911 Call Analysis v2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "%matplotlib inline\n",
    "plt.rcParams[\"patch.force_edgecolor\"] = True # in matplotlib, edge borders are turned off by default. \n",
    "sns.set_style(\"darkgrid\") # set a grey grid as a background\n",
    "# quell warnings\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('911.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['lat', 'lng', 'desc', 'zip', 'title', 'timeStamp', 'twp', 'addr', 'e'], dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 99492 entries, 0 to 99491\n",
      "Data columns (total 9 columns):\n",
      "lat          99492 non-null float64\n",
      "lng          99492 non-null float64\n",
      "desc         99492 non-null object\n",
      "zip          86637 non-null float64\n",
      "title        99492 non-null object\n",
      "timeStamp    99492 non-null object\n",
      "twp          99449 non-null object\n",
      "addr         98973 non-null object\n",
      "e            99492 non-null int64\n",
      "dtypes: float64(3), int64(1), object(5)\n",
      "memory usage: 6.8+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>desc</th>\n",
       "      <th>zip</th>\n",
       "      <th>title</th>\n",
       "      <th>timeStamp</th>\n",
       "      <th>twp</th>\n",
       "      <th>addr</th>\n",
       "      <th>e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40.297876</td>\n",
       "      <td>-75.581294</td>\n",
       "      <td>REINDEER CT &amp; DEAD END;  NEW HANOVER; Station ...</td>\n",
       "      <td>19525.0</td>\n",
       "      <td>EMS: BACK PAINS/INJURY</td>\n",
       "      <td>2015-12-10 17:40:00</td>\n",
       "      <td>NEW HANOVER</td>\n",
       "      <td>REINDEER CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>40.258061</td>\n",
       "      <td>-75.264680</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN;  HATFIELD TOWNSHIP...</td>\n",
       "      <td>19446.0</td>\n",
       "      <td>EMS: DIABETIC EMERGENCY</td>\n",
       "      <td>2015-12-10 17:40:00</td>\n",
       "      <td>HATFIELD TOWNSHIP</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>40.121182</td>\n",
       "      <td>-75.351975</td>\n",
       "      <td>HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-St...</td>\n",
       "      <td>19401.0</td>\n",
       "      <td>Fire: GAS-ODOR/LEAK</td>\n",
       "      <td>2015-12-10 17:40:00</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>HAWS AVE</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40.116153</td>\n",
       "      <td>-75.343513</td>\n",
       "      <td>AIRY ST &amp; SWEDE ST;  NORRISTOWN; Station 308A;...</td>\n",
       "      <td>19401.0</td>\n",
       "      <td>EMS: CARDIAC EMERGENCY</td>\n",
       "      <td>2015-12-10 17:40:01</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>AIRY ST &amp; SWEDE ST</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40.251492</td>\n",
       "      <td>-75.603350</td>\n",
       "      <td>CHERRYWOOD CT &amp; DEAD END;  LOWER POTTSGROVE; S...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EMS: DIZZINESS</td>\n",
       "      <td>2015-12-10 17:40:01</td>\n",
       "      <td>LOWER POTTSGROVE</td>\n",
       "      <td>CHERRYWOOD CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         lat        lng                                               desc  \\\n",
       "0  40.297876 -75.581294  REINDEER CT & DEAD END;  NEW HANOVER; Station ...   \n",
       "1  40.258061 -75.264680  BRIAR PATH & WHITEMARSH LN;  HATFIELD TOWNSHIP...   \n",
       "2  40.121182 -75.351975  HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-St...   \n",
       "3  40.116153 -75.343513  AIRY ST & SWEDE ST;  NORRISTOWN; Station 308A;...   \n",
       "4  40.251492 -75.603350  CHERRYWOOD CT & DEAD END;  LOWER POTTSGROVE; S...   \n",
       "\n",
       "       zip                    title            timeStamp                twp  \\\n",
       "0  19525.0   EMS: BACK PAINS/INJURY  2015-12-10 17:40:00        NEW HANOVER   \n",
       "1  19446.0  EMS: DIABETIC EMERGENCY  2015-12-10 17:40:00  HATFIELD TOWNSHIP   \n",
       "2  19401.0      Fire: GAS-ODOR/LEAK  2015-12-10 17:40:00         NORRISTOWN   \n",
       "3  19401.0   EMS: CARDIAC EMERGENCY  2015-12-10 17:40:01         NORRISTOWN   \n",
       "4      NaN           EMS: DIZZINESS  2015-12-10 17:40:01   LOWER POTTSGROVE   \n",
       "\n",
       "                         addr  e  \n",
       "0      REINDEER CT & DEAD END  1  \n",
       "1  BRIAR PATH & WHITEMARSH LN  1  \n",
       "2                    HAWS AVE  1  \n",
       "3          AIRY ST & SWEDE ST  1  \n",
       "4    CHERRYWOOD CT & DEAD END  1  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19401.0    6979\n",
       "19464.0    6643\n",
       "19403.0    4854\n",
       "19446.0    4748\n",
       "19406.0    3174\n",
       "Name: zip, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Top 5 zipcodes for calls\n",
    "df['zip'].value_counts().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LOWER MERION    8443\n",
       "ABINGTON        5977\n",
       "NORRISTOWN      5890\n",
       "UPPER MERION    5227\n",
       "CHELTENHAM      4575\n",
       "Name: twp, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Top 5 Townships\n",
    "df['twp'].value_counts().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "110"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Unique title codes\n",
    "df['title'].nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**What Department Services are most frequently called?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     EMS: BACK PAINS/INJURY\n",
       "1    EMS: DIABETIC EMERGENCY\n",
       "2        Fire: GAS-ODOR/LEAK\n",
       "3     EMS: CARDIAC EMERGENCY\n",
       "4             EMS: DIZZINESS\n",
       "Name: title, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Adding a feature called \"service\" from the 'title' field to indicate if Fire, EMS, or Police were involved\n",
    "df['title'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add a column called 'service' with the first token on the left side of the colon in title\n",
    "df['service'] = df['title'].apply(lambda title: title.split(':')[0])\n",
    "# changeup 'Traffic' to indicate police services\n",
    "df['service'] = np.where(df.title.str.contains('Traffic'),'Police',df.service)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>desc</th>\n",
       "      <th>zip</th>\n",
       "      <th>title</th>\n",
       "      <th>timeStamp</th>\n",
       "      <th>twp</th>\n",
       "      <th>addr</th>\n",
       "      <th>e</th>\n",
       "      <th>service</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40.297876</td>\n",
       "      <td>-75.581294</td>\n",
       "      <td>REINDEER CT &amp; DEAD END;  NEW HANOVER; Station ...</td>\n",
       "      <td>19525.0</td>\n",
       "      <td>EMS: BACK PAINS/INJURY</td>\n",
       "      <td>2015-12-10 17:40:00</td>\n",
       "      <td>NEW HANOVER</td>\n",
       "      <td>REINDEER CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>40.258061</td>\n",
       "      <td>-75.264680</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN;  HATFIELD TOWNSHIP...</td>\n",
       "      <td>19446.0</td>\n",
       "      <td>EMS: DIABETIC EMERGENCY</td>\n",
       "      <td>2015-12-10 17:40:00</td>\n",
       "      <td>HATFIELD TOWNSHIP</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>40.121182</td>\n",
       "      <td>-75.351975</td>\n",
       "      <td>HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-St...</td>\n",
       "      <td>19401.0</td>\n",
       "      <td>Fire: GAS-ODOR/LEAK</td>\n",
       "      <td>2015-12-10 17:40:00</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>HAWS AVE</td>\n",
       "      <td>1</td>\n",
       "      <td>Fire</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         lat        lng                                               desc  \\\n",
       "0  40.297876 -75.581294  REINDEER CT & DEAD END;  NEW HANOVER; Station ...   \n",
       "1  40.258061 -75.264680  BRIAR PATH & WHITEMARSH LN;  HATFIELD TOWNSHIP...   \n",
       "2  40.121182 -75.351975  HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-St...   \n",
       "\n",
       "       zip                    title            timeStamp                twp  \\\n",
       "0  19525.0   EMS: BACK PAINS/INJURY  2015-12-10 17:40:00        NEW HANOVER   \n",
       "1  19446.0  EMS: DIABETIC EMERGENCY  2015-12-10 17:40:00  HATFIELD TOWNSHIP   \n",
       "2  19401.0      Fire: GAS-ODOR/LEAK  2015-12-10 17:40:00         NORRISTOWN   \n",
       "\n",
       "                         addr  e service  \n",
       "0      REINDEER CT & DEAD END  1     EMS  \n",
       "1  BRIAR PATH & WHITEMARSH LN  1     EMS  \n",
       "2                    HAWS AVE  1    Fire  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "EMS Services are the most frequently called, then Police, then Fire"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EMS       48877\n",
       "Police    35695\n",
       "Fire      14920\n",
       "Name: service, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['service'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11ae3c510>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the services use\n",
    "sns.countplot('service',data=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Doing time analysis**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 99492 entries, 0 to 99491\n",
      "Data columns (total 10 columns):\n",
      "lat          99492 non-null float64\n",
      "lng          99492 non-null float64\n",
      "desc         99492 non-null object\n",
      "zip          86637 non-null float64\n",
      "title        99492 non-null object\n",
      "timeStamp    99492 non-null object\n",
      "twp          99449 non-null object\n",
      "addr         98973 non-null object\n",
      "e            99492 non-null int64\n",
      "service      99492 non-null object\n",
      "dtypes: float64(3), int64(1), object(6)\n",
      "memory usage: 7.6+ MB\n"
     ]
    }
   ],
   "source": [
    "# What dtype is timestamp?\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df.timeStamp[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "time = pd.to_datetime(df['timeStamp'][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert the timeStamp entries to be\n",
    "df['timeStamp'] = pd.to_datetime(df['timeStamp'])\n",
    "df['Date'] = df['timeStamp'].apply(lambda time: time.date())\n",
    "#df['Date'] = pd.to_datetime(df['timeStamp'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now create features for Hour of Day, Month of Year and Day of Week to simplify Analysis\n",
    "df['Hour'] = df['timeStamp'].apply(lambda t: t.hour)\n",
    "df['Month'] = df['timeStamp'].apply(lambda t: t.month)\n",
    "df['Day of Week'] = df['timeStamp'].apply(lambda t: t.dayofweek)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>desc</th>\n",
       "      <th>zip</th>\n",
       "      <th>title</th>\n",
       "      <th>timeStamp</th>\n",
       "      <th>twp</th>\n",
       "      <th>addr</th>\n",
       "      <th>e</th>\n",
       "      <th>service</th>\n",
       "      <th>Date</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day of Week</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40.297876</td>\n",
       "      <td>-75.581294</td>\n",
       "      <td>REINDEER CT &amp; DEAD END;  NEW HANOVER; Station ...</td>\n",
       "      <td>19525.0</td>\n",
       "      <td>EMS: BACK PAINS/INJURY</td>\n",
       "      <td>2015-12-10 17:40:00</td>\n",
       "      <td>NEW HANOVER</td>\n",
       "      <td>REINDEER CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>2015-12-10</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>40.258061</td>\n",
       "      <td>-75.264680</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN;  HATFIELD TOWNSHIP...</td>\n",
       "      <td>19446.0</td>\n",
       "      <td>EMS: DIABETIC EMERGENCY</td>\n",
       "      <td>2015-12-10 17:40:00</td>\n",
       "      <td>HATFIELD TOWNSHIP</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>2015-12-10</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         lat        lng                                               desc  \\\n",
       "0  40.297876 -75.581294  REINDEER CT & DEAD END;  NEW HANOVER; Station ...   \n",
       "1  40.258061 -75.264680  BRIAR PATH & WHITEMARSH LN;  HATFIELD TOWNSHIP...   \n",
       "\n",
       "       zip                    title           timeStamp                twp  \\\n",
       "0  19525.0   EMS: BACK PAINS/INJURY 2015-12-10 17:40:00        NEW HANOVER   \n",
       "1  19446.0  EMS: DIABETIC EMERGENCY 2015-12-10 17:40:00  HATFIELD TOWNSHIP   \n",
       "\n",
       "                         addr  e service        Date  Hour  Month  Day of Week  \n",
       "0      REINDEER CT & DEAD END  1     EMS  2015-12-10    17     12            3  \n",
       "1  BRIAR PATH & WHITEMARSH LN  1     EMS  2015-12-10    17     12            3  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make the Day Of Week more readable with DayNames\n",
    "days = {0:'Mon',1:'Tue',2:'Wed',3:'Thu',4:'Fri',5:'Sat',6:'Sun'}\n",
    "df['Day of Week'] = df['Day of Week'].map(days)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "No Calls on Tuesdays. Also the weekends are weirdly quiet."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x11ced1590>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now show Emergency calls by Service and Day of Week\n",
    "sns.countplot(x=df['Day of Week'],hue=df['service'], order=['Mon','Tues','Wed','Thu','Fri','Sat','Sun'])\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.) # move legend outside plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at months"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>Month</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>desc</th>\n",
       "      <th>zip</th>\n",
       "      <th>title</th>\n",
       "      <th>timeStamp</th>\n",
       "      <th>twp</th>\n",
       "      <th>addr</th>\n",
       "      <th>e</th>\n",
       "      <th>service</th>\n",
       "      <th>Date</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Day of Week</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>13205</td>\n",
       "      <td>13205</td>\n",
       "      <td>13205</td>\n",
       "      <td>11527</td>\n",
       "      <td>13205</td>\n",
       "      <td>13205</td>\n",
       "      <td>13203</td>\n",
       "      <td>13096</td>\n",
       "      <td>13205</td>\n",
       "      <td>13205</td>\n",
       "      <td>13205</td>\n",
       "      <td>13205</td>\n",
       "      <td>13205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>11467</td>\n",
       "      <td>11467</td>\n",
       "      <td>11467</td>\n",
       "      <td>9930</td>\n",
       "      <td>11467</td>\n",
       "      <td>11467</td>\n",
       "      <td>11465</td>\n",
       "      <td>11396</td>\n",
       "      <td>11467</td>\n",
       "      <td>11467</td>\n",
       "      <td>11467</td>\n",
       "      <td>11467</td>\n",
       "      <td>11467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>11101</td>\n",
       "      <td>11101</td>\n",
       "      <td>11101</td>\n",
       "      <td>9755</td>\n",
       "      <td>11101</td>\n",
       "      <td>11101</td>\n",
       "      <td>11092</td>\n",
       "      <td>11059</td>\n",
       "      <td>11101</td>\n",
       "      <td>11101</td>\n",
       "      <td>11101</td>\n",
       "      <td>11101</td>\n",
       "      <td>11101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>11326</td>\n",
       "      <td>11326</td>\n",
       "      <td>11326</td>\n",
       "      <td>9895</td>\n",
       "      <td>11326</td>\n",
       "      <td>11326</td>\n",
       "      <td>11323</td>\n",
       "      <td>11283</td>\n",
       "      <td>11326</td>\n",
       "      <td>11326</td>\n",
       "      <td>11326</td>\n",
       "      <td>11326</td>\n",
       "      <td>11326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>11423</td>\n",
       "      <td>11423</td>\n",
       "      <td>11423</td>\n",
       "      <td>9946</td>\n",
       "      <td>11423</td>\n",
       "      <td>11423</td>\n",
       "      <td>11420</td>\n",
       "      <td>11378</td>\n",
       "      <td>11423</td>\n",
       "      <td>11423</td>\n",
       "      <td>11423</td>\n",
       "      <td>11423</td>\n",
       "      <td>11423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>11786</td>\n",
       "      <td>11786</td>\n",
       "      <td>11786</td>\n",
       "      <td>10212</td>\n",
       "      <td>11786</td>\n",
       "      <td>11786</td>\n",
       "      <td>11777</td>\n",
       "      <td>11732</td>\n",
       "      <td>11786</td>\n",
       "      <td>11786</td>\n",
       "      <td>11786</td>\n",
       "      <td>11786</td>\n",
       "      <td>11786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>12137</td>\n",
       "      <td>12137</td>\n",
       "      <td>12137</td>\n",
       "      <td>10633</td>\n",
       "      <td>12137</td>\n",
       "      <td>12137</td>\n",
       "      <td>12133</td>\n",
       "      <td>12088</td>\n",
       "      <td>12137</td>\n",
       "      <td>12137</td>\n",
       "      <td>12137</td>\n",
       "      <td>12137</td>\n",
       "      <td>12137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>9078</td>\n",
       "      <td>9078</td>\n",
       "      <td>9078</td>\n",
       "      <td>7832</td>\n",
       "      <td>9078</td>\n",
       "      <td>9078</td>\n",
       "      <td>9073</td>\n",
       "      <td>9025</td>\n",
       "      <td>9078</td>\n",
       "      <td>9078</td>\n",
       "      <td>9078</td>\n",
       "      <td>9078</td>\n",
       "      <td>9078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>12</td>\n",
       "      <td>7969</td>\n",
       "      <td>7969</td>\n",
       "      <td>7969</td>\n",
       "      <td>6907</td>\n",
       "      <td>7969</td>\n",
       "      <td>7969</td>\n",
       "      <td>7963</td>\n",
       "      <td>7916</td>\n",
       "      <td>7969</td>\n",
       "      <td>7969</td>\n",
       "      <td>7969</td>\n",
       "      <td>7969</td>\n",
       "      <td>7969</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Month    lat    lng   desc    zip  title  timeStamp    twp   addr      e  \\\n",
       "0      1  13205  13205  13205  11527  13205      13205  13203  13096  13205   \n",
       "1      2  11467  11467  11467   9930  11467      11467  11465  11396  11467   \n",
       "2      3  11101  11101  11101   9755  11101      11101  11092  11059  11101   \n",
       "3      4  11326  11326  11326   9895  11326      11326  11323  11283  11326   \n",
       "4      5  11423  11423  11423   9946  11423      11423  11420  11378  11423   \n",
       "5      6  11786  11786  11786  10212  11786      11786  11777  11732  11786   \n",
       "6      7  12137  12137  12137  10633  12137      12137  12133  12088  12137   \n",
       "7      8   9078   9078   9078   7832   9078       9078   9073   9025   9078   \n",
       "8     12   7969   7969   7969   6907   7969       7969   7963   7916   7969   \n",
       "\n",
       "   service   Date   Hour  Day of Week  \n",
       "0    13205  13205  13205        13205  \n",
       "1    11467  11467  11467        11467  \n",
       "2    11101  11101  11101        11101  \n",
       "3    11326  11326  11326        11326  \n",
       "4    11423  11423  11423        11423  \n",
       "5    11786  11786  11786        11786  \n",
       "6    12137  12137  12137        12137  \n",
       "7     9078   9078   9078         9078  \n",
       "8     7969   7969   7969         7969  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "byMonth = df.groupby('Month').count()\n",
    "byMonth.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11ca48b10>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# use this to draw a line for the calls per township. This fills in the missing data in the viz\n",
    "byMonth['twp'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11ca14490>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='Month',data=df,palette='viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x11ca065d0>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# showing calls in zipcode by Month with linear regression. Reset the index on byMonth for the plot\n",
    "# Notice on the right how the Error shade grows when the line moves past December\n",
    "sns.lmplot(x='Month',y='zip',data=byMonth.reset_index(), markers=['^'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11bf18a10>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Counting by date at latitude\n",
    "plt.figure(figsize=(10,4))\n",
    "df.groupby('Date').count()['twp'].plot(kind='line')\n",
    "#plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tidying up Month Names\n",
    "# remap the month\n",
    "# Make the map to show names\n",
    "monthmap = {1:'Jan',2:'Feb',3:'Mar',4:'Apr',5:'May',6:'Jun',7:'Jul',8:'Aug',9:'Sep',10:'Oct',11:'Nov',12:'Dec'}\n",
    "df['MonthName'] = df['Month'].map(monthmap)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "No data for Oct, Nov, Dec and January"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x11c585610>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FtiIiIq6kQS7FiY6OZvr06cTHxxMeHs6AAQOwWCxEREQQFRWFzWYjJiamyrbimnRpjIhcqZwargkJCY7/JyYmVnjcarVitVrLLQsLC6u0rbgeXRojUnd+Ad74eHlU+lhBUQl5vxQ2cI+kNjSJhIhIE+Tj5UHP51dW+lj6/LHkoXBtyjQ7g4iIiMkUriIiIiZTuIqIiJhM4SoiImIyhauIiIjJ9G3hK4iuOxURaRgK1yuIrjsVEWkYOiwsIiJiMoWriIiIyRSuIiIiJlO4ioiImEzhKiIiYrIahWtSUlK5n1eurHwyaREREbnMpTgffPABn3zyCWlpaezevRuA0tJSvvvuO8aOHdsgHRQREXE11YbrHXfcQevWrcnJySEqKgoANzc3QkJCGqRzIiIirqjacG3ZsiWRkZFERkZy5swZioqKgAujVxEREalcjWZomjVrFjt27KBNmzbY7XYMw2Dt2rXO7puIiIhLqlG4fvHFF2zduhU3N325WERE5HJqlJbt2rVzHBIWERGR6tVo5JqVlcVdd91Fu3btAHRYWEREpBo1CtcFCxY4ux8iIiLNRo3CddOmTRWWPf3006Z3RkREpDmoUbheffXVANjtdr7++mtsNptTOyUiIuLKahSuw4cPL/fzE0884ZTOiIiINAc1CtejR486/v/jjz+SmZnptA6JiIi4uhqFa0xMjOP/Xl5eREdHV9u+tLSUadOmcfToUQzDYNasWXh5eTFp0iQMw6Bjx47MmDEDNzc3Fi1axPbt23F3d2fKlCl069aNjIyMStuKSMPwa+mBj6d3lY8XFBeS93NJA/ZIxLXUKFwTEhI4e/YsJ06coG3btgQFBVXb/tNPPwVg7dq1pKWl8eqrr2K325k4cSKRkZHExMSwbds2goOD2bNnD0lJSWRlZWG1WtmwYQNxcXEV2t53333131sRqREfT296L+xd5eOp1lTyULiKVKVGw8GPPvqI4cOHs2TJEqKionj//ferbX/vvffy4osvApCZmUlAQAAHDhzgtttuA6Bv377s2rWL9PR0+vTpg2EYBAcHU1paSnZ2dqVtRUREXEWNRq7Lly9n48aN+Pr6kpeXx29+8xseeeSR6jfs7k50dDT/+Mc/+Nvf/kZqaiqGYQDg6+tLbm4ueXl5BAYGOtYpW142f/HFy6pjsRgEBraoya4A1Kptfderay3VU73mWE/Mo99/01ajcDUMA19fXwD8/Pzw8vKq0cbnzZvHn//8Z4YNG1Zu+sT8/HwCAgLw8/MjPz+/3HJ/f/9y51fL2lantNROTs45AFq39r9sv8raXupy61a2Xl3WUT3Xr1fX11lD1nPm30J164o56vO3UN0584vPl9fkeZa6qVG4hoSEMHfuXCIiIkhPTyc0NLTa9u+99x6nT5/md7/7HT4+PhiGwY033khaWhqRkZGkpKTQq1cvQkNDmT9/PuPHj+fUqVPYbDaCgoLo2rVrhbYiIlIz1Z0z1/nyhlGjcI2KimLv3r3s2rWLzZs389Zbb1Xbvn///kyePJlRo0Zx/vx5pkyZwnXXXcf06dOJj48nPDycAQMGYLFYiIiIICoqCpvN5vhWcnR0dIW2IiIirqJG4RoXF8err75KaGgo48aNY9KkSaxatarK9i1atOCvf/1rheWJiYkVllmtVqxWa7llYWFhlbYVERFxBTX6trCHh4fjUHBISIiuORUREalGjUauwcHBxMfH0717d/bv30+bNm2c3S8RERGXVaMhaFxcHEFBQezYsYOgoCDi4uKc3S8RERGXVaORq5eXF48//riTuyIiItI86OSpiIiIyRSuIiIiJlO4ioiImEzhKiIiYjKFq4iIiMkUriIiIiZTuIqIiJhM4SoiImIyhauIiIjJFK4iIiImU7iKiIiYTOEqIiJiMoWriIiIyRSuIiIiJlO4ioiImEzhKiIiYjKFq4iIiMkUriIiIiZTuIqIiJhM4SoiImIyhauIiIjJFK4iIiImczd7gyUlJUyZMoX//Oc/FBcX89RTT9GhQwcmTZqEYRh07NiRGTNm4ObmxqJFi9i+fTvu7u5MmTKFbt26kZGRUWlbERERV2F6aiUnJxMYGMjq1at56623ePHFF4mLi2PixImsXr0au93Otm3bOHDgAHv27CEpKYn4+HhmzZoFUGlbERERV2J6uN5///388Y9/BMBut2OxWDhw4AC33XYbAH379mXXrl2kp6fTp08fDMMgODiY0tJSsrOzK20rIiLiSkw/LOzr6wtAXl4ezzzzDBMnTmTevHkYhuF4PDc3l7y8PAIDA8utl5ubi91ur9D2ciwWg8DAFjXuY23a1ne9utZSPdVrjvXEPHrumjbTwxUgKyuLP/zhD4wcOZKBAwcyf/58x2P5+fkEBATg5+dHfn5+ueX+/v7lzq+Wtb2c0lI7OTnnAGjd2v+y7cvaXupy61a2Xl3WUT3Xr1fX11lD1nPm30J164o5GuJvoSbPs9SN6YeFf/rpJ37729/y/PPPM2TIEAC6du1KWloaACkpKURERNCjRw927tyJzWYjMzMTm81GUFBQpW1FRERciekj1yVLlvDLL7/w+uuv8/rrrwMwdepUYmNjiY+PJzw8nAEDBmCxWIiIiCAqKgqbzUZMTAwA0dHRTJ8+vVxbERERV2J6uE6bNo1p06ZVWJ6YmFhhmdVqxWq1llsWFhZWaVuz2M8X6VCINEl6bYo0H04559qUGe5eHJ99U6WPhcZ8aWotvVlKbTTka1NEnOuKC9eGVN2bJegNU0SkuVK4ilRBRx5EpK4UriJV0GFaEakrTdorIiJiMo1cpc502FREpHIKV6kzfWFLRKRyOiwsIiJiMoWriIiIyXRYuBnROVARkaZB4dqMNPdzoPrwICKuQuEqLqO5f3gQkeZD51xFRERMppGryBVKh9lFnEfhKnKF0vSOIs6jw8IiIiImU7iKiIiYTOEqIiJiMoWriIiIyRSuIiIiJlO4ioiImEzhKiIiYjKFq4iIiMkUriIiIiZTuIqIiJhM4SoiImIyp80t/MUXX/DKK6+QkJBARkYGkyZNwjAMOnbsyIwZM3Bzc2PRokVs374dd3d3pkyZQrdu3apsKyIiF+imC02fU8L1zTffJDk5GR8fHwDi4uKYOHEikZGRxMTEsG3bNoKDg9mzZw9JSUlkZWVhtVrZsGFDpW3vu+8+Z3RTRMQl6d7GTZ9ThoShoaEsXLjQ8fOBAwe47bbbAOjbty+7du0iPT2dPn36YBgGwcHBlJaWkp2dXWlbERERV+KUcB0wYADu7v8dFNvtdgzDAMDX15fc3Fzy8vLw8/NztClbXllbERERV9Ig93O9+Jxpfn4+AQEB+Pn5kZ+fX265v79/pW0vx2IxCAxsYW6nK9EQNVRP9VRPnE3PnfM1SLh27dqVtLQ0IiMjSUlJoVevXoSGhjJ//nzGjx/PqVOnsNlsBAUFVdr2ckpL7eTknANw6kn+shoXUz3Va6r1nP2Fl8r2T8zTEK8VfSnKeRokXKOjo5k+fTrx8fGEh4czYMAALBYLERERREVFYbPZiImJqbKtiIiIK3FauLZt25Z3330XgLCwMBITEyu0sVqtWK3WcsuqaisiIuIqdAGpiIiIyRSuIiIiJlO4ioiImEzhKiIiYjKFq4iIiMkUriIiIiZTuIqIiJhM4SoiImIyhauIiIjJFK4iIiImU7iKiIiYTOEqIiJiMoWriIiIyRSuIiIiJlO4ioiImEzhKiIiYjKFq4iIiMkUriIiIiZTuIqIiJhM4SoiImIyhauIiIjJFK4iIiImU7iKiIiYTOEqIiJiMoWriIiIyRSuIiIiJlO4ioiImMy9sTtQGZvNxsyZMzl06BCenp7ExsbSrl27xu6WiIhIjTTJkevWrVspLi5m3bp1PPfcc8ydO7exuyQiIlJjTTJc09PTueOOOwDo3r07X331VSP3SEREpOYMu91ub+xOXGrq1Kn079+ffv36AXDnnXeydetW3N2b5FFsERGRcprkyNXPz4/8/HzHzzabTcEqIiIuo0mGa48ePUhJSQFg3759dOrUqZF7JCIiUnNN8rBw2beFv/32W+x2O3PmzOG6665r7G6JiIjUSJMMVxEREVfWJA8Li4iIuDKFq4iIiMmumHAdM2YMR44ccWqNkydP0qNHD8aMGeP4t2jRIqf1Jy0tjc6dO7N58+ZyywcOHMikSZPqte3LefPNN+nTpw9FRUVO2X5j7hs0zOultnXvvvtuU37fzn7uyixdupTHH3+c0aNHM2bMmAa5Xv3EiRNYrVbGjBnD8OHDmTlzJnl5eZW2zczM5JNPPqlTnbS0NHr27ElWVpZj2SuvvMLGjRvrtL2a1Lv99tsZM2YMo0ePZvjw4Xz44YdOqSXm0PUtJuvQoQMJCQkNVi88PJzNmzfz0EMPAXDo0CEKCgqcXjc5OZkHH3yQzZs3M2jQIKfUaKx9a+4a4rk7fPgwn3zyCWvWrMEwDL755huio6NJTk52Sj2AwsJCfv/73xMbG8vNN98MwKZNm3juued44403KrTfvXs333//PXfffXed6nl6ejJ58mTeeecdDMOoV99rolevXrz66qsA5OfnM2bMGMLCwrj++uudXltq74oZuQKcPXuW//3f/2XcuHH8+te/ZuvWrcCF0dCLL77o+ISdm5trat0FCxYwYsQIoqKi+OijjxzL//a3vzF27FieeOIJsrOz67TtLl26kJmZ6ehzcnIyAwcOBCAxMZGxY8cydOhQJkyYQHFxMRs3bmTUqFGMGDGCzz//vE4109LSCA0NZfjw4axatQq4MOKKiYlxfLL+8ccfSUtLY+jQoYwcOZL33nvP6fv23HPPsX37dgCOHDnChAkT6rR/ZRYtWsSaNWsc2xszZgzg/NdLVXXNUNVzVzZaXrNmDQsXLgTgtdde47HHHmP8+PGMHDmStLS0Gtfx9/cnMzOT9evXc/r0aa6//nrWr1/PoUOHHEd1rFYrubm5pKWlMW7cOMaPH8/DDz/s6Fdtbd++nVtvvdURrACPPfYYZ8+e5dixY4wePZqoqCh+85vf8NNPP7F06VI++OADtm3bVqd6vXr1omXLlhX6u2zZMgYPHkxUVBTz588HYNCgQZw8eRKALVu2EBsbW6eaZXx9fYmKimLLli2Vvr988cUXREVFMXToUJ5++mkKCwvrVU9q74oK14MHDzJu3DjeeecdZs+e7fijyM/P56GHHiIxMZE2bdo4rrGti8OHD5c7LJycnMzJkydZs2YNK1euZMmSJfzyyy8A9O/fn5UrV3LXXXdV+sm6pvr378/HH3+M3W5n//793HLLLdhsNnJycli+fDlJSUmUlpby5ZdfAhAQEMCaNWu4/fbb61QvKSmJoUOHEh4ejqenJ1988QVw4frkhIQEHnjgAcf+FBUVsXr1ah599FGn79vQoUPZtGkTAOvXr2fIkCF1qnk5Zr5eGlpVz92lDh48yGeffcb69et57bXX+PHHH2tV55prrmHx4sX861//Iioqivvvv59PP/2U6dOnM2PGDBISEujbty9vvfUWAKdPn2bx4sW8++67LF++nDNnztR6306cOEFoaGiF5W3btmXw4MFMmDCBdevWMXbsWA4ePMiECRP49a9/zT333FPrWmVmzpzJ8uXLycjIAC68Nj766CPWrl3L2rVrycjI4NNPP2XIkCGOD5gbN25k2LBhda5Z5qqrrmLLli2Vvr/ExMQwZ84ckpKS6NevX6Oc4rjSNevDwvn5+Xh6euLh4QFAREQES5cuZf369RiGwfnz5x1tu3btCsD//M//1Otc1KWHhd98800OHDjgGH2cP3+e//znP47+wIVQ2rFjR51rDhw4kJkzZxISEuLYppubGx4eHjz77LO0aNGCU6dOOfY3LCyszrV+/vlnUlJSyM7OJiEhgby8PBITE4ELn+TL9qfsXFZ9akHt9i0yMpLY2Fiys7NJTU3l2WefrVWtS18v1R3qM+v1Utu69VHdc1em7Mq8I0eOcNNNN2GxWLBYLNx44421qpWRkYGfnx9xcXEAfPnllzz55JMUFRUxa9YsAEpKSmjfvj0At9xyC56engB07NiR48ePc9VVV9Wq5jXXXMP+/fsr7UtRURG33HILgCMC4rxIAAAHH0lEQVRMzTg/2qpVK6ZMmUJ0dDQ9evSgqKiIm2++udx7znfffceIESMYOXIkQ4cOJS8vz5SJcTIzMxk4cCDJyckV3l9++uknx9wAQ4cOrXctqb1mPXKdNGkS6enp2Gw2zpw5w5w5c3jkkUeYP38+kZGRXHyJr7Pe0MLDw4mMjCQhIYEVK1bwwAMPEBISAuAYSf7zn/+kY8eOda4REhLCuXPnSEhI4OGHHwYgLy+PrVu38pe//IXp06djs9kc++vmVvenPTk5mcGDB7Ns2TLefvtt3n33XVJTU8nOznZ8YeVf//oXHTp0qHet2u6bYRg8/PDDxMbG0rt3b8cbXE1d+nrp1KmTY8R24MCBcm3NfL3Upm59VPXcubm5Oep9/fXXwIUPiV9++SU2m43i4mLH8po6dOgQs2fPpri4GLjwISsgIIB27doxb948EhISeP7557nzzjsB+OabbygtLaWgoIDDhw/X6RaT99xzD7t27SoXsElJSbRq1Yp+/fo5/t6Sk5NJSEjAzc0Nm81W6zqXuvvuuwkLC2PTpk14eXmxf/9+zp8/j91uZ+/evYSFheHv78+NN95IXFycKee58/LySEpKwt/fv9L3lzZt2nDs2DHgwhfL/vGPf9S7ptROsx65jhs3znFuY8CAAVx33XW8/PLLLF26lGuvvZazZ886vQ933303e/bsYeTIkZw7d457770XPz8/4MKt9VasWIGvry/z5s2rV50HH3yQ999/n7CwME6cOIHFYsHHx4fhw4cD0Lp1a3744Yd6709SUhIvv/yy42cfHx/69+/P+vXr2bRpE8uXL8fHx4eXX36Zb7/9tt71oHb7NmjQIO68807ef//9Wte59PXy0EMPMXHiRPbu3csNN9xgyr40Zt2qnrtrr72WWbNmERwcTJs2bQDo3Lkz/fr1Y9iwYbRq1QoPD49aze/dv39/jhw5wpAhQ2jRogV2u50XXniBa6+9lujoaM6fP49hGLz00kv88MMPnD9/nieffJKcnByeeuopgoKCar1/vr6+LFmyhDlz5pCTk0NpaSmdO3cmPj6es2fPEhMTw+LFi/H29mb+/PlkZmayePFibrjhBseX5upq6tSp7N69G19fXx544AFGjBiBzWajZ8+e3HvvvcCFEeQTTzzBnDlz6lRj9+7djBkzBjc3N0pLS7Fardx3333MnTu3wvvLrFmzmDJlCm5ubrRu3ZrHH3+8XvsntacZmsQUY8aMYebMmY0+TeXp06d54YUXWLFiRaP2w9WdOXOGLVu2MGrUKIqLi3nooYdYsWIFwcHBptdKS0tj7dq1jm/CijQHzXrkKleWjz/+mIULFzJz5szG7orLa9WqFV999RWDBw/GMAyGDh3qlGAVaa40chURETFZs/5Ck4iISGNQuIqIiJhM4SoiImIyhatckcy8McChQ4fYu3cvUPnk+g09ybuIND6Fq1yxym4MUKauNwb4+OOPOXz4cLVtyiZ51/cHRa4MuhRHrlhdunTh6NGj5Obm4u/v77gxQFZWFsnJyaxYsQJPT0/at2/P7Nmz+fvf/86OHTsoLCzk+PHjPPnkk/Tu3ZtNmzbh4eHhmPBh5syZjknay2452KtXL2w2G6tWrWL06NHl+rFgwQK++uorcnJy6NKlC3FxcSxcuJCMjAzOnj1LTk4Oo0aN4uOPP+bo0aPMmzeP7t27k5CQwAcffIBhGDz44IOMHTu2YX+BIlIljVzlilbZjQFycnJYuHAhK1asYM2aNfj7+7Nu3TrgwrRzb7zxBosXL2bp0qVcc801PPbYYzz++ON069YNgMGDB5OQkMCvfvUrUlNTHbUuneS9bHsBAQG88847bNiwgX379nH69GkAvL29efvttxkwYAA7duxgyZIlTJgwgc2bN3P48GE+/PBDVq9ezapVq9i6dSvff/99A/7mRKQ6GrnKFa2yGwPYbDY6dOjgmKby1ltvZefOndx888106dIFuDBhf9m8uZcqm+T+6quvLnerr0sneQfw8vIiOzvbcROCc+fOUVJSAvz35gD+/v6OuZpbtmxJUVER3377LZmZmY5p7X7++WcyMjIIDw8389cjInWkkatc0Sq7MYBhGBw5coRz584BsGfPHsfdfSqbsN8wjHITwFc3qf/Fk7wDpKSkkJWVRXx8PM8++yyFhYWO87LVbSc8PJwOHTqwcuVKEhISGDRoEJ07d67l3ouIsyhc5Yr34IMPkpWV5QjQVq1aYbVaGTt2LMOGDePs2bOMGDGiyvVvvPFGVq1axe7du2tUb+rUqXh7ewPQrVs3Tpw4wahRo3jmmWcICQmp0Q0WunTpwu23386IESMYNGgQx44d45prrqlRfRFxPk1/KCIiYjKNXEVEREymcBURETGZwlVERMRkClcRERGTKVxFRERMpnAVERExmcJVRETEZApXERERk/1/qJRyDBMDAH0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=df['MonthName'],hue=df['service'], order=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'])\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.) # move legend outside plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remapping the order to show the gap more clearly.\n",
    "Police get many more calls in February than the summer, which is counterintuitive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x11c160150>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=df['MonthName'],hue=df['service'], order=['Dec','Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov'])\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.) # move legend outside plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Breaking out a timeseries view by service**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "services=['Police','EMS','Fire']\n",
    "for s in services:\n",
    "    df[df['service']==s].groupby('Date').count()['twp'].plot(label=s,figsize=(15,5))\n",
    "    plt.title(f'Responses By Department')\n",
    "    plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Adding Heatmaps**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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>Hour</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>20</th>\n",
       "      <th>21</th>\n",
       "      <th>22</th>\n",
       "      <th>23</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day of Week</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>Fri</th>\n",
       "      <td>275</td>\n",
       "      <td>235</td>\n",
       "      <td>191</td>\n",
       "      <td>175</td>\n",
       "      <td>201</td>\n",
       "      <td>194</td>\n",
       "      <td>372</td>\n",
       "      <td>598</td>\n",
       "      <td>742</td>\n",
       "      <td>752</td>\n",
       "      <td>...</td>\n",
       "      <td>932</td>\n",
       "      <td>980</td>\n",
       "      <td>1039</td>\n",
       "      <td>980</td>\n",
       "      <td>820</td>\n",
       "      <td>696</td>\n",
       "      <td>667</td>\n",
       "      <td>559</td>\n",
       "      <td>514</td>\n",
       "      <td>474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mon</th>\n",
       "      <td>282</td>\n",
       "      <td>221</td>\n",
       "      <td>201</td>\n",
       "      <td>194</td>\n",
       "      <td>204</td>\n",
       "      <td>267</td>\n",
       "      <td>397</td>\n",
       "      <td>653</td>\n",
       "      <td>819</td>\n",
       "      <td>786</td>\n",
       "      <td>...</td>\n",
       "      <td>869</td>\n",
       "      <td>913</td>\n",
       "      <td>989</td>\n",
       "      <td>997</td>\n",
       "      <td>885</td>\n",
       "      <td>746</td>\n",
       "      <td>613</td>\n",
       "      <td>497</td>\n",
       "      <td>472</td>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <td>375</td>\n",
       "      <td>301</td>\n",
       "      <td>263</td>\n",
       "      <td>260</td>\n",
       "      <td>224</td>\n",
       "      <td>231</td>\n",
       "      <td>257</td>\n",
       "      <td>391</td>\n",
       "      <td>459</td>\n",
       "      <td>640</td>\n",
       "      <td>...</td>\n",
       "      <td>789</td>\n",
       "      <td>796</td>\n",
       "      <td>848</td>\n",
       "      <td>757</td>\n",
       "      <td>778</td>\n",
       "      <td>696</td>\n",
       "      <td>628</td>\n",
       "      <td>572</td>\n",
       "      <td>506</td>\n",
       "      <td>467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <td>383</td>\n",
       "      <td>306</td>\n",
       "      <td>286</td>\n",
       "      <td>268</td>\n",
       "      <td>242</td>\n",
       "      <td>240</td>\n",
       "      <td>300</td>\n",
       "      <td>402</td>\n",
       "      <td>483</td>\n",
       "      <td>620</td>\n",
       "      <td>...</td>\n",
       "      <td>684</td>\n",
       "      <td>691</td>\n",
       "      <td>663</td>\n",
       "      <td>714</td>\n",
       "      <td>670</td>\n",
       "      <td>655</td>\n",
       "      <td>537</td>\n",
       "      <td>461</td>\n",
       "      <td>415</td>\n",
       "      <td>330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thu</th>\n",
       "      <td>278</td>\n",
       "      <td>202</td>\n",
       "      <td>233</td>\n",
       "      <td>159</td>\n",
       "      <td>182</td>\n",
       "      <td>203</td>\n",
       "      <td>362</td>\n",
       "      <td>570</td>\n",
       "      <td>777</td>\n",
       "      <td>828</td>\n",
       "      <td>...</td>\n",
       "      <td>876</td>\n",
       "      <td>969</td>\n",
       "      <td>935</td>\n",
       "      <td>1013</td>\n",
       "      <td>810</td>\n",
       "      <td>698</td>\n",
       "      <td>617</td>\n",
       "      <td>553</td>\n",
       "      <td>424</td>\n",
       "      <td>354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tue</th>\n",
       "      <td>269</td>\n",
       "      <td>240</td>\n",
       "      <td>186</td>\n",
       "      <td>170</td>\n",
       "      <td>209</td>\n",
       "      <td>239</td>\n",
       "      <td>415</td>\n",
       "      <td>655</td>\n",
       "      <td>889</td>\n",
       "      <td>880</td>\n",
       "      <td>...</td>\n",
       "      <td>943</td>\n",
       "      <td>938</td>\n",
       "      <td>1026</td>\n",
       "      <td>1019</td>\n",
       "      <td>905</td>\n",
       "      <td>731</td>\n",
       "      <td>647</td>\n",
       "      <td>571</td>\n",
       "      <td>462</td>\n",
       "      <td>274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wed</th>\n",
       "      <td>250</td>\n",
       "      <td>216</td>\n",
       "      <td>189</td>\n",
       "      <td>209</td>\n",
       "      <td>156</td>\n",
       "      <td>255</td>\n",
       "      <td>410</td>\n",
       "      <td>701</td>\n",
       "      <td>875</td>\n",
       "      <td>808</td>\n",
       "      <td>...</td>\n",
       "      <td>904</td>\n",
       "      <td>867</td>\n",
       "      <td>990</td>\n",
       "      <td>1037</td>\n",
       "      <td>894</td>\n",
       "      <td>686</td>\n",
       "      <td>668</td>\n",
       "      <td>575</td>\n",
       "      <td>490</td>\n",
       "      <td>335</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Hour          0    1    2    3    4    5    6    7    8    9   ...   14   15  \\\n",
       "Day of Week                                                    ...             \n",
       "Fri          275  235  191  175  201  194  372  598  742  752  ...  932  980   \n",
       "Mon          282  221  201  194  204  267  397  653  819  786  ...  869  913   \n",
       "Sat          375  301  263  260  224  231  257  391  459  640  ...  789  796   \n",
       "Sun          383  306  286  268  242  240  300  402  483  620  ...  684  691   \n",
       "Thu          278  202  233  159  182  203  362  570  777  828  ...  876  969   \n",
       "Tue          269  240  186  170  209  239  415  655  889  880  ...  943  938   \n",
       "Wed          250  216  189  209  156  255  410  701  875  808  ...  904  867   \n",
       "\n",
       "Hour           16    17   18   19   20   21   22   23  \n",
       "Day of Week                                            \n",
       "Fri          1039   980  820  696  667  559  514  474  \n",
       "Mon           989   997  885  746  613  497  472  325  \n",
       "Sat           848   757  778  696  628  572  506  467  \n",
       "Sun           663   714  670  655  537  461  415  330  \n",
       "Thu           935  1013  810  698  617  553  424  354  \n",
       "Tue          1026  1019  905  731  647  571  462  274  \n",
       "Wed           990  1037  894  686  668  575  490  335  \n",
       "\n",
       "[7 rows x 24 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# using .unstack() to pivot the data into a matrix\n",
    "df.groupby(by=['Day of Week','Hour']).count()['service'].unstack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "dayHour = df.groupby(by=['Day of Week','Hour']).count()['service'].unstack()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Easier to see the high counts are working hours on all weekdays, with a slight drop on Sunday**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11b1cb690>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,4))\n",
    "sns.heatmap(dayHour,cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Adding a clustermap view for specific time/day correlations**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.matrix.ClusterGrid at 0x11b18ef10>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.clustermap(dayHour,linecolor='black',linewidths=.10,cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**How about by Month?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "monthHour = df.groupby(by=['Day of Week','Month']).count()['service'].unstack()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Saturdays in January are weirdly active, Sundays in December the least active**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120a83750>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(monthHour,cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**This is a little easier to see with the clustermap**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.matrix.ClusterGrid at 0x120bc3250>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.clustermap(monthHour,linecolor='black',linewidths=.10,cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}