n",
       "      <th>Henry Hudson ezpass</th>\n",
       "      <th>Marine Parkway cash</th>\n",
       "      <th>Marine Parkway ezpass</th>\n",
       "      <th>Queens Midtown cash</th>\n",
       "      <th>Queens Midtown ezpass</th>\n",
       "      <th>...</th>\n",
       "      <th>dayofweek</th>\n",
       "      <th>year</th>\n",
       "      <th>week</th>\n",
       "      <th>day</th>\n",
       "      <th>quarter</th>\n",
       "      <th>dayofyear</th>\n",
       "      <th>Phase</th>\n",
       "      <th>Cashless</th>\n",
       "      <th>weekend</th>\n",
       "      <th>holiday</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ds</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",
       "      <th>2010-01-01</th>\n",
       "      <td>4902.0</td>\n",
       "      <td>17043.0</td>\n",
       "      <td>3577.0</td>\n",
       "      <td>9760.0</td>\n",
       "      <td>7491.0</td>\n",
       "      <td>27175.0</td>\n",
       "      <td>2899.0</td>\n",
       "      <td>10243.0</td>\n",
       "      <td>12295.0</td>\n",
       "      <td>31460.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>53</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-02</th>\n",
       "      <td>5347.0</td>\n",
       "      <td>20799.0</td>\n",
       "      <td>3508.0</td>\n",
       "      <td>11673.0</td>\n",
       "      <td>9396.0</td>\n",
       "      <td>37110.0</td>\n",
       "      <td>3053.0</td>\n",
       "      <td>11552.0</td>\n",
       "      <td>14182.0</td>\n",
       "      <td>40597.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>53</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-03</th>\n",
       "      <td>4957.0</td>\n",
       "      <td>21605.0</td>\n",
       "      <td>3030.0</td>\n",
       "      <td>9983.0</td>\n",
       "      <td>7959.0</td>\n",
       "      <td>34720.0</td>\n",
       "      <td>2674.0</td>\n",
       "      <td>10155.0</td>\n",
       "      <td>12846.0</td>\n",
       "      <td>40411.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>2010</td>\n",
       "      <td>53</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>5759.0</td>\n",
       "      <td>35557.0</td>\n",
       "      <td>3494.0</td>\n",
       "      <td>16032.0</td>\n",
       "      <td>8653.0</td>\n",
       "      <td>45846.0</td>\n",
       "      <td>3341.0</td>\n",
       "      <td>16503.0</td>\n",
       "      <td>12441.0</td>\n",
       "      <td>55307.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2010</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>6096.0</td>\n",
       "      <td>38810.0</td>\n",
       "      <td>3647.0</td>\n",
       "      <td>16821.0</td>\n",
       "      <td>8818.0</td>\n",
       "      <td>49009.0</td>\n",
       "      <td>3285.0</td>\n",
       "      <td>17418.0</td>\n",
       "      <td>12443.0</td>\n",
       "      <td>59430.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-27</th>\n",
       "      <td>7017.0</td>\n",
       "      <td>48686.0</td>\n",
       "      <td>3119.0</td>\n",
       "      <td>18489.0</td>\n",
       "      <td>7327.0</td>\n",
       "      <td>49382.0</td>\n",
       "      <td>2504.0</td>\n",
       "      <td>18027.0</td>\n",
       "      <td>10890.0</td>\n",
       "      <td>54152.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2020</td>\n",
       "      <td>44</td>\n",
       "      <td>27</td>\n",
       "      <td>4</td>\n",
       "      <td>301</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-28</th>\n",
       "      <td>7169.0</td>\n",
       "      <td>49697.0</td>\n",
       "      <td>2964.0</td>\n",
       "      <td>18280.0</td>\n",
       "      <td>7682.0</td>\n",
       "      <td>53050.0</td>\n",
       "      <td>2203.0</td>\n",
       "      <td>17072.0</td>\n",
       "      <td>11612.0</td>\n",
       "      <td>57293.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2020</td>\n",
       "      <td>44</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>302</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-29</th>\n",
       "      <td>6817.0</td>\n",
       "      <td>48263.0</td>\n",
       "      <td>2902.0</td>\n",
       "      <td>17012.0</td>\n",
       "      <td>7623.0</td>\n",
       "      <td>52082.0</td>\n",
       "      <td>2198.0</td>\n",
       "      <td>16172.0</td>\n",
       "      <td>11002.0</td>\n",
       "      <td>56973.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2020</td>\n",
       "      <td>44</td>\n",
       "      <td>29</td>\n",
       "      <td>4</td>\n",
       "      <td>303</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-30</th>\n",
       "      <td>7225.0</td>\n",
       "      <td>46641.0</td>\n",
       "      <td>3380.0</td>\n",
       "      <td>19998.0</td>\n",
       "      <td>8879.0</td>\n",
       "      <td>54020.0</td>\n",
       "      <td>2069.0</td>\n",
       "      <td>14614.0</td>\n",
       "      <td>14757.0</td>\n",
       "      <td>55082.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>2020</td>\n",
       "      <td>44</td>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>304</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-31</th>\n",
       "      <td>5953.0</td>\n",
       "      <td>32686.0</td>\n",
       "      <td>2942.0</td>\n",
       "      <td>16319.0</td>\n",
       "      <td>8464.0</td>\n",
       "      <td>45459.0</td>\n",
       "      <td>2239.0</td>\n",
       "      <td>14049.0</td>\n",
       "      <td>10535.0</td>\n",
       "      <td>46169.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>2020</td>\n",
       "      <td>44</td>\n",
       "      <td>31</td>\n",
       "      <td>4</td>\n",
       "      <td>305</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3957 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Brooklyn Battery cash  Brooklyn Battery ezpass  Cross Bay cash  \\\n",
       "ds                                                                           \n",
       "2010-01-01                 4902.0                  17043.0          3577.0   \n",
       "2010-01-02                 5347.0                  20799.0          3508.0   \n",
       "2010-01-03                 4957.0                  21605.0          3030.0   \n",
       "2010-01-04                 5759.0                  35557.0          3494.0   \n",
       "2010-01-05                 6096.0                  38810.0          3647.0   \n",
       "...                           ...                      ...             ...   \n",
       "2020-10-27                 7017.0                  48686.0          3119.0   \n",
       "2020-10-28                 7169.0                  49697.0          2964.0   \n",
       "2020-10-29                 6817.0                  48263.0          2902.0   \n",
       "2020-10-30                 7225.0                  46641.0          3380.0   \n",
       "2020-10-31                 5953.0                  32686.0          2942.0   \n",
       "\n",
       "            Cross Bay ezpass  Henry Hudson cash  Henry Hudson ezpass  \\\n",
       "ds                                                                     \n",
       "2010-01-01            9760.0             7491.0              27175.0   \n",
       "2010-01-02           11673.0             9396.0              37110.0   \n",
       "2010-01-03            9983.0             7959.0              34720.0   \n",
       "2010-01-04           16032.0             8653.0              45846.0   \n",
       "2010-01-05           16821.0             8818.0              49009.0   \n",
       "...                      ...                ...                  ...   \n",
       "2020-10-27           18489.0             7327.0              49382.0   \n",
       "2020-10-28           18280.0             7682.0              53050.0   \n",
       "2020-10-29           17012.0             7623.0              52082.0   \n",
       "2020-10-30           19998.0             8879.0              54020.0   \n",
       "2020-10-31           16319.0             8464.0              45459.0   \n",
       "\n",
       "            Marine Parkway cash  Marine Parkway ezpass  Queens Midtown cash  \\\n",
       "ds                                                                            \n",
       "2010-01-01               2899.0                10243.0              12295.0   \n",
       "2010-01-02               3053.0                11552.0              14182.0   \n",
       "2010-01-03               2674.0                10155.0              12846.0   \n",
       "2010-01-04               3341.0                16503.0              12441.0   \n",
       "2010-01-05               3285.0                17418.0              12443.0   \n",
       "...                         ...                    ...                  ...   \n",
       "2020-10-27               2504.0                18027.0              10890.0   \n",
       "2020-10-28               2203.0                17072.0              11612.0   \n",
       "2020-10-29               2198.0                16172.0              11002.0   \n",
       "2020-10-30               2069.0                14614.0              14757.0   \n",
       "2020-10-31               2239.0                14049.0              10535.0   \n",
       "\n",
       "            Queens Midtown ezpass  ...  dayofweek  year  week  day  quarter  \\\n",
       "ds                                 ...                                        \n",
       "2010-01-01                31460.0  ...          4  2010    53    1        1   \n",
       "2010-01-02                40597.0  ...          5  2010    53    2        1   \n",
       "2010-01-03                40411.0  ...          6  2010    53    3        1   \n",
       "2010-01-04                55307.0  ...          0  2010     1    4        1   \n",
       "2010-01-05                59430.0  ...          1  2010     1    5        1   \n",
       "...                           ...  ...        ...   ...   ...  ...      ...   \n",
       "2020-10-27                54152.0  ...          1  2020    44   27        4   \n",
       "2020-10-28                57293.0  ...          2  2020    44   28        4   \n",
       "2020-10-29                56973.0  ...          3  2020    44   29        4   \n",
       "2020-10-30                55082.0  ...          4  2020    44   30        4   \n",
       "2020-10-31                46169.0  ...          5  2020    44   31        4   \n",
       "\n",
       "            dayofyear  Phase  Cashless  weekend  holiday  \n",
       "ds                                                        \n",
       "2010-01-01          1     -1         0        0        1  \n",
       "2010-01-02          2     -1         0        1        0  \n",
       "2010-01-03          3     -1         0        1        0  \n",
       "2010-01-04          4     -1         0        0        0  \n",
       "2010-01-05          5     -1         0        0        0  \n",
       "...               ...    ...       ...      ...      ...  \n",
       "2020-10-27        301      7         1        0        0  \n",
       "2020-10-28        302      7         1        0        0  \n",
       "2020-10-29        303      7         1        0        0  \n",
       "2020-10-30        304      7         1        0        0  \n",
       "2020-10-31        305      7         1        1        0  \n",
       "\n",
       "[3957 rows x 29 columns]"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_to_tableau"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "_to_tableau_final = pd.DataFrame(columns=crossing_rates.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "for left, right in zip(_to_tableau_final.columns, bridges_joined):\n",
    "    _to_tableau_final[left] = _to_tableau[right]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "_to_tableau_final.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "_to_tableau_final = pd.melt(_to_tableau_final, id_vars = ['ds'])\n",
    "_to_tableau_final.columns = ['datetime', 'crossing', 'variation', 'count']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "_to_tableau_final.set_index('datetime', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "_to_tableau_final = date_features(_to_tableau_final)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "_to_tableau_final.to_csv('to_tableau.csv', index=True, header=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('to_tableau.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>datetime</th>\n",
       "      <th>crossing</th>\n",
       "      <th>variation</th>\n",
       "      <th>count</th>\n",
       "      <th>month</th>\n",
       "      <th>dayofweek</th>\n",
       "      <th>year</th>\n",
       "      <th>week</th>\n",
       "      <th>day</th>\n",
       "      <th>quarter</th>\n",
       "      <th>dayofyear</th>\n",
       "      <th>Phase</th>\n",
       "      <th>Cashless</th>\n",
       "      <th>weekend</th>\n",
       "      <th>holiday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-01</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>4902.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>53</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-02</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>5347.0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>53</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-03</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>4957.0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>2010</td>\n",
       "      <td>53</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>5759.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2010</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-05</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>6096.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71977</th>\n",
       "      <td>2020-12-01</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>92265.0</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>2020</td>\n",
       "      <td>49</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>336</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71978</th>\n",
       "      <td>2020-12-02</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>93345.0</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>2020</td>\n",
       "      <td>49</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>337</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71979</th>\n",
       "      <td>2020-12-03</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>94703.0</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>2020</td>\n",
       "      <td>49</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>338</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71980</th>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>98436.0</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>2020</td>\n",
       "      <td>49</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>339</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71981</th>\n",
       "      <td>2020-12-05</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>75063.0</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>2020</td>\n",
       "      <td>49</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>340</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>71982 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         datetime          crossing variation    count  month  dayofweek  \\\n",
       "0      2010-01-01  Brooklyn Battery      cash   4902.0      1          4   \n",
       "1      2010-01-02  Brooklyn Battery      cash   5347.0      1          5   \n",
       "2      2010-01-03  Brooklyn Battery      cash   4957.0      1          6   \n",
       "3      2010-01-04  Brooklyn Battery      cash   5759.0      1          0   \n",
       "4      2010-01-05  Brooklyn Battery      cash   6096.0      1          1   \n",
       "...           ...               ...       ...      ...    ...        ...   \n",
       "71977  2020-12-01        Whitestone    ezpass  92265.0     12          1   \n",
       "71978  2020-12-02        Whitestone    ezpass  93345.0     12          2   \n",
       "71979  2020-12-03        Whitestone    ezpass  94703.0     12          3   \n",
       "71980  2020-12-04        Whitestone    ezpass  98436.0     12          4   \n",
       "71981  2020-12-05        Whitestone    ezpass  75063.0     12          5   \n",
       "\n",
       "       year  week  day  quarter  dayofyear  Phase  Cashless  weekend  holiday  \n",
       "0      2010    53    1        1          1     -1         0        0        1  \n",
       "1      2010    53    2        1          2     -1         0        1        0  \n",
       "2      2010    53    3        1          3     -1         0        1        0  \n",
       "3      2010     1    4        1          4     -1         0        0        0  \n",
       "4      2010     1    5        1          5     -1         0        0        0  \n",
       "...     ...   ...  ...      ...        ...    ...       ...      ...      ...  \n",
       "71977  2020    49    1        4        336      7         1        0        0  \n",
       "71978  2020    49    2        4        337      7         1        0        0  \n",
       "71979  2020    49    3        4        338      7         1        0        0  \n",
       "71980  2020    49    4        4        339      7         1        0        0  \n",
       "71981  2020    49    5        4        340      7         1        1        0  \n",
       "\n",
       "[71982 rows x 15 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['datetime'] = pd.to_datetime(df['datetime'])\n",
    "df = df.loc[df['datetime'] < '2020-11-08']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>datetime</th>\n",
       "      <th>crossing</th>\n",
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       "      <td>4957.0</td>\n",
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       "      <td>6</td>\n",
       "      <td>2010</td>\n",
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       "      <td>6096.0</td>\n",
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       "      <td>2010</td>\n",
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       "      <th>71347</th>\n",
       "      <td>2020-11-03</td>\n",
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       "      <td>ezpass</td>\n",
       "      <td>89018.0</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>71348</th>\n",
       "      <td>2020-11-04</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>94310.0</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
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       "      <td>2020-11-05</td>\n",
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       "      <td>100195.0</td>\n",
       "      <td>11</td>\n",
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       "      <td>45</td>\n",
       "      <td>5</td>\n",
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       "      <td>7</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>71350</th>\n",
       "      <td>2020-11-06</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>107605.0</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>2020</td>\n",
       "      <td>45</td>\n",
       "      <td>6</td>\n",
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       "      <td>311</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>71351</th>\n",
       "      <td>2020-11-07</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>99573.0</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>2020</td>\n",
       "      <td>45</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>312</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>71352 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        datetime          crossing variation     count  month  dayofweek  \\\n",
       "0     2010-01-01  Brooklyn Battery      cash    4902.0      1          4   \n",
       "1     2010-01-02  Brooklyn Battery      cash    5347.0      1          5   \n",
       "2     2010-01-03  Brooklyn Battery      cash    4957.0      1          6   \n",
       "3     2010-01-04  Brooklyn Battery      cash    5759.0      1          0   \n",
       "4     2010-01-05  Brooklyn Battery      cash    6096.0      1          1   \n",
       "...          ...               ...       ...       ...    ...        ...   \n",
       "71347 2020-11-03        Whitestone    ezpass   89018.0     11          1   \n",
       "71348 2020-11-04        Whitestone    ezpass   94310.0     11          2   \n",
       "71349 2020-11-05        Whitestone    ezpass  100195.0     11          3   \n",
       "71350 2020-11-06        Whitestone    ezpass  107605.0     11          4   \n",
       "71351 2020-11-07        Whitestone    ezpass   99573.0     11          5   \n",
       "\n",
       "       year  week  day  quarter  dayofyear  Phase  Cashless  weekend  holiday  \n",
       "0      2010    53    1        1          1     -1         0        0        1  \n",
       "1      2010    53    2        1          2     -1         0        1        0  \n",
       "2      2010    53    3        1          3     -1         0        1        0  \n",
       "3      2010     1    4        1          4     -1         0        0        0  \n",
       "4      2010     1    5        1          5     -1         0        0        0  \n",
       "...     ...   ...  ...      ...        ...    ...       ...      ...      ...  \n",
       "71347  2020    45    3        4        308      7         1        0        0  \n",
       "71348  2020    45    4        4        309      7         1        0        0  \n",
       "71349  2020    45    5        4        310      7         1        0        0  \n",
       "71350  2020    45    6        4        311      7         1        0        0  \n",
       "71351  2020    45    7        4        312      7         1        1        0  \n",
       "\n",
       "[71352 rows x 15 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "_ender = return_series('mta_new.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "_bob = _ender.unstack().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "_bob = _bob['2020-11-8':]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>ezpass</th>\n",
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       "      <th>ezpass</th>\n",
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       "      <th>ezpass</th>\n",
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       "    <tr>\n",
       "      <th>datetime</th>\n",
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       "      <th></th>\n",
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       "      <th>2020-11-08</th>\n",
       "      <td>5782</td>\n",
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       "      <td>3221</td>\n",
       "      <td>16787</td>\n",
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       "      <th>2020-11-09</th>\n",
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       "      <td>10919</td>\n",
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       "      <td>95514</td>\n",
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       "      <th>2020-11-10</th>\n",
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       "      <td>2504</td>\n",
       "      <td>18046</td>\n",
       "      <td>11799</td>\n",
       "      <td>56147</td>\n",
       "      <td>14506</td>\n",
       "      <td>84070</td>\n",
       "      <td>25834</td>\n",
       "      <td>130327</td>\n",
       "      <td>11036</td>\n",
       "      <td>84512</td>\n",
       "      <td>20433</td>\n",
       "      <td>98639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-11</th>\n",
       "      <td>5956</td>\n",
       "      <td>41748</td>\n",
       "      <td>2776</td>\n",
       "      <td>15988</td>\n",
       "      <td>6458</td>\n",
       "      <td>45817</td>\n",
       "      <td>2199</td>\n",
       "      <td>15522</td>\n",
       "      <td>9496</td>\n",
       "      <td>47977</td>\n",
       "      <td>14111</td>\n",
       "      <td>80401</td>\n",
       "      <td>23371</td>\n",
       "      <td>118067</td>\n",
       "      <td>10080</td>\n",
       "      <td>75414</td>\n",
       "      <td>18112</td>\n",
       "      <td>87137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-12</th>\n",
       "      <td>6816</td>\n",
       "      <td>48087</td>\n",
       "      <td>3023</td>\n",
       "      <td>17871</td>\n",
       "      <td>7755</td>\n",
       "      <td>52239</td>\n",
       "      <td>2257</td>\n",
       "      <td>16448</td>\n",
       "      <td>11210</td>\n",
       "      <td>54770</td>\n",
       "      <td>14235</td>\n",
       "      <td>81909</td>\n",
       "      <td>25245</td>\n",
       "      <td>130829</td>\n",
       "      <td>10259</td>\n",
       "      <td>81774</td>\n",
       "      <td>19482</td>\n",
       "      <td>94821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-13</th>\n",
       "      <td>6947</td>\n",
       "      <td>45492</td>\n",
       "      <td>3280</td>\n",
       "      <td>18750</td>\n",
       "      <td>9110</td>\n",
       "      <td>56007</td>\n",
       "      <td>2346</td>\n",
       "      <td>16877</td>\n",
       "      <td>12872</td>\n",
       "      <td>56179</td>\n",
       "      <td>14537</td>\n",
       "      <td>80607</td>\n",
       "      <td>28045</td>\n",
       "      <td>137394</td>\n",
       "      <td>12038</td>\n",
       "      <td>86297</td>\n",
       "      <td>22796</td>\n",
       "      <td>104511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-14</th>\n",
       "      <td>5172</td>\n",
       "      <td>30314</td>\n",
       "      <td>2831</td>\n",
       "      <td>15664</td>\n",
       "      <td>8583</td>\n",
       "      <td>46044</td>\n",
       "      <td>2325</td>\n",
       "      <td>14535</td>\n",
       "      <td>11330</td>\n",
       "      <td>43878</td>\n",
       "      <td>17013</td>\n",
       "      <td>81312</td>\n",
       "      <td>27725</td>\n",
       "      <td>121172</td>\n",
       "      <td>12660</td>\n",
       "      <td>79945</td>\n",
       "      <td>22381</td>\n",
       "      <td>91399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-15</th>\n",
       "      <td>4174</td>\n",
       "      <td>24524</td>\n",
       "      <td>2298</td>\n",
       "      <td>12314</td>\n",
       "      <td>5216</td>\n",
       "      <td>32123</td>\n",
       "      <td>1775</td>\n",
       "      <td>11702</td>\n",
       "      <td>8499</td>\n",
       "      <td>33424</td>\n",
       "      <td>15505</td>\n",
       "      <td>71448</td>\n",
       "      <td>22649</td>\n",
       "      <td>98622</td>\n",
       "      <td>10752</td>\n",
       "      <td>65179</td>\n",
       "      <td>18308</td>\n",
       "      <td>75248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-16</th>\n",
       "      <td>6572</td>\n",
       "      <td>44653</td>\n",
       "      <td>2938</td>\n",
       "      <td>17138</td>\n",
       "      <td>6665</td>\n",
       "      <td>44355</td>\n",
       "      <td>2275</td>\n",
       "      <td>16529</td>\n",
       "      <td>10931</td>\n",
       "      <td>51627</td>\n",
       "      <td>13939</td>\n",
       "      <td>80344</td>\n",
       "      <td>25453</td>\n",
       "      <td>130314</td>\n",
       "      <td>10972</td>\n",
       "      <td>81787</td>\n",
       "      <td>19081</td>\n",
       "      <td>91469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-17</th>\n",
       "      <td>6585</td>\n",
       "      <td>46427</td>\n",
       "      <td>2935</td>\n",
       "      <td>17688</td>\n",
       "      <td>6478</td>\n",
       "      <td>46605</td>\n",
       "      <td>2222</td>\n",
       "      <td>16701</td>\n",
       "      <td>10816</td>\n",
       "      <td>52013</td>\n",
       "      <td>14109</td>\n",
       "      <td>82518</td>\n",
       "      <td>24194</td>\n",
       "      <td>126595</td>\n",
       "      <td>10615</td>\n",
       "      <td>83044</td>\n",
       "      <td>19109</td>\n",
       "      <td>94181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-18</th>\n",
       "      <td>6790</td>\n",
       "      <td>47507</td>\n",
       "      <td>2955</td>\n",
       "      <td>17883</td>\n",
       "      <td>7230</td>\n",
       "      <td>50306</td>\n",
       "      <td>2258</td>\n",
       "      <td>16948</td>\n",
       "      <td>11382</td>\n",
       "      <td>53809</td>\n",
       "      <td>13963</td>\n",
       "      <td>80775</td>\n",
       "      <td>25057</td>\n",
       "      <td>130667</td>\n",
       "      <td>10097</td>\n",
       "      <td>81846</td>\n",
       "      <td>19841</td>\n",
       "      <td>97064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-19</th>\n",
       "      <td>6844</td>\n",
       "      <td>48091</td>\n",
       "      <td>2968</td>\n",
       "      <td>17651</td>\n",
       "      <td>7440</td>\n",
       "      <td>52346</td>\n",
       "      <td>2279</td>\n",
       "      <td>16641</td>\n",
       "      <td>11963</td>\n",
       "      <td>56474</td>\n",
       "      <td>14290</td>\n",
       "      <td>83262</td>\n",
       "      <td>25744</td>\n",
       "      <td>134039</td>\n",
       "      <td>10859</td>\n",
       "      <td>84981</td>\n",
       "      <td>20501</td>\n",
       "      <td>99810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-20</th>\n",
       "      <td>7105</td>\n",
       "      <td>45276</td>\n",
       "      <td>3959</td>\n",
       "      <td>20387</td>\n",
       "      <td>8757</td>\n",
       "      <td>54876</td>\n",
       "      <td>2567</td>\n",
       "      <td>17637</td>\n",
       "      <td>12910</td>\n",
       "      <td>58731</td>\n",
       "      <td>16155</td>\n",
       "      <td>87244</td>\n",
       "      <td>28665</td>\n",
       "      <td>142007</td>\n",
       "      <td>12197</td>\n",
       "      <td>87479</td>\n",
       "      <td>22518</td>\n",
       "      <td>106153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-21</th>\n",
       "      <td>5748</td>\n",
       "      <td>32064</td>\n",
       "      <td>2916</td>\n",
       "      <td>15987</td>\n",
       "      <td>8906</td>\n",
       "      <td>48810</td>\n",
       "      <td>2265</td>\n",
       "      <td>14674</td>\n",
       "      <td>11610</td>\n",
       "      <td>45361</td>\n",
       "      <td>17102</td>\n",
       "      <td>80920</td>\n",
       "      <td>27336</td>\n",
       "      <td>119992</td>\n",
       "      <td>12203</td>\n",
       "      <td>78303</td>\n",
       "      <td>23540</td>\n",
       "      <td>96154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-22</th>\n",
       "      <td>4567</td>\n",
       "      <td>25260</td>\n",
       "      <td>2309</td>\n",
       "      <td>12620</td>\n",
       "      <td>5288</td>\n",
       "      <td>33088</td>\n",
       "      <td>1931</td>\n",
       "      <td>11587</td>\n",
       "      <td>8650</td>\n",
       "      <td>33275</td>\n",
       "      <td>15961</td>\n",
       "      <td>72482</td>\n",
       "      <td>21499</td>\n",
       "      <td>94900</td>\n",
       "      <td>10536</td>\n",
       "      <td>64510</td>\n",
       "      <td>19643</td>\n",
       "      <td>78586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-23</th>\n",
       "      <td>6645</td>\n",
       "      <td>44990</td>\n",
       "      <td>2911</td>\n",
       "      <td>16743</td>\n",
       "      <td>7511</td>\n",
       "      <td>48512</td>\n",
       "      <td>2212</td>\n",
       "      <td>15571</td>\n",
       "      <td>11529</td>\n",
       "      <td>53287</td>\n",
       "      <td>14529</td>\n",
       "      <td>80217</td>\n",
       "      <td>24880</td>\n",
       "      <td>127466</td>\n",
       "      <td>10582</td>\n",
       "      <td>78052</td>\n",
       "      <td>19651</td>\n",
       "      <td>93647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-24</th>\n",
       "      <td>7027</td>\n",
       "      <td>47910</td>\n",
       "      <td>3044</td>\n",
       "      <td>18088</td>\n",
       "      <td>8221</td>\n",
       "      <td>53319</td>\n",
       "      <td>2384</td>\n",
       "      <td>16959</td>\n",
       "      <td>10759</td>\n",
       "      <td>56423</td>\n",
       "      <td>15735</td>\n",
       "      <td>88075</td>\n",
       "      <td>27287</td>\n",
       "      <td>139090</td>\n",
       "      <td>11678</td>\n",
       "      <td>87216</td>\n",
       "      <td>20907</td>\n",
       "      <td>99653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-25</th>\n",
       "      <td>7119</td>\n",
       "      <td>46222</td>\n",
       "      <td>3360</td>\n",
       "      <td>18571</td>\n",
       "      <td>8540</td>\n",
       "      <td>52702</td>\n",
       "      <td>2380</td>\n",
       "      <td>17080</td>\n",
       "      <td>11543</td>\n",
       "      <td>56815</td>\n",
       "      <td>16582</td>\n",
       "      <td>87843</td>\n",
       "      <td>29181</td>\n",
       "      <td>143072</td>\n",
       "      <td>13157</td>\n",
       "      <td>93227</td>\n",
       "      <td>23138</td>\n",
       "      <td>106936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-26</th>\n",
       "      <td>3257</td>\n",
       "      <td>20349</td>\n",
       "      <td>2503</td>\n",
       "      <td>11704</td>\n",
       "      <td>4205</td>\n",
       "      <td>26785</td>\n",
       "      <td>1882</td>\n",
       "      <td>11551</td>\n",
       "      <td>5004</td>\n",
       "      <td>23543</td>\n",
       "      <td>14589</td>\n",
       "      <td>68129</td>\n",
       "      <td>19439</td>\n",
       "      <td>87853</td>\n",
       "      <td>11211</td>\n",
       "      <td>70145</td>\n",
       "      <td>18604</td>\n",
       "      <td>74948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-27</th>\n",
       "      <td>4962</td>\n",
       "      <td>27894</td>\n",
       "      <td>2973</td>\n",
       "      <td>15903</td>\n",
       "      <td>6402</td>\n",
       "      <td>36352</td>\n",
       "      <td>2278</td>\n",
       "      <td>14975</td>\n",
       "      <td>8431</td>\n",
       "      <td>34909</td>\n",
       "      <td>16214</td>\n",
       "      <td>79150</td>\n",
       "      <td>24447</td>\n",
       "      <td>106695</td>\n",
       "      <td>11881</td>\n",
       "      <td>74174</td>\n",
       "      <td>21132</td>\n",
       "      <td>88829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-28</th>\n",
       "      <td>4941</td>\n",
       "      <td>25028</td>\n",
       "      <td>2694</td>\n",
       "      <td>14066</td>\n",
       "      <td>6976</td>\n",
       "      <td>37520</td>\n",
       "      <td>1999</td>\n",
       "      <td>12967</td>\n",
       "      <td>8736</td>\n",
       "      <td>34255</td>\n",
       "      <td>16429</td>\n",
       "      <td>76296</td>\n",
       "      <td>25020</td>\n",
       "      <td>103946</td>\n",
       "      <td>11743</td>\n",
       "      <td>70315</td>\n",
       "      <td>21395</td>\n",
       "      <td>85478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-29</th>\n",
       "      <td>4513</td>\n",
       "      <td>24851</td>\n",
       "      <td>2586</td>\n",
       "      <td>12821</td>\n",
       "      <td>6156</td>\n",
       "      <td>35830</td>\n",
       "      <td>1945</td>\n",
       "      <td>12617</td>\n",
       "      <td>8650</td>\n",
       "      <td>35704</td>\n",
       "      <td>16348</td>\n",
       "      <td>75372</td>\n",
       "      <td>23932</td>\n",
       "      <td>102864</td>\n",
       "      <td>11568</td>\n",
       "      <td>65857</td>\n",
       "      <td>21114</td>\n",
       "      <td>84827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-30</th>\n",
       "      <td>5455</td>\n",
       "      <td>38532</td>\n",
       "      <td>2510</td>\n",
       "      <td>14433</td>\n",
       "      <td>5800</td>\n",
       "      <td>39934</td>\n",
       "      <td>1876</td>\n",
       "      <td>12999</td>\n",
       "      <td>8844</td>\n",
       "      <td>47662</td>\n",
       "      <td>12220</td>\n",
       "      <td>68419</td>\n",
       "      <td>22097</td>\n",
       "      <td>114627</td>\n",
       "      <td>8912</td>\n",
       "      <td>64256</td>\n",
       "      <td>18059</td>\n",
       "      <td>86419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-01</th>\n",
       "      <td>6506</td>\n",
       "      <td>43922</td>\n",
       "      <td>2872</td>\n",
       "      <td>16847</td>\n",
       "      <td>6508</td>\n",
       "      <td>45046</td>\n",
       "      <td>2157</td>\n",
       "      <td>15951</td>\n",
       "      <td>9924</td>\n",
       "      <td>52819</td>\n",
       "      <td>13962</td>\n",
       "      <td>78577</td>\n",
       "      <td>24759</td>\n",
       "      <td>127648</td>\n",
       "      <td>25013</td>\n",
       "      <td>168230</td>\n",
       "      <td>19013</td>\n",
       "      <td>92265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-02</th>\n",
       "      <td>6550</td>\n",
       "      <td>44939</td>\n",
       "      <td>2896</td>\n",
       "      <td>16893</td>\n",
       "      <td>6676</td>\n",
       "      <td>45400</td>\n",
       "      <td>2061</td>\n",
       "      <td>15732</td>\n",
       "      <td>10256</td>\n",
       "      <td>52570</td>\n",
       "      <td>13476</td>\n",
       "      <td>77287</td>\n",
       "      <td>24046</td>\n",
       "      <td>125363</td>\n",
       "      <td>23950</td>\n",
       "      <td>166103</td>\n",
       "      <td>19253</td>\n",
       "      <td>93345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-03</th>\n",
       "      <td>6746</td>\n",
       "      <td>44705</td>\n",
       "      <td>2971</td>\n",
       "      <td>17272</td>\n",
       "      <td>6646</td>\n",
       "      <td>47020</td>\n",
       "      <td>2185</td>\n",
       "      <td>16164</td>\n",
       "      <td>10313</td>\n",
       "      <td>54187</td>\n",
       "      <td>14432</td>\n",
       "      <td>81453</td>\n",
       "      <td>25012</td>\n",
       "      <td>128702</td>\n",
       "      <td>24646</td>\n",
       "      <td>170814</td>\n",
       "      <td>19308</td>\n",
       "      <td>94703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-04</th>\n",
       "      <td>6341</td>\n",
       "      <td>41531</td>\n",
       "      <td>3089</td>\n",
       "      <td>17642</td>\n",
       "      <td>7713</td>\n",
       "      <td>48878</td>\n",
       "      <td>2336</td>\n",
       "      <td>15763</td>\n",
       "      <td>11006</td>\n",
       "      <td>56159</td>\n",
       "      <td>15258</td>\n",
       "      <td>82066</td>\n",
       "      <td>26088</td>\n",
       "      <td>130579</td>\n",
       "      <td>25329</td>\n",
       "      <td>166370</td>\n",
       "      <td>21080</td>\n",
       "      <td>98436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-05</th>\n",
       "      <td>4430</td>\n",
       "      <td>24171</td>\n",
       "      <td>2410</td>\n",
       "      <td>13358</td>\n",
       "      <td>5149</td>\n",
       "      <td>30573</td>\n",
       "      <td>1701</td>\n",
       "      <td>11157</td>\n",
       "      <td>8025</td>\n",
       "      <td>33663</td>\n",
       "      <td>13832</td>\n",
       "      <td>62056</td>\n",
       "      <td>20891</td>\n",
       "      <td>92143</td>\n",
       "      <td>22988</td>\n",
       "      <td>132444</td>\n",
       "      <td>18458</td>\n",
       "      <td>75063</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "plaza_id   Brooklyn Battery        Cross Bay        Henry Hudson         \\\n",
       "variable               cash ezpass      cash ezpass         cash ezpass   \n",
       "datetime                                                                  \n",
       "2020-11-08             5782  32749      3221  16787         7893  45602   \n",
       "2020-11-09             6701  45059      3217  18435         7904  51293   \n",
       "2020-11-10             7080  48714      3328  18741         7941  53346   \n",
       "2020-11-11             5956  41748      2776  15988         6458  45817   \n",
       "2020-11-12             6816  48087      3023  17871         7755  52239   \n",
       "2020-11-13             6947  45492      3280  18750         9110  56007   \n",
       "2020-11-14             5172  30314      2831  15664         8583  46044   \n",
       "2020-11-15             4174  24524      2298  12314         5216  32123   \n",
       "2020-11-16             6572  44653      2938  17138         6665  44355   \n",
       "2020-11-17             6585  46427      2935  17688         6478  46605   \n",
       "2020-11-18             6790  47507      2955  17883         7230  50306   \n",
       "2020-11-19             6844  48091      2968  17651         7440  52346   \n",
       "2020-11-20             7105  45276      3959  20387         8757  54876   \n",
       "2020-11-21             5748  32064      2916  15987         8906  48810   \n",
       "2020-11-22             4567  25260      2309  12620         5288  33088   \n",
       "2020-11-23             6645  44990      2911  16743         7511  48512   \n",
       "2020-11-24             7027  47910      3044  18088         8221  53319   \n",
       "2020-11-25             7119  46222      3360  18571         8540  52702   \n",
       "2020-11-26             3257  20349      2503  11704         4205  26785   \n",
       "2020-11-27             4962  27894      2973  15903         6402  36352   \n",
       "2020-11-28             4941  25028      2694  14066         6976  37520   \n",
       "2020-11-29             4513  24851      2586  12821         6156  35830   \n",
       "2020-11-30             5455  38532      2510  14433         5800  39934   \n",
       "2020-12-01             6506  43922      2872  16847         6508  45046   \n",
       "2020-12-02             6550  44939      2896  16893         6676  45400   \n",
       "2020-12-03             6746  44705      2971  17272         6646  47020   \n",
       "2020-12-04             6341  41531      3089  17642         7713  48878   \n",
       "2020-12-05             4430  24171      2410  13358         5149  30573   \n",
       "\n",
       "plaza_id   Marine Parkway        Queens Midtown        Throgs Neck         \\\n",
       "variable             cash ezpass           cash ezpass        cash ezpass   \n",
       "datetime                                                                    \n",
       "2020-11-08           2628  16636          10345  40539       18365  88748   \n",
       "2020-11-09           2446  17471          10793  51311       14406  82218   \n",
       "2020-11-10           2504  18046          11799  56147       14506  84070   \n",
       "2020-11-11           2199  15522           9496  47977       14111  80401   \n",
       "2020-11-12           2257  16448          11210  54770       14235  81909   \n",
       "2020-11-13           2346  16877          12872  56179       14537  80607   \n",
       "2020-11-14           2325  14535          11330  43878       17013  81312   \n",
       "2020-11-15           1775  11702           8499  33424       15505  71448   \n",
       "2020-11-16           2275  16529          10931  51627       13939  80344   \n",
       "2020-11-17           2222  16701          10816  52013       14109  82518   \n",
       "2020-11-18           2258  16948          11382  53809       13963  80775   \n",
       "2020-11-19           2279  16641          11963  56474       14290  83262   \n",
       "2020-11-20           2567  17637          12910  58731       16155  87244   \n",
       "2020-11-21           2265  14674          11610  45361       17102  80920   \n",
       "2020-11-22           1931  11587           8650  33275       15961  72482   \n",
       "2020-11-23           2212  15571          11529  53287       14529  80217   \n",
       "2020-11-24           2384  16959          10759  56423       15735  88075   \n",
       "2020-11-25           2380  17080          11543  56815       16582  87843   \n",
       "2020-11-26           1882  11551           5004  23543       14589  68129   \n",
       "2020-11-27           2278  14975           8431  34909       16214  79150   \n",
       "2020-11-28           1999  12967           8736  34255       16429  76296   \n",
       "2020-11-29           1945  12617           8650  35704       16348  75372   \n",
       "2020-11-30           1876  12999           8844  47662       12220  68419   \n",
       "2020-12-01           2157  15951           9924  52819       13962  78577   \n",
       "2020-12-02           2061  15732          10256  52570       13476  77287   \n",
       "2020-12-03           2185  16164          10313  54187       14432  81453   \n",
       "2020-12-04           2336  15763          11006  56159       15258  82066   \n",
       "2020-12-05           1701  11157           8025  33663       13832  62056   \n",
       "\n",
       "plaza_id   Triboro         Verrazano         Whitestone          \n",
       "variable      cash  ezpass      cash  ezpass       cash  ezpass  \n",
       "datetime                                                         \n",
       "2020-11-08   25735  113706     12493   73988      22722   93990  \n",
       "2020-11-09   26177  129507     10919   80539      19796   95514  \n",
       "2020-11-10   25834  130327     11036   84512      20433   98639  \n",
       "2020-11-11   23371  118067     10080   75414      18112   87137  \n",
       "2020-11-12   25245  130829     10259   81774      19482   94821  \n",
       "2020-11-13   28045  137394     12038   86297      22796  104511  \n",
       "2020-11-14   27725  121172     12660   79945      22381   91399  \n",
       "2020-11-15   22649   98622     10752   65179      18308   75248  \n",
       "2020-11-16   25453  130314     10972   81787      19081   91469  \n",
       "2020-11-17   24194  126595     10615   83044      19109   94181  \n",
       "2020-11-18   25057  130667     10097   81846      19841   97064  \n",
       "2020-11-19   25744  134039     10859   84981      20501   99810  \n",
       "2020-11-20   28665  142007     12197   87479      22518  106153  \n",
       "2020-11-21   27336  119992     12203   78303      23540   96154  \n",
       "2020-11-22   21499   94900     10536   64510      19643   78586  \n",
       "2020-11-23   24880  127466     10582   78052      19651   93647  \n",
       "2020-11-24   27287  139090     11678   87216      20907   99653  \n",
       "2020-11-25   29181  143072     13157   93227      23138  106936  \n",
       "2020-11-26   19439   87853     11211   70145      18604   74948  \n",
       "2020-11-27   24447  106695     11881   74174      21132   88829  \n",
       "2020-11-28   25020  103946     11743   70315      21395   85478  \n",
       "2020-11-29   23932  102864     11568   65857      21114   84827  \n",
       "2020-11-30   22097  114627      8912   64256      18059   86419  \n",
       "2020-12-01   24759  127648     25013  168230      19013   92265  \n",
       "2020-12-02   24046  125363     23950  166103      19253   93345  \n",
       "2020-12-03   25012  128702     24646  170814      19308   94703  \n",
       "2020-12-04   26088  130579     25329  166370      21080   98436  \n",
       "2020-12-05   20891   92143     22988  132444      18458   75063  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_bob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "_bob.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "_bob = pd.melt(_bob,id_vars=['datetime'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>datetime</th>\n",
       "      <th>crossing</th>\n",
       "      <th>variation</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-11-08</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>5782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-11-09</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>6701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-11-10</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>7080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-11-11</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>5956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-11-12</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>6816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>2020-12-01</td>\n",
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       "      <td>ezpass</td>\n",
       "      <td>92265</td>\n",
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       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>2020-12-02</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>93345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>2020-12-03</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>94703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>98436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>2020-12-05</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>75063</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>504 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      datetime          crossing variation  count\n",
       "0   2020-11-08  Brooklyn Battery      cash   5782\n",
       "1   2020-11-09  Brooklyn Battery      cash   6701\n",
       "2   2020-11-10  Brooklyn Battery      cash   7080\n",
       "3   2020-11-11  Brooklyn Battery      cash   5956\n",
       "4   2020-11-12  Brooklyn Battery      cash   6816\n",
       "..         ...               ...       ...    ...\n",
       "499 2020-12-01        Whitestone    ezpass  92265\n",
       "500 2020-12-02        Whitestone    ezpass  93345\n",
       "501 2020-12-03        Whitestone    ezpass  94703\n",
       "502 2020-12-04        Whitestone    ezpass  98436\n",
       "503 2020-12-05        Whitestone    ezpass  75063\n",
       "\n",
       "[504 rows x 4 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_bob.columns = ['datetime', 'crossing', 'variation', 'count']\n",
    "_bob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-11-09</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>6701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-11-10</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>7080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-11-11</td>\n",
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       "      <td>6816</td>\n",
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       "    <tr>\n",
       "      <th>499</th>\n",
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       "      <td>ezpass</td>\n",
       "      <td>92265</td>\n",
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       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>2020-12-02</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>93345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>2020-12-03</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>94703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>98436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>2020-12-05</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>75063</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>504 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      datetime          crossing variation  count\n",
       "0   2020-11-08  Brooklyn Battery      cash   5782\n",
       "1   2020-11-09  Brooklyn Battery      cash   6701\n",
       "2   2020-11-10  Brooklyn Battery      cash   7080\n",
       "3   2020-11-11  Brooklyn Battery      cash   5956\n",
       "4   2020-11-12  Brooklyn Battery      cash   6816\n",
       "..         ...               ...       ...    ...\n",
       "499 2020-12-01        Whitestone    ezpass  92265\n",
       "500 2020-12-02        Whitestone    ezpass  93345\n",
       "501 2020-12-03        Whitestone    ezpass  94703\n",
       "502 2020-12-04        Whitestone    ezpass  98436\n",
       "503 2020-12-05        Whitestone    ezpass  75063\n",
       "\n",
       "[504 rows x 4 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_bob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "_bob.set_index('datetime', inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "_bob = date_features(_bob)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "_bob.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>week</th>\n",
       "      <th>day</th>\n",
       "      <th>quarter</th>\n",
       "      <th>dayofyear</th>\n",
       "      <th>Phase</th>\n",
       "      <th>Cashless</th>\n",
       "      <th>weekend</th>\n",
       "      <th>holiday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-11-08</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>5782</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>2020</td>\n",
       "      <td>45</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-11-09</td>\n",
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       "      <td>cash</td>\n",
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       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>2020</td>\n",
       "      <td>46</td>\n",
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       "      <td>4</td>\n",
       "      <td>314</td>\n",
       "      <td>7</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-11-10</td>\n",
       "      <td>Brooklyn Battery</td>\n",
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       "      <td>7080</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>2020</td>\n",
       "      <td>46</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>315</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-11-11</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>5956</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>2020</td>\n",
       "      <td>46</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>316</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-11-12</td>\n",
       "      <td>Brooklyn Battery</td>\n",
       "      <td>cash</td>\n",
       "      <td>6816</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>2020</td>\n",
       "      <td>46</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>317</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>2020-12-01</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>92265</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>2020</td>\n",
       "      <td>49</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>336</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>2020-12-02</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>93345</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>2020</td>\n",
       "      <td>49</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>337</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>2020-12-03</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>94703</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>2020</td>\n",
       "      <td>49</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>338</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>98436</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>2020</td>\n",
       "      <td>49</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>339</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>2020-12-05</td>\n",
       "      <td>Whitestone</td>\n",
       "      <td>ezpass</td>\n",
       "      <td>75063</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>2020</td>\n",
       "      <td>49</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>340</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>504 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      datetime          crossing variation  count  month  dayofweek  year  \\\n",
       "0   2020-11-08  Brooklyn Battery      cash   5782     11          6  2020   \n",
       "1   2020-11-09  Brooklyn Battery      cash   6701     11          0  2020   \n",
       "2   2020-11-10  Brooklyn Battery      cash   7080     11          1  2020   \n",
       "3   2020-11-11  Brooklyn Battery      cash   5956     11          2  2020   \n",
       "4   2020-11-12  Brooklyn Battery      cash   6816     11          3  2020   \n",
       "..         ...               ...       ...    ...    ...        ...   ...   \n",
       "499 2020-12-01        Whitestone    ezpass  92265     12          1  2020   \n",
       "500 2020-12-02        Whitestone    ezpass  93345     12          2  2020   \n",
       "501 2020-12-03        Whitestone    ezpass  94703     12          3  2020   \n",
       "502 2020-12-04        Whitestone    ezpass  98436     12          4  2020   \n",
       "503 2020-12-05        Whitestone    ezpass  75063     12          5  2020   \n",
       "\n",
       "     week  day  quarter  dayofyear  Phase  Cashless  weekend  holiday  \n",
       "0      45    8        4        313      7         1        1        0  \n",
       "1      46    9        4        314      7         1        0        0  \n",
       "2      46   10        4        315      7         1        0        0  \n",
       "3      46   11        4        316      7         1        0        1  \n",
       "4      46   12        4        317      7         1        0        0  \n",
       "..    ...  ...      ...        ...    ...       ...      ...      ...  \n",
       "499    49    1        4        336      7         1        0        0  \n",
       "500    49    2        4        337      7         1        0        0  \n",
       "501    49    3        4        338      7         1        0        0  \n",
       "502    49    4        4        339      7         1        0        0  \n",
       "503    49    5        4        340      7         1        1        0  \n",
       "\n",
       "[504 rows x 15 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_bob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\albert\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df['datetime'] = pd.to_datetime(df['datetime'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>datetime</th>\n",
       "      <th>crossing</th>\n",
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       "      <td>2010-01-01</td>\n",
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       "      <td>4902.0</td>\n",
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       "      <td>2010-01-05</td>\n",
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       "      <td>6096.0</td>\n",
       "      <td>1</td>\n",
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       "      <th>499</th>\n",
       "      <td>2020-12-01</td>\n",
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       "      <td>ezpass</td>\n",
       "      <td>92265.0</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
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       "      <td>ezpass</td>\n",
       "      <td>75063.0</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>2020</td>\n",
       "      <td>49</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>340</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>71856 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      datetime          crossing variation    count  month  dayofweek  year  \\\n",
       "0   2010-01-01  Brooklyn Battery      cash   4902.0      1          4  2010   \n",
       "1   2010-01-02  Brooklyn Battery      cash   5347.0      1          5  2010   \n",
       "2   2010-01-03  Brooklyn Battery      cash   4957.0      1          6  2010   \n",
       "3   2010-01-04  Brooklyn Battery      cash   5759.0      1          0  2010   \n",
       "4   2010-01-05  Brooklyn Battery      cash   6096.0      1          1  2010   \n",
       "..         ...               ...       ...      ...    ...        ...   ...   \n",
       "499 2020-12-01        Whitestone    ezpass  92265.0     12          1  2020   \n",
       "500 2020-12-02        Whitestone    ezpass  93345.0     12          2  2020   \n",
       "501 2020-12-03        Whitestone    ezpass  94703.0     12          3  2020   \n",
       "502 2020-12-04        Whitestone    ezpass  98436.0     12          4  2020   \n",
       "503 2020-12-05        Whitestone    ezpass  75063.0     12          5  2020   \n",
       "\n",
       "     week  day  quarter  dayofyear  Phase  Cashless  weekend  holiday  \n",
       "0      53    1        1          1     -1         0        0        1  \n",
       "1      53    2        1          2     -1         0        1        0  \n",
       "2      53    3        1          3     -1         0        1        0  \n",
       "3       1    4        1          4     -1         0        0        0  \n",
       "4       1    5        1          5     -1         0        0        0  \n",
       "..    ...  ...      ...        ...    ...       ...      ...      ...  \n",
       "499    49    1        4        336      7         1        0        0  \n",
       "500    49    2        4        337      7         1        0        0  \n",
       "501    49    3        4        338      7         1        0        0  \n",
       "502    49    4        4        339      7         1        0        0  \n",
       "503    49    5        4        340      7         1        1        0  \n",
       "\n",
       "[71856 rows x 15 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_final = pd.concat([df,_bob])\n",
    "_final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "_final.to_csv('to_tableau.csv', index=False,header=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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