paulegan/Location History.ipynb

## Location History.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploring Google's Location History\n",
    "\n",
    "\n",
    "## Download data\n",
    "\n",
    "Follow the Google \"Takeout\" instructions and get the `JSON` format file for \"Location History\":\n",
    "\n",
    "https://support.google.com/accounts/answer/3024190?hl=en\n",
    "\n",
    "\n",
    "Unzip and ensure that `LOCATION_HISTORY_JSON` refers to that downloaded file.\n",
    "\n",
    "## GMaps API Key\n",
    "\n",
    "GMaps needs an API key for rendering Google maps. Follow these instructions and put the key in your env:\n",
    "\n",
    "https://jupyter-gmaps.readthedocs.io/en/stable/authentication.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import os\n",
    "\n",
    "MAPS_API_KEY = os.environ['GOOGLE_API_KEY']\n",
    "LOCATION_HISTORY_JSON = './Location History.json'\n",
    "\n",
    "WORK_LAT_LONG = 51.5016264, -0.1903144\n",
    "# Hard-coded center of our geo-fence, but could also used Google geocoder like this:\n",
    "# from geopy.geocoders import GoogleV3\n",
    "# GoogleV3().geocode('Founders Factory, London')\n",
    "\n",
    "\n",
    "DX, DY = 0.0008, 0.0012\n",
    "WORK_GEO_FENCE = [\n",
    "    (WORK_LAT_LONG[0] - DX, WORK_LAT_LONG[1] - DY),\n",
    "    (WORK_LAT_LONG[0] + DX, WORK_LAT_LONG[1] - DY),\n",
    "    (WORK_LAT_LONG[0] + DX, WORK_LAT_LONG[1] + DY),\n",
    "    (WORK_LAT_LONG[0] - DX, WORK_LAT_LONG[1] + DY),\n",
    "]\n",
    "# Hard-coded size again, but could also used Shapely buffer like this:\n",
    "# from shapely.geometry import Point, CAP_STYLE\n",
    "# fence = Point(WORK_LAT_LONG).buffer(0.001, cap_style=CAP_STYLE.square)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert JSON locations to DataFrame with Datetime index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import json\n",
    "\n",
    "with open(LOCATION_HISTORY_JSON) as f:\n",
    "    locations = json.load(f)['locations']\n",
    "    \n",
    "timestamps, latitudes, longitudes = zip(*[\n",
    "    (int(l['timestampMs']), float(l['latitudeE7']) / 10000000, float(l['longitudeE7']) / 10000000)\n",
    "    for l in locations\n",
    "])\n",
    "df = pd.DataFrame({'timestamp': timestamps, 'latitude': latitudes, 'longitude': longitudes})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-06-17 20:32:14.989</th>\n",
       "      <td>1529267534989</td>\n",
       "      <td>51.519908</td>\n",
       "      <td>-0.324779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-17 20:27:12.941</th>\n",
       "      <td>1529267232941</td>\n",
       "      <td>51.519908</td>\n",
       "      <td>-0.324779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-17 20:26:56.563</th>\n",
       "      <td>1529267216563</td>\n",
       "      <td>51.519908</td>\n",
       "      <td>-0.324779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-17 20:25:12.887</th>\n",
       "      <td>1529267112887</td>\n",
       "      <td>51.519908</td>\n",
       "      <td>-0.324779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-17 20:23:12.878</th>\n",
       "      <td>1529266992878</td>\n",
       "      <td>51.519908</td>\n",
       "      <td>-0.324779</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             timestamp   latitude  longitude\n",
       "datetime                                                    \n",
       "2018-06-17 20:32:14.989  1529267534989  51.519908  -0.324779\n",
       "2018-06-17 20:27:12.941  1529267232941  51.519908  -0.324779\n",
       "2018-06-17 20:26:56.563  1529267216563  51.519908  -0.324779\n",
       "2018-06-17 20:25:12.887  1529267112887  51.519908  -0.324779\n",
       "2018-06-17 20:23:12.878  1529266992878  51.519908  -0.324779"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.assign(datetime=pd.DatetimeIndex(pd.to_datetime(df.timestamp, unit='ms')))\n",
    "df = df.set_index('datetime')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Looking at how many locations were logged over time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.groupby(df.index.year).count().timestamp.plot.bar(color='cyan', width=0.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "count_by_date = df.groupby(df.index.date).count().timestamp\n",
    "ax = count_by_date.plot.hist(color='cyan')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2017-01-03    2026\n",
       "2017-01-15    2104\n",
       "2016-12-31    2131\n",
       "2016-12-30    2296\n",
       "2017-03-29    2343\n",
       "Name: timestamp, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_by_date.sort_values().tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add a new `at_work` column for locations within the geo-fence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((124957, 4), (846536, 4))"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['at_work'] = (\n",
    "    (df.latitude > WORK_GEO_FENCE[0][0]) &\n",
    "    (df.latitude < WORK_GEO_FENCE[2][0]) &\n",
    "    (df.longitude > WORK_GEO_FENCE[0][1]) &\n",
    "    (df.longitude < WORK_GEO_FENCE[2][1])\n",
    ")\n",
    "df[df.at_work].shape, df[df.at_work == False].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting using `gmaps`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c693871574aa41c2bbf5279bf21de3ac",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import gmaps\n",
    "gmaps.configure(api_key=MAPS_API_KEY)\n",
    "\n",
    "fig = gmaps.figure()\n",
    "fig.add_layer(gmaps.symbol_layer(WORK_GEO_FENCE))\n",
    "fig.add_layer(gmaps.drawing_layer(features=[\n",
    "    gmaps.Marker(WORK_LAT_LONG, label='W'),\n",
    "    gmaps.Polygon(WORK_GEO_FENCE, fill_color='blue')\n",
    "]))\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "16b5507c34154c78b6da23aeedc19168",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Looking at a (not so) random day, are the locations correctly categorised as `at_work` ?\n",
    "\n",
    "random_day = df['2018-06-12']\n",
    "\n",
    "fig = gmaps.figure()\n",
    "fig.add_layer(gmaps.symbol_layer(random_day[random_day.at_work][['latitude', 'longitude']], stroke_color='yellow', stroke_opacity=0.5))\n",
    "fig.add_layer(gmaps.symbol_layer(random_day[random_day.at_work == False][['latitude', 'longitude']], stroke_color='red', stroke_opacity=0.5))\n",
    "fig.add_layer(gmaps.marker_layer([random_day.between_time('14:00', '15:00')[['latitude', 'longitude']].mean()]))\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create new `times_by_date` DataFrame, mapping date to number of hours at work\n",
    "\n",
    "Iterate over all rows, recording \"time in\" and \"time out\", and sum up the number of minutes for each date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "series = df[:'2017'].sort_index(ascending=True)\n",
    "\n",
    "dindex = pd.date_range(series.index[0].date(), series.index[-1].date())\n",
    "times_by_date = pd.DataFrame({'minutes': np.zeros(len(dindex), dtype=int)}, index=dindex)\n",
    "\n",
    "at_work_prev = False\n",
    "\n",
    "for ts, at_work_cur in zip(series.index, series.at_work):\n",
    "    if at_work_cur == True and at_work_prev == False:\n",
    "        time_in = ts\n",
    "    if at_work_cur == False and at_work_prev == True:\n",
    "        d = int((ts - time_in).total_seconds() / 60)\n",
    "        times_by_date.loc[time_in.date(), 'minutes'] += d\n",
    "    at_work_prev = at_work_cur\n",
    "\n",
    "times_by_date['hours'] = times_by_date.minutes / 60"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Examining general statistics for time spend at work"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>minutes</th>\n",
       "      <th>hours</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>339.000000</td>\n",
       "      <td>339.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>573.964602</td>\n",
       "      <td>9.566077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>159.727704</td>\n",
       "      <td>2.662128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>528.000000</td>\n",
       "      <td>8.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>601.000000</td>\n",
       "      <td>10.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>665.500000</td>\n",
       "      <td>11.091667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>905.000000</td>\n",
       "      <td>15.083333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          minutes       hours\n",
       "count  339.000000  339.000000\n",
       "mean   573.964602    9.566077\n",
       "std    159.727704    2.662128\n",
       "min      3.000000    0.050000\n",
       "25%    528.000000    8.800000\n",
       "50%    601.000000   10.016667\n",
       "75%    665.500000   11.091667\n",
       "max    905.000000   15.083333"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = times_by_date[times_by_date.minutes > 0]\n",
    "\n",
    "t.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "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>minutes</th>\n",
       "      <th>hours</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-03-13</th>\n",
       "      <td>833</td>\n",
       "      <td>13.883333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-17</th>\n",
       "      <td>839</td>\n",
       "      <td>13.983333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-03</th>\n",
       "      <td>861</td>\n",
       "      <td>14.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-07</th>\n",
       "      <td>896</td>\n",
       "      <td>14.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-12</th>\n",
       "      <td>905</td>\n",
       "      <td>15.083333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            minutes      hours\n",
       "2018-03-13      833  13.883333\n",
       "2017-05-17      839  13.983333\n",
       "2017-11-03      861  14.350000\n",
       "2018-02-07      896  14.933333\n",
       "2018-06-12      905  15.083333"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t.sort_values('hours').tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting mean time at work, by month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "d = t.resample('M').mean()\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(16,8))\n",
    "ax.bar(d.index, d.hours, width=25, color='cyan')\n",
    "ax.xaxis.set_major_locator(mdates.MonthLocator())\n",
    "ax.xaxis.set_major_formatter(mdates.DateFormatter('%b %Y'))\n",
    "ax.xaxis.set_tick_params(rotation=70)\n",
    "\n",
    "for patch, value in zip(ax.patches, d.hours.values):\n",
    "    ax.text(patch.get_x() + patch.get_width() / 2, patch.get_height(), '%.1f' % value, ha='center', va='bottom')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting stats of time at work, by day of the week"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import calendar\n",
    "\n",
    "d = times_by_date.groupby(times_by_date.index.dayofweek).hours.mean()\n",
    "ax = d.plot.bar(color='cyan', width=0.9, figsize=(16,8))\n",
    "\n",
    "ax.set_xticklabels(calendar.day_abbr)\n",
    "for patch, value in zip(ax.patches, d.values):\n",
    "    ax.text(patch.get_x() + patch.get_width() / 2, patch.get_height(), '%.1f' % value, ha='center', va='bottom')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "fig, ax = plt.subplots(figsize=(16,8))\n",
    "\n",
    "boxes = times_by_date.boxplot(\n",
    "    column='hours',\n",
    "    by=times_by_date.index.dayofweek,\n",
    "    grid=False,\n",
    "    notch=True,\n",
    "    patch_artist=True,\n",
    "    flierprops=dict(markerfacecolor='cyan', markeredgewidth=0),\n",
    "    boxprops=dict(color='cyan'),\n",
    "    ax=ax,\n",
    "    return_type='dict'\n",
    ")\n",
    "ax.set_xticklabels(calendar.day_abbr)\n",
    "ax.set_xlabel('')\n",
    "ax.set_title('Hours at work, by day of the week')\n",
    "fig.suptitle('')\n",
    "\n",
    "# boxprops argument above doesn't seem to work. Dunno why!\n",
    "for box in boxes.hours['boxes']:\n",
    "    box.set_color('cyan')\n",
    "\n",
    "for line in boxes.hours['medians']:\n",
    "    x, y = line.get_xydata()[0]\n",
    "    ax.text(x + 0.125, y, '%.1f' % y, ha='center', va='bottom')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## General plots on time at work"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYMAAAD8CAYAAACVZ8iyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAADgRJREFUeJzt3X1snIddwPHv7+ybszYpSRrHCXWS80q1uY6gawPamNgkBk23VWslkLqJdR0gIUWkbKhoa7AEEy9jCMKGNEQ1Cu3CmqBRNqgmXlr1gGJpA5J2bdMWaClbl9LSTlBAGeBl+/HHPXbO57PvnDh+7nzfj3TK8zx+fPfLcy9f351fIjORJA22StkDSJLKZwwkScZAkmQMJEkYA0kSxkCShDGQJGEMJEkYA0kSMFz2AN3atm1b1mq1sseQpL5y4sSJr2XmaKf9+iYGtVqN48ePlz2GJPWViPhKN/v5MpEkyRhIkoyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJIyBJAljIEnCGEiSMAaSJGC47AEkdfZh4E9X+TyvBO4Cos3HngV+FPifVbicDwI/vArnowvLGEh94PdpPECvpieBdwP723zsQ8AM8K1VuJz7MAb9wJeJpAF1msZX7dmy/Vng86xOCNQ/jIE0wP4Z+OuWbR8Gzqz9KCqZMZAG2Gng9qb1U8AfYgwGkTGQBtzjwBeK5V8EvlniLCqPMZAG3NeBQ8CLwBHgG+WOo5IYA0n8HfBeFr+ZrMHht5ZK4n+BB/E7iAaZzwzUl9r9oJTOXWIILrRev80aA0mSMZAkGQNJEl3EICJqEXFyLYaRJJWjlGcGEbFm38W0f/9+ImLR6dJLL+XYsWOL9j927Bh79+5laGiIXbt2sWvXrkXLe/fu5dZbb+1qv06XMbdPu20rNXcelUqFDRs2UKlUOs7Qad9u51rquDUfq0qlwvDwcFfXgzSolrsvXdD7SmYuewJqwFPA7wBPAPcDrwauAr4IPAZ8DthS7P9XwL5ieRvw5WL5fTR+gWGdxq9D2Qk8BHwJOAl833JzXHPNNblS1157bQJZrVYzIrJarSaQw8PDGRG5adOmPHr06Pz+R48ezYmJiazX63nkyJHcuXNn7tixIw8cOJA7duzInTt35pEjR3J6ejqHh4dzenp60X5zy0eOHMl6vZ4TExNLXsbs7GzW6/UcHR3N0dHRBdtaP6+TufOdnp7OiYmJPHz4cNZqtfn1djNMT09nrVbLw4cPL/jcuX3bzdpurtbj1u5Y3Xjjjblx48YEslKp5E033ZSbN2/OiMhLLrlkRf/XzMaNYpC8JjvcUXv4dPMFOB79qJvb7FKPQUs9nnR1uXA8u7iquo3BGeCqYv0zwHuKCLyl2PYLwMezcwxOAVuL9duA6WJ5CNi03BznEoOIyC1btmS1Ws2xsbGs1+t54MCBBHJsbCyr1WpOTU3N7z81NZX1en3Bcr1ez5GRkfnlqampnJqaysOHD88vL7VfZi5Ybr2MObVaLWu12oJtrZ/Xydz5Np9/83q7GTrt227WdnMtddyaj9XIyEhWq9XcsWPH/LGr1+ttr4duGIP+ORmDhm5us8vdlzJX/riQufoxeLpp/UPAzwPPNW27HHg4O8fgrqbPeTPwDI1fknjVEpf9E8Bx4Pju3btXdACKg5ARMf/v7OxsvvLKKwu2VyqV+f0rlUrOzs4uWJ6dnU1gfrlSqWSlUsnTp0/PLy+1X2YuWG69jOZtEbFgW+vndTJ3vs3n37zeboZO+7abtd1cSx235mNF41vZFxy7uWPWej10o+wHOE+ezuXUyXL3pcyVPy5kZtcx6PY9g/9rWv4msHmZfc9w9r2IDS0fOz23kJkPFUF4Hrg7It7bekaZ+cnM3JeZ+0ZHR7sc9ayIYPPmzVSrVbZv387MzAyHDh0CYPv27VSrVSYnJ+f3n5ycZGZmZsHyzMwMIyMj88uTk5NMTk5yxx13zC8vtR+wYLn1Mubs3r2bPXv2LNjW+nmdzJ1v8/k3r7ebodO+7WZtN9dSx635WI2MjMxfD3PHbmZmhrGxsUXXQ7dygE6vWfHR6R03U/7x64VTN5a7L8HKHxdWpFMtaDwzONm0/jM0vpp/lOJ1/mL9Y8XyncCBYvkDLHxm8Imm89kDDBXLByleZlrq5HsGy/M9g/XNl4n6Xze32X54z6BdDJrfQP5jzr6B/Lpi2yPALy0Tg1tovHH8CPA3wMRyc5xLDDLPBqH1tHXr1rYH9ejRozk1NZWVSiXHx8dzfHx80fLU1FQePHiwq/06XcbcPu22rdTceUREjoyMZER0nKHTvt3OtdRxaz5WEZFDQ0NdXQ+dGIP+ORmDhm5vs8vdl87pvtJlDKKxb+/bt29fHj9+vOwx1COC7p96rweXs/p/A3mt3EzjV2MPurJusxFxIjP3ddrPn0CWJBkDSZIxkCRhDCRJGAP1qUF683gtXAxM0fhVALowev02awwksYfGLxirlj2ISmMMpAG3EfhV4ApgPz4oDCqvd2nAjQHvKJZ/GXhVibOoPMZAGmAbgV/h7B9rnwLe0rSuwWEMpAG2Bfihlm0fYfFvmNT6ZwykAbWRxgN/64PA1cB3r/04Ktma/flJSefujcB/rPJ5fgfwriU+dhi4HphdhcsxLP3BGEh94NNrfHn7gBfX+DJVLl8mkiQZA0mSMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkYQwkSRgDSRLGQJKEMZAkAZGZZc/QlYh4GfjKOX76NuBrqzjOauv1+aD3Z3S+89frM/b6fNCbM+7JzNFOO/VNDM5HRBzPzH1lz7GUXp8Pen9G5zt/vT5jr88H/THjUnyZSJJkDCRJgxODT5Y9QAe9Ph/0/ozOd/56fcZenw/6Y8a2BuI9A0nS8gblmYEkaRnrOgYRcV1E/GNEPBMRt5c9T6uI2BURfxkRT0bEExHx/rJnaicihiLikYj4fNmztBMRmyPi3oj4h4h4KiLeWPZMzSLip4vr92REHIuIDT0w0+9FxEsRcbJp29aIeCAini7+3dJj8/1acR0/FhGfi4jNZc231IxNH7stIjIitpUx27lYtzGIiCHgt4C3AVcC746IK8udapEzwG2ZeSXwBuAne3BGgPcDT5U9xDJ+E/jzzHwd8F300KwRcRnwU8C+zNwLDAHvKncqAO4GrmvZdjvwYGZeATxYrJflbhbP9wCwNzO/E/gn4NBaD9XibhbPSETsAq4Fnlvrgc7Huo0B8D3AM5n5bGbOAn8A3FDyTAtk5guZ+XCx/N80HsQuK3eqhSJiHHgHcGfZs7QTEd8GvBn4XYDMnM3MV8qdapFh4NURMQxcBPxryfOQmQ8B/96y+QbgU8Xyp4Ab13SoJu3my8z7M/NMsfpFYHzNB1s4T7tjCPAx4INAX70hu55jcBnw1ab1U/TYA22ziKgBrwf+ttxJFvk4jRv2t8oeZAkTwMvAXcVLWXdGxMVlDzUnM58Hfp3GV4kvAP+ZmfeXO9WSxjLzhWL5RWCszGE6+DHgz8oeolVE3AA8n5mPlj3LSq3nGPSNiNgI/BHwgcz8r7LnmRMR1wMvZeaJsmdZxjBwNfDbmfl64DTlvryxQPG6+w00ovXtwMUR8Z5yp+osG99m2JNf2UbENI2XWO8pe5ZmEXER8LPAz5U9y7lYzzF4HtjVtD5ebOspEVGlEYJ7MvOzZc/T4k3AOyPiyzReZvv+iPh0uSMtcgo4lZlzz6jupRGHXvEDwL9k5suZ+Q3gs8D3ljzTUv4tInYCFP++VPI8i0TE+4DrgR/J3vu++MtpRP/R4j4zDjwcETtKnapL6zkGfw9cERETEfEqGm/a3VfyTAtERNB4rfupzPyNsudplZmHMnM8M2s0jl89M3vqq9rMfBH4akS8ttj0VuDJEkdq9Rzwhoi4qLi+30oPvcHd4j7glmL5FuBPSpxlkYi4jsZLlu/MzK+XPU+rzHw8M7dnZq24z5wCri5uoz1v3cageKPpIPAXNO58n8nMJ8qdapE3ATfT+Ir7S8Xp7WUP1YduBe6JiMeAq4CPlDzPvOIZy73Aw8DjNO5zpf+UakQcA74AvDYiTkXEjwMfBX4wIp6m8Yzmoz023yeATcADxX3ljrLmW2bGvuVPIEuS1u8zA0lS94yBJMkYSJKMgSQJYyBJwhhIkjAGkiSMgSQJ+H94VBsWpI9FiQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = t.hours.plot.box(vert=False, notch=True, patch_artist=True, color='cyan')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = times_by_date.hours.plot.hist(color='cyan')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 6 Axes>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas import plotting\n",
    "plotting.bootstrap_plot(t.hours, color='cyan')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYMAAAD8CAYAAACVZ8iyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAADMZJREFUeJzt3X1sXXUdgPHn23bsTdwLW5pFwBZFGZ0yoFHxBRVfgmg0UWMgGEFJSIybmGAEssT49ocSX6PGqKgYtVPxBQkBFamI0zjtYMBg8qJuCqKD+JYgc2P7+sc5jNu6tre31557bp9PcrN7Tu89/f3as/v0ntPeG5mJJGl+66l6AJKk6hkDSZIxkCQZA0kSxkCShDGQJGEMJEkYA0kSxkCSBPRVPYBmrVq1KgcGBqoehiTVyrZt2x7OzNXT3a42MRgYGGBsbKzqYUhSrUTE7mZu52EiSZIxkCQZA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJElAX9UDkNSZHgDOAfZWPI6TgI8BT27zdv8GXATcPc3tjgSuAla2+fN3GmMg6bDuAG4BHumAcVxD8YB8epu2eT1wLsXc9k1z26XAfcBz2vS5O5WHiSRNqhN+WtwL7AHOBN4J/GcW23oEeBvwBuDvTB8C6IyvwVwwBpJq4VHgCuBE4LYW7v8r4BnA5nJbGs8YSKqNR4HfA6cBHwQONHGf/cAlwBnAn6n+HEinMgaSaudR4MPAMEUcJnMX8CzgM/hsYDrGQFIt/Ru4neLB/vNANnzsIPBRiljcU95WUzMGkmrrIMUD/cXAy4C/An8Eng+8j+LZQE52Z40zX06US+pijwBbKE4QH6SIQDPnE/QEY6B5LfAnx26xv7x0o7nYTz1MJEkyBpIkYyBJookYRMRAROyYi8FIkqpRyTODiJizE9cbN25kwYIFRAQRwVFHHcXGjRtZt24dvb29rFu3js2bN7e07c2bN7dlO528rXbotPFIOozMnPICDAA7gS8CdwI/BhYD6yle7uN24PvAivL2NwHD5fVVwK7y+vkULz44CvwMWAPcDGwHdgAvmmocp556as7Uhg0bsqenJ1esWJHXXXddXn755dnT05MRkZs2bcp9+/bl6OhoDg4O5sjIyIy2PTIykoODgzk6Ojqr7XTyttqh08YzEVUPoINdn5nLcpoHiHlwWZaZW2f5tZyt2eynwFg2MdVmY/AYsL5c/jbw5jICLy7XfQD4ZE4fg/uBleXyxcCm8novcORU42glBgsXLsz+/v4cHR09tK6/vz/7+vpyaGjo0LrR0dFxy80YGhoat91Wt9PJ22qHThvPRMZgcsZgfsUgittOLiIGgBsy8/hy+RJgEXBBZh5brnsacFVmnhIRNwHvzsyxiFhVDmQgIs4v4/HW8j6nA18Gvg5cnZnbD/O5LwQuBDj22GNP3b1795RjPcz9Adi3bx8LFiwYt66np4cDB4o/S9m/fz+LFi06tNyM3t5e9u7de2i7rW6nk7fVDp02nomi6gGo4y0D/ln1IGj97wwiYltmDk93u2bPGTS+hPgBYPkUt32sYbuLJnzs0PtkZObNFO9V8QBwZUS8ZeKGMvMLmTmcmcOrV69ucqhPWLhwIf39/WzZsuXQuv7+fvr6+li7du2hdVu2bBm33Iy1a9eO226r2+nkbbVDp43ncNLLYS/XUzwQCrZS7fdiTkz31IHiMNGOhuV3U7zsx22Ux/nL5U+U168A3l5efxfjDxN9pmE7TwV6y+sbKA8zTXbxnMHcb6sdOm08E3mYaHIeJppfh4lmE4PGE8hX88QJ5BPKdbcCH5oiBudRnDi+Ffg5MDjVOFqJQWYRhL6+vkORXblyZW7YsCGHhoayp6cnh4aGWn5gGhkZact2Onlb7dBp42lkDCZnDOZXDKY9Z9AphoeHc2xsrOphqMv42kST+yFwNp1xvLxKyyh+hbLK90CezX7a7nMGkqQuZgwkScZAkmQMJHWRxVUPoMaMgeY1Tx53h8UUv/b4i/Kyhv/9I6c6m4v91BhIqrXFwAUUL6B2MsX7H98DvAlYUuG46sYYSKqlhcBq4Drg04x/JvAk4KsUL6S2HDhizkdXP8ZAUu0sAV4H3Au8ZIrbvbq8zcvxWcJ0jIGk2lgAPBn4GvAtmnvtpFXAtcDngKUUL5Gs/2UMJNXCUuBFFOcDXj/D+wbwForzCsP4LOFwjIGkSR2segAUD1JLgI8DPwH6Z7GtY4BfUrwBy2KaewnzTvgazIU5e/tJSfVyHMVP41U/SDwT+AbFeNqhh+Kdtc4CzgV2TXP7JcBT2vS5O1nV32dJHeoZwINVD+L/aC1wS9WD6CAeJpIkGQNJkjGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJGEMJEkYA0kSxkCShDGQJAGRmVWPoSkR8RCwexabWAU83KbhdIJumw84pzrotvlA98/pqZm5ero71CYGsxURY5k5XPU42qXb5gPOqQ66bT7gnB7nYSJJkjGQJM2vGHyh6gG0WbfNB5xTHXTbfMA5AfPonIEkaXLz6ZmBJGkSXR+DiDgzIu6OiPsi4tKqx9OKiPhyROyJiB0N61ZGxA0RcW/574oqxzgTEXFMRPw0Iu6KiDsj4qJyfZ3ntCgifh0Rt5Vzen+5fjAitpb737ci4oiqxzoTEdEbEbdGxLXlct3nsysi7oiI7RExVq6r7X4HEBHLI+I7EfHbiNgZEae1MqeujkFE9AKfBV4FnAicExEnVjuqllwJnDlh3aXAjZl5PHBjuVwXjwEXZ+aJwPOAd5TflzrP6T/AGZl5ErAeODMingd8BPhEZj4d+DtwQYVjbMVFwM6G5brPB+Clmbm+4Vcv67zfAXwK+GFmngCcRPH9mvmcMrNrL8BpwI8ali8DLqt6XC3OZQDY0bB8N7CmvL4GuLvqMc5ibj8AXtEtcwKWALcAz6X4w5++cv24/bHTL8DR5QPJGcC1QNR5PuWYdwGrJqyr7X4HLAP+QHn+dzZz6upnBsBTgD81LN9frusG/Zn5YHn9L0B/lYNpVUQMACcDW6n5nMpDKtuBPcANwO+Af2TmY+VN6rb/fRJ4D3CwXD6Kes8HIIEfR8S2iLiwXFfn/W4QeAj4Snk474qIWEoLc+r2GMwLWeS/dr8WFhFPAr4LvCsz/9X4sTrOKTMPZOZ6ip+onwOcUPGQWhYRrwH2ZOa2qsfSZi/MzFMoDh2/IyJOb/xgDfe7PuAU4HOZeTLwCBMOCTU7p26PwQPAMQ3LR5frusFfI2INQPnvnorHMyMRsYAiBN/IzO+Vq2s9p8dl5j+An1IcRlkeEX3lh+q0/70AeG1E7AK+SXGo6FPUdz4AZOYD5b97gO9TRLvO+939wP2ZubVc/g5FHGY8p26PwW+A48vfgDgCOBu4puIxtcs1wHnl9fMojrvXQkQE8CVgZ2Z+vOFDdZ7T6ohYXl5fTHEOZCdFFN5Y3qw2c8rMyzLz6MwcoPh/M5qZ51LT+QBExNKIOPLx68ArgR3UeL/LzL8Af4qIZ5arXgbcRStzqvoEyBycYDkLuIfi+O2mqsfT4hw2Aw8C+yl+EriA4vjtjcC9wE+AlVWPcwbzeSHF09bbge3l5ayaz+nZwK3lnHYA7y3XHwf8GrgPuApYWPVYW5jbS4Br6z6fcuy3lZc7H388qPN+V45/PTBW7ntXAytamZN/gSxJ6vrDRJKkJhgDSZIxkCQZA0kSxkCShDGQJGEMJEkYA0kS8F/SCko2TwrCjQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = t.resample('W').sum().hours.plot.box(vert=False, notch=True, patch_artist=True, color='cyan')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Heatmap with `gmaps`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4ae652f7d74a4df18dd5a07a4ec61bd2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "locs = df['2018'][['latitude', 'longitude']]\n",
    "hlayer = gmaps.heatmap_layer(locs)\n",
    "hlayer.max_intensity = 100\n",
    "hlayer.point_radius = 5\n",
    "hlayer.gradient = 'rgba(0,255,255,0) rgba(0,255,255,1) rgba(0,0,255,1) rgba(255,0,0,1)'.split()\n",
    "fig = gmaps.figure(map_type='SATELLITE')\n",
    "fig.add_layer(hlayer)\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A look clusters of location using KMeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfj = df['2018-06']\n",
    "dfw = dfj[dfj.index.dayofweek < 5].between_time('10:00', '18:00')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "03288b4378dd49fbb7c8c9844447f90f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "kmeans = KMeans(n_clusters=2).fit(dfw[['latitude', 'longitude']])\n",
    "\n",
    "#slayer = gmaps.symbol_layer(dfw[['latitude', 'longitude']], stroke_color='red', stroke_opacity=0.5)\n",
    "clayer = gmaps.symbol_layer(kmeans.cluster_centers_, fill_color='rgba(255,0,0,0.8)', stroke_color='rgba(0,255,255,0.5)', scale=16)\n",
    "\n",
    "fig = gmaps.figure()\n",
    "fig.add_layer(clayer)\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Converting to GeoPandas geomerty for an alternative way to explore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "from shapely.geometry import Point\n",
    "\n",
    "geometry = [Point(xy) for xy in df[['longitude', 'latitude']].values]\n",
    "crs = {'proj': 'longlat', 'ellps': 'WGS84', 'datum': 'WGS84', 'no_defs': True}\n",
    "gdf = gpd.GeoDataFrame({'timestamp': df.timestamp}, geometry=geometry, crs=crs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))\n",
    "\n",
    "gdf = gdf.to_crs(world.crs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = world.plot(color='lightgrey', figsize=(16,8))\n",
    "\n",
    "#gdf.plot(ax=ax, color='r')\n",
    "kmeans = KMeans(n_clusters=2).fit(df[['longitude', 'latitude']])\n",
    "ax = gpd.GeoDataFrame(geometry=[Point(xy) for xy in kmeans.cluster_centers_]).plot(ax=ax, color='cyan')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spatial join with GeoPandas to determine in which country is each location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "locations_with_country = gpd.sjoin(gdf, world)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "locations_with_country['date'] = locations_with_country.index.date\n",
    "grouped = locations_with_country.groupby([locations_with_country.index.year, 'name'])\n",
    "summary = grouped.date.agg([np.size, np.min, np.max, lambda x: len(np.unique(x))])\n",
    "summary.sort_values('amin')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Attribute join with GeoPandas to combine location counts with country data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "world2 = world.merge(pd.DataFrame({'loc_count': locations_with_country.groupby('iso_a3').size()}), how='left', on='iso_a3')\n",
    "world2['weight'] = np.nan_to_num(world2['loc_count']) / 500\n",
    "ax = world2.plot(column='weight', cmap='Paired', scheme='quantiles', figsize=(16,8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Multi-dimensional (time & space) clusters?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "05c55b9ddd354e90b41069f44ec524af",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1 = df['2018']\n",
    "df2 = pd.DataFrame({\n",
    "    'latitude': df1.latitude,\n",
    "    'longitude': df1.longitude,\n",
    "    'dayofweek': df1.index.dayofweek,\n",
    "    'hour': df1.index.hour,\n",
    "})\n",
    "kmeans = KMeans().fit(df2)\n",
    "\n",
    "clusters = list(zip(*kmeans.cluster_centers_))\n",
    "locs = list(zip(*clusters[:2]))\n",
    "info = ['{} {:02}:00'.format(calendar.day_name[int(d)], int(h)) for d, h in zip(*clusters[2:])]\n",
    "\n",
    "fig = gmaps.figure()\n",
    "fig.add_layer(gmaps.marker_layer(locs, info_box_content=info))\n",
    "fig"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}

## requirements.txt
jupyter
geopandas
gmaps
scipy
sklearn
rtree
pysal
seaborn