911 Calls Project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5"
   },
   "source": [
    "# For this Capstone Project we will be analyzing some 911 call data from Kaggle. \n",
    "\n",
    "# Just go along with this notebook and try to complete some tasks using my Python and Data Science skills!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0",
    "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a"
   },
   "outputs": [],
   "source": [
    "# First of all, I will import the two libraries that will help me analyze the 911 data. \n",
    "# One of them is the poweful Pandas.🐼\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_uuid": "573b7c3c9b9e601cd75f296acb966fadf80bbf86"
   },
   "outputs": [],
   "source": [
    "# Secondly, I will import the libraries for data visualization.\n",
    "# For a greater practicality, I will tap a code which will enable to watch the graphs after coding them.\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "% matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "_uuid": "25da1205250796ae2e664242d6737c260354ab4c"
   },
   "outputs": [],
   "source": [
    "# Now I will read the file that I will analyze and visualize.\n",
    "df = pd.read_csv('../input/911.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "_uuid": "491d3269ae8577eb48d8bd9e1eef0fd7b39b0245"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 423909 entries, 0 to 423908\n",
      "Data columns (total 9 columns):\n",
      "lat          423909 non-null float64\n",
      "lng          423909 non-null float64\n",
      "desc         423909 non-null object\n",
      "zip          371780 non-null float64\n",
      "title        423909 non-null object\n",
      "timeStamp    423909 non-null object\n",
      "twp          423750 non-null object\n",
      "addr         423909 non-null object\n",
      "e            423909 non-null int64\n",
      "dtypes: float64(3), int64(1), object(5)\n",
      "memory usage: 29.1+ MB\n"
     ]
    }
   ],
   "source": [
    "# Let's extract some informations from this file.\n",
    "\n",
    "df.info()   # We can see that there are more than 300,000 entries and 9 columns. \n",
    "            # There are numbers (floats and integers) and strings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "_uuid": "bf381f339871952b5395cb1eb2c93bc23dd2acbd"
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
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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 17:10:52</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 17:29:21</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 14:39:21</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 16:47:36</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 16:56:52</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 ...                        addr  e\n",
       "0  40.297876 -75.581294 ...      REINDEER CT & DEAD END  1\n",
       "1  40.258061 -75.264680 ...  BRIAR PATH & WHITEMARSH LN  1\n",
       "2  40.121182 -75.351975 ...                    HAWS AVE  1\n",
       "3  40.116153 -75.343513 ...          AIRY ST & SWEDE ST  1\n",
       "4  40.251492 -75.603350 ...    CHERRYWOOD CT & DEAD END  1\n",
       "\n",
       "[5 rows x 9 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's check the head!\n",
    "\n",
    "df.head()   # The data contains the following fields:\n",
    "\n",
    "            # lat : String variable, Latitude\n",
    "            # lng: String variable, Longitude\n",
    "            # desc: String variable, Description of the Emergency Call\n",
    "            # zip: String variable, Zipcode\n",
    "            # title: String variable, Title\n",
    "            # timeStamp: String variable, YYYY-MM-DD HH:MM:SS\n",
    "            # twp: String variable, Township\n",
    "            # addr: String variable, Address\n",
    "            # e: String variable, Dummy variable (always 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "_uuid": "33ad509c693db4133f3f1ca40056a87e676f56d2"
   },
   "outputs": [],
   "source": [
    "# Now I will answer some basic questions!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "_uuid": "749f523dee2f3c2e55f30eac2d808f4f2ec10bc1"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19401.0    28656\n",
       "19464.0    27948\n",
       "19403.0    21631\n",
       "19446.0    20496\n",
       "19406.0    14097\n",
       "Name: zip, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What're the top 5 zipcodes for 911 calls?\n",
    "\n",
    "df.zip.value_counts().head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "_uuid": "e97e4d21a8154f61570e30bafa37d9f2b73802c9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LOWER MERION    36441\n",
       "ABINGTON        25835\n",
       "NORRISTOWN      23883\n",
       "UPPER MERION    22694\n",
       "CHELTENHAM      19629\n",
       "Name: twp, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What're the top 5 townships (twp) for 911 calls?\n",
    "\n",
    "df.twp.value_counts().head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "_uuid": "435840f806cb24458da5aaba59a77037ec3f1fb8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "141"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How many unique title codes are there?\n",
    "\n",
    "df.title.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "_uuid": "5026b415b92b3a7e38308c40213c0ceff9bc7e3c"
   },
   "outputs": [],
   "source": [
    "# To better understand the informations whitin the data and posteriorly to use for a better prediction, ...\n",
    "# ... is important create a new column from 'title' column with only the Reason.\n",
    "\n",
    "df['Reason'] = df['title'].apply(lambda title: title.split(':')[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "_uuid": "8f4d8cc1194faea178d9cafafad984506358be2e"
   },
   "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>Reason</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 17:10:52</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 17:29:21</td>\n",
       "      <td>HATFIELD TOWNSHIP</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</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 14:39:21</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   ...    e  Reason\n",
       "0  40.297876 -75.581294   ...    1     EMS\n",
       "1  40.258061 -75.264680   ...    1     EMS\n",
       "2  40.121182 -75.351975   ...    1    Fire\n",
       "\n",
       "[3 rows x 10 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets check the result!\n",
    "\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "_uuid": "d1132328f75fe854266915ed8d3469691fdbb11a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EMS        208676\n",
       "Traffic    151458\n",
       "Fire        63775\n",
       "Name: Reason, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What's the most common Reason for a 911 call based in this new column?\n",
    "\n",
    "df.Reason.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "_uuid": "6e28621780c39f347ef67c3f67302d012c126581"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f87be650278>"
      ]
     },
     "execution_count": 13,
     "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": [
    "# Let's do the first graph visualization.\n",
    "# \"911 calls X Reason\"\"\n",
    "\n",
    "sns.countplot(x='Reason', data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "_uuid": "c7f5c4e4489b50f9642a8d2dc477b03b235c03e5"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What's the data type of the objects in the 'timeStamp' column?\n",
    "\n",
    "type(df['timeStamp'].iloc[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "_uuid": "0168f6cd7ec20f1ee4d61b0b34203628787cedb4"
   },
   "outputs": [],
   "source": [
    "# The timestamps are still strings. \n",
    "# I have to convert the column to DateTime objects with the purpose to better use in data analize.\n",
    "\n",
    "df['timeStamp'] = pd.to_datetime(df['timeStamp'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "_uuid": "219277bd4264c79fbe24affeff1e8377b057e18f"
   },
   "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>Reason</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 17:10:52</td>\n",
       "      <td>NEW HANOVER</td>\n",
       "      <td>REINDEER CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</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 17:29:21</td>\n",
       "      <td>HATFIELD TOWNSHIP</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>3</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 14:39:21</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>HAWS AVE</td>\n",
       "      <td>1</td>\n",
       "      <td>Fire</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         lat        lng     ...      Month  Day of Week\n",
       "0  40.297876 -75.581294     ...         12            3\n",
       "1  40.258061 -75.264680     ...         12            3\n",
       "2  40.121182 -75.351975     ...         12            3\n",
       "\n",
       "[3 rows x 13 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# One more time, to good understand the informations and get a better prediction, ...\n",
    "# ... is important create new columns, from 'timeStamp' column, called 'Hour', 'Month' and 'Day of Week'.\n",
    "\n",
    "df['Hour'] = df['timeStamp'].apply(lambda time: time.hour)\n",
    "df['Month'] = df['timeStamp'].apply(lambda time: time.month)\n",
    "df['Day of Week'] = df['timeStamp'].apply(lambda time: time.dayofweek)\n",
    "\n",
    "# Let's see the result.\n",
    "\n",
    "df.head(3) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "_uuid": "ed1232d0328c41d59fbedc4dd23559679879159f"
   },
   "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>Reason</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 17:10:52</td>\n",
       "      <td>NEW HANOVER</td>\n",
       "      <td>REINDEER CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</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 17:29:21</td>\n",
       "      <td>HATFIELD TOWNSHIP</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</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 14:39:21</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>HAWS AVE</td>\n",
       "      <td>1</td>\n",
       "      <td>Fire</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         lat        lng     ...      Month  Day of Week\n",
       "0  40.297876 -75.581294     ...         12          Thu\n",
       "1  40.258061 -75.264680     ...         12          Thu\n",
       "2  40.121182 -75.351975     ...         12          Thu\n",
       "\n",
       "[3 rows x 13 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The 'Day of Week' column has only number instead of strings, such as 'Mon', 'Sun', 'Thu' and so on.\n",
    "# I will solve this problem.\n",
    "\n",
    "dmap = {0:'Mon', 1:'Tue', 2:'Wed', 3:'Thu', 4:'Fri', 5:'Sat', 6:'Sun'}\n",
    "df['Day of Week'] = df['Day of Week'].map(dmap)\n",
    "\n",
    "# Let's check if the problem was solved.\n",
    "\n",
    "df.head(3) # Now we can see that the values in the 'Day of Week'changed from number to days of week."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "_uuid": "f6b2c7738cf48306f6e4b3e6aa2640e0884e52fe"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f87bdd72240>"
      ]
     },
     "execution_count": 18,
     "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 I can use these new columns to do a new graph using 'Day of Week' column with the hue based in the Reason column.\n",
    "\n",
    "sns.countplot(x='Day of Week',data=df,hue='Reason',palette='viridis')\n",
    "\n",
    "# To relocate the legend\n",
    "\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "_uuid": "62eacdc066467908ab0c5d0069651cfad546cb5f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f87bddb1cf8>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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q+xWzpE8CZwKnpoJKROwEdqblRZLWAccCG4CBRbsPTDGATZKOjoiNach7c5lOwczMLDNlLcySJgFXAn8ZEY1F8VpgS0Q0S3o3hUle6yNii6Ttkk4AngHOB76bdpsDXABcm34+WMZTMbPE97TNSiuzwizpLgqTs/pJqgOupjAL+1BgXvrW04I0A/sk4BpJu4AW4DMRsSUd6rMUZnh3pzDp6+EUvxb4qaQLgZeAc7I6FzPLD/8iUDq+p51PWc7Knt5G+AfttL0PuK+dbQuBMW3EXwVOPZA+mpmZ5Y0fyWlmZpYjLsxmZmY54sJsZmaWIy7MZmZmOeLCbGZmliMuzGZmZjniwmxmZpYjlXyJhXXQwf4QgIP9/MzM9oWvmM3MzHLEhdnMzCxHXJjNzMxyxIXZzMwsR1yYzczMcqRDhVnS/I7EzMzM7MDs8etSkg4DDqfwTuU+gNKmXsCAjPtmZmbW5ezte8wXA5cDxwCLeLswbwduzLBfZmZmXdIeC3NEfAf4jqTPRcR3y9QnMzOzLqtDT/6KiO9K+nNgSPE+EXFHRv0yMzPrkjpUmCX9CBgGLAGaUzgAF2YzM7MS6ujXpcYDJ0bEZyPic+nz+b3tJGm2pM2SlhfF+kqaJ2lN+tknxSXpBklrJS2VdHzRPhek9mskXVAUHydpWdrnBknCzMysE+toYV4OHLUfx78NmLRbbCYwPyKGA/PTOsBHgOHpMwO4CQqFHLga+FNgAnB1azFPbS4q2m/3XGZmZp1KRwtzP2ClpEclzWn97G2niHgS2LJbeDJwe1q+HTi7KH5HFCwAeks6GjgdmBcRWyJiKzAPmJS29YqIBRHROqx+NmZmZp1YR1/7OKuEOftHxMa0XA/0T8sDgJeL2tWl2J7idW3E30HSDApX4QwePPgAu29mZpadjs7K/s8skkdESIosjr1bnpuBmwHGjx+feT4zM7P91dFHcu6QtD193pDULGn7fubclIahST83p/gGYFBRu4Eptqf4wDbiZmZmnVaHCnNE9IyIXhHRC+gOfBz4/n7mnAO0zqy+AHiwKH5+mp19AvBaGvJ+FJgoqU+a9DUReDRt2y7phDQb+/yiY5mZmXVK+/x2qTQ56+cUJmXtkaS7gF8DIyTVSboQuBY4TdIa4MNpHWAusB5YC9wCfDbl2wL8E/Bc+lyTYqQ2t6Z91gEP7+v5mJmZ5UlHHzAypWi1isL3mt/Y234RMb2dTae20TaAS9o5zmxgdhvxhcCYvfXDzMyss+jorOyzipabgBcpfL3JzMzMSqijs7L/NuuOmJmZWcdnZQ+U9EB6vOZmSfdJGrj3Pc3MzGxfdHTy1w8pzJo+Jn1+kWJmZmZWQh0tzLUR8cOIaEqf24DaDPtlZmbWJXW0ML8q6W8kVafP3wCvZtkxMzOzrqijhflTwDkUnm29EZgKfDKjPpmZmXVZHf261DXABentTq2vYryOQsE2MzOzEunoFfP7W4syvPU0rg9k0yUzM7Ouq6OFuSo9pxp464q5o1fbZmZm1kEdLa7XA7+W9LO0/lfA17LpkpmZWdfV0Sd/3SFpIXBKCk2JiJXZdcvMzKxr6vBwdCrELsZmZmYZ2ufXPpqZmVl2XJjNzMxyxIXZzMwsR1yYzczMcsSF2czMLEfKXpgljZC0pOizXdLlkmZJ2lAUP6Nony9JWivpeUmnF8UnpdhaSTPLfS5mZmalVvand0XE88BYAEnVwAbgAeBvgX+NiOuK20saBUwDRlN4F/Tjko5Nm78HnAbUAc9JmuPvV5uZWWdW6cdqngqsi4iXJLXXZjJwd0TsBF6QtBaYkLatjYj1AJLuTm1dmM3MrNOq9D3macBdReuXSloqaXbRs7kHAC8XtalLsfbiZmZmnVbFCrOkQ4CPAq3P374JGEZhmHsjhedzlyrXDEkLJS1saGgo1WHNzMxKrpJXzB8BfhMRmwAiYlNENEdEC3ALbw9XbwAGFe03MMXai79DRNwcEeMjYnxtbW2JT8PMzKx0KlmYp1M0jC3p6KJtHwOWp+U5wDRJh0oaCgwHngWeA4ZLGpquvqeltmZmZp1WRSZ/STqCwmzqi4vC35A0FgjgxdZtEbFC0k8pTOpqAi6JiOZ0nEuBR4FqYHZErCjbSZiZmWWgIoU5In4PvGu32Hl7aP812nj/c0TMBeaWvINmZmYVUulZ2WZmZlbEhdnMzCxHXJjNzMxyxIXZzMwsR1yYzczMcsSF2czMLEdcmM3MzHLEhdnMzCxHXJjNzMxyxIXZzMwsR1yYzczMcsSF2czMLEdcmM3MzHLEhdnMzCxHXJjNzMxypCLvY7bKG/vPs9rd9sE/K1s3bD/s6f8dlP7/X7nzmXV1LsztcOGyfeE/L52Xf/GwvPFQtpmZWY74itnMcsVXsNbVVeyKWdKLkpZJWiJpYYr1lTRP0pr0s0+KS9INktZKWirp+KLjXJDar5F0QaXOx8zMrBQqPZT9oYgYGxHj0/pMYH5EDAfmp3WAjwDD02cGcBMUCjlwNfCnwATg6tZibmZm1hnlbSh7MnByWr4deAK4KsXviIgAFkjqLeno1HZeRGwBkDQPmATcVd5uW954MpaZdVaVvGIO4DFJiyTNSLH+EbExLdcD/dPyAODlon3rUqy9uJmZWadUySvmv4iIDZL+CJgnaXXxxogISVGKRKnwzwAYPHhwKQ5p+8hXsGZmHVOxwhwRG9LPzZIeoHCPeJOkoyNiYxqq3pyabwAGFe0+MMU28PbQd2v8iTZy3QzcDDB+/PiSFPtSc+EyMzOo0FC2pCMk9WxdBiYCy4E5QOvM6guAB9PyHOD8NDv7BOC1NOT9KDBRUp806WtiipmZmXVKlbpi7g88IKm1Dz+JiEckPQf8VNKFwEvAOan9XOAMYC3QCPwtQERskfRPwHOp3TWtE8HMzMyjcZ1RRQpzRKwHjmsj/ipwahvxAC5p51izgdml7qOZmVklVPp7zGZmZlYkb99jNjM7qHlo2fbGV8xmZmY54sJsZmaWIy7MZmZmOeLCbGZmliMuzGZmZjniwmxmZpYjLsxmZmY54sJsZmaWIy7MZmZmOeLCbGZmliMuzGZmZjniwmxmZpYjLsxmZmY54sJsZmaWIy7MZmZmOeLCbGZmliMuzGZmZjlS9sIsaZCkX0laKWmFpMtSfJakDZKWpM8ZRft8SdJaSc9LOr0oPinF1kqaWe5zMTMzK7WaCuRsAv4+In4jqSewSNK8tO1fI+K64saSRgHTgNHAMcDjko5Nm78HnAbUAc9JmhMRK8tyFmZmZhkoe2GOiI3AxrS8Q9IqYMAedpkM3B0RO4EXJK0FJqRtayNiPYCku1NbF2YzM+u0KnqPWdIQ4APAMyl0qaSlkmZL6pNiA4CXi3arS7H24mZmZp1WxQqzpB7AfcDlEbEduAkYBoylcEV9fQlzzZC0UNLChoaGUh3WzMys5CpSmCV1o1CU74yI+wEiYlNENEdEC3ALbw9XbwAGFe0+MMXai79DRNwcEeMjYnxtbW1pT8bMzKyEKjErW8APgFUR8a2i+NFFzT4GLE/Lc4Bpkg6VNBQYDjwLPAcMlzRU0iEUJojNKcc5mJmZZaUSs7JPBM4DlklakmJfBqZLGgsE8CJwMUBErJD0UwqTupqASyKiGUDSpcCjQDUwOyJWlPNEzMzMSq0Ss7KfAtTGprl72OdrwNfaiM/d035mZmadjZ/8ZWZmliMuzGZmZjniwmxmZpYjLsxmZmY54sJsZmaWIy7MZmZmOeLCbGZmliMuzGZmZjniwmxmZpYjLsxmZmY54sJsZmaWIy7MZmZmOeLCbGZmliMuzGZmZjniwmxmZpYjLsxmZmY54sJsZmaWIy7MZmZmOeLCbGZmliOdvjBLmiTpeUlrJc2sdH/MzMwORKcuzJKqge8BHwFGAdMljapsr8zMzPZfpy7MwARgbUSsj4g3gbuByRXuk5mZ2X7r7IV5APBy0XpdipmZmXVKiohK92G/SZoKTIqIT6f184A/jYhLd2s3A5iRVkcAz+9Hun7AKwfQXeerTC7ncz7nK02+P46I2lJ3xt6pptIdOEAbgEFF6wNT7A9ExM3AzQeSSNLCiBh/IMdwvvLncj7nc77K5rN919mHsp8DhksaKukQYBowp8J9MjMz22+d+oo5IpokXQo8ClQDsyNiRYW7ZWZmtt86dWEGiIi5wNwypDqgoXDnq1gu53M+56tsPttHnXryl5mZ2cGms99jNjMzO6i4MO+FpNmSNktaXoZcgyT9StJKSSskXZZxvsMkPSvpf1K+f8wyX1HeakmLJT1UhlwvSlomaYmkhWXI11vSvZJWS1ol6c8yzDUinVfrZ7uky7PKl3J+If1ZWS7pLkmHZZjrspRnRVbn1dbfb0l9Jc2TtCb97JNxvr9K59giqWSzpdvJ9c30Z3OppAck9S5VPisdF+a9uw2YVKZcTcDfR8Qo4ATgkowfMboTOCUijgPGApMknZBhvlaXAavKkKfVhyJibJm+IvId4JGIGAkcR4bnGRHPp/MaC4wDGoEHssonaQDweWB8RIyhMOFyWka5xgAXUXi633HAmZLek0Gq23jn3++ZwPyIGA7MT+tZ5lsOTAGeLGGe9nLNA8ZExPuB/wW+VOKcVgIuzHsREU8CW8qUa2NE/CYt76Dwj3pmTzKLgt+l1W7pk+mkA0kDgf8H3JplnkqQdCRwEvADgIh4MyK2lSn9qcC6iHgp4zw1QHdJNcDhwG8zyvNe4JmIaIyIJuA/KRSvkmrn7/dk4Pa0fDtwdpb5ImJVROzPQ4/2J9dj6b8nwAIKz36wnHFhzilJQ4APAM9knKda0hJgMzAvIjLNB3wbuBJoyThPqwAek7QoPQEuS0OBBuCHaaj+VklHZJyz1TTgriwTRMQG4Drg/4CNwGsR8VhG6ZYDH5T0LkmHA2fwhw8TylL/iNiYluuB/mXKW26fAh6udCfsnVyYc0hSD+A+4PKI2J5lrohoTkOhA4EJaQgxE5LOBDZHxKKscrThLyLieApvILtE0kkZ5qoBjgduiogPAL+ntMOgbUoP1/ko8LOM8/ShcDU5FDgGOELS32SRKyJWAf8CPAY8AiwBmrPItZd+BBmPIlWCpK9QuHV2Z6X7Yu/kwpwzkrpRKMp3RsT95cqbhlx/Rbb3008EPirpRQpvAjtF0o8zzNd6lUdEbKZw/3VChunqgLqiUYd7KRTqrH0E+E1EbMo4z4eBFyKiISJ2AfcDf55Vsoj4QUSMi4iTgK0U7omWwyZJRwOkn5vLlLcsJH0SOBP4RPj7srnkwpwjkkTh/uSqiPhWGfLVts7KlNQdOA1YnVW+iPhSRAyMiCEUhl7/IyIyueICkHSEpJ6ty8BECkOkmYiIeuBlSSNS6FRgZVb5ikwn42Hs5P+AEyQdnv6snkqGk9sk/VH6OZjC/eWfZJVrN3OAC9LyBcCDZcqbOUmTKNxK+mhENFa6P9Y2F+a9kHQX8GtghKQ6SRdmmO5E4DwKV5KtX4E5I8N8RwO/krSUwnPH50VE5l9hKqP+wFOS/gd4FvhlRDyScc7PAXem/6Zjga9nmSz9wnEahavXTKWRgHuB3wDLKPz7keVTpO6TtBL4BXBJFhPp2vn7fS1wmqQ1FEYJrs0yn6SPSaoD/gz4paRHs8oF3Aj0BOalf1/+rRS5rLT85C8zM7Mc8RWzmZlZjrgwm5mZ5YgLs5mZWY64MJuZmeWIC7OZmVmOuDCblZikKH5wiqQaSQ37+zat9Maqzxatn7y/xzKz/HNhNiu93wNj0kNboPA94w0HcLzewGf32srMDgouzGbZmEvhLVqw25O50vt+f57eibtA0vtTfFZ6h+4TktZL+nza5VpgWHogxDdTrIfefu/znelJXGZ2EHBhNsvG3cA0SYcB7+cP3xL2j8Di9E7cLwN3FG0bCZxO4ZneV6dnp8+k8ErHsRHxxdTuA8DlwCjg3RSeGmdmBwEXZrMMRMRSYAiFq+W5u23+C+BHqd1/AO+S1Ctt+2VE7IyIVyi8PKG9Vw4+GxF1EdFC4c1LQ0p7BmZWKTWV7oDZQWwOhfcXnwy8q4P77Cxabqb9v6MdbWdmnYyvmM2yMxv4x4hYtlv8v4BPQGGGNfDKXt67vYPCiwfMrAsDibb/AAAAa0lEQVTwb9lmGYmIOuCGNjbNAmanN1A18vYrBts7zquSnpa0HHgY+GWp+2pm+eG3S5mZmeWIh7LNzMxyxIXZzMwsR1yYzczMcsSF2czMLEdcmM3MzHLEhdnMzCxHXJjNzMxyxIXZzMwsR/4/MSxOhAHjdVoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now I will do the same thing for 'Month'\n",
    "\n",
    "sns.countplot(x='Month',data=df,hue='Reason',palette='viridis')\n",
    "\n",
    "# To relocate the legend\n",
    "\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.) \n",
    "\n",
    "# We can notice that is missing some months: 9,10, and 11 are not there."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "_uuid": "2078cc8a3dccfac3190c7b4fa7ce50a63db1c5ba"
   },
   "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>Reason</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Day of Week</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</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>1</th>\n",
       "      <td>37824</td>\n",
       "      <td>37824</td>\n",
       "      <td>37824</td>\n",
       "      <td>33480</td>\n",
       "      <td>37824</td>\n",
       "      <td>37824</td>\n",
       "      <td>37812</td>\n",
       "      <td>37824</td>\n",
       "      <td>37824</td>\n",
       "      <td>37824</td>\n",
       "      <td>37824</td>\n",
       "      <td>37824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>32828</td>\n",
       "      <td>32828</td>\n",
       "      <td>32828</td>\n",
       "      <td>28963</td>\n",
       "      <td>32828</td>\n",
       "      <td>32828</td>\n",
       "      <td>32817</td>\n",
       "      <td>32828</td>\n",
       "      <td>32828</td>\n",
       "      <td>32828</td>\n",
       "      <td>32828</td>\n",
       "      <td>32828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>37666</td>\n",
       "      <td>37666</td>\n",
       "      <td>37666</td>\n",
       "      <td>33416</td>\n",
       "      <td>37666</td>\n",
       "      <td>37666</td>\n",
       "      <td>37651</td>\n",
       "      <td>37666</td>\n",
       "      <td>37666</td>\n",
       "      <td>37666</td>\n",
       "      <td>37666</td>\n",
       "      <td>37666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>33583</td>\n",
       "      <td>33583</td>\n",
       "      <td>33583</td>\n",
       "      <td>29488</td>\n",
       "      <td>33583</td>\n",
       "      <td>33583</td>\n",
       "      <td>33575</td>\n",
       "      <td>33583</td>\n",
       "      <td>33583</td>\n",
       "      <td>33583</td>\n",
       "      <td>33583</td>\n",
       "      <td>33583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>35644</td>\n",
       "      <td>35644</td>\n",
       "      <td>35644</td>\n",
       "      <td>31114</td>\n",
       "      <td>35644</td>\n",
       "      <td>35644</td>\n",
       "      <td>35628</td>\n",
       "      <td>35644</td>\n",
       "      <td>35644</td>\n",
       "      <td>35644</td>\n",
       "      <td>35644</td>\n",
       "      <td>35644</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         lat    lng   desc     ...       Reason   Hour  Day of Week\n",
       "Month                          ...                                 \n",
       "1      37824  37824  37824     ...        37824  37824        37824\n",
       "2      32828  32828  32828     ...        32828  32828        32828\n",
       "3      37666  37666  37666     ...        37666  37666        37666\n",
       "4      33583  33583  33583     ...        33583  33583        33583\n",
       "5      35644  35644  35644     ...        35644  35644        35644\n",
       "\n",
       "[5 rows x 12 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's see if we can maybe fill in this information by plotting the information in another way.\n",
    "# I will create a gropuby object called 'byMonth', where I group the DataFrame by the month column and use the count() method for aggregation.\n",
    "\n",
    "byMonth = df.groupby('Month').count()\n",
    "\n",
    "# Let's chck the result!\n",
    "\n",
    "byMonth.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "_uuid": "c68633e7e1a7f2935b733a32596aa835619e167e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f87bdcba320>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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61MpLh9p480QHyxYlcddVxVy3KhtblFQHDoUnKhvJS0vggoLg/o4Wup28eCg42wsvBBocxshNTcAZa4/YvMPQiJeaFg/vKpnZ1L7c1AQykuLYXXea2y8OcufUlE529fuCweE2XjncOloldNXiZG6/uIgXD7XwmYffZHm2a8EGiVPdA/ylpo2/eed5QS+vXZSRyG/eqKd3cBhnrP7pm4r+FxrDZpOITkofbe1haMQEXDbjbCJCeX6Kbhs6R/qHRni9tn10dOCfJp2RFMe7SxfxzpJMLivOICMpDoAR7wqe2tPI9547PBokvnB1MdeuXDhBYuveJka8Zla1lCbzdlK6lxXTnNCxEGlwOEtplos/VZ0Mdzcm5M8VBFpwbyLl+an8qaqFzr4hUhJigtU1hW8NyuGW7tHRwc6jpxgY9hJrt/GOJWncesFy3lmcyYoc14Tfiu02YVN5Ljeev5gnKxu597nDfPoXCytIVFQ2UpKVNKvf8ckUpvvWOhw/1aPBIQAaHM5Smu3ikV11tHoGyHTFhbs7Z6hq8hBjF87LDHyD9bOVWYvh9tZ3cllxRrC6tmB19AzylyNtvHSolZcPt9HU6dtOfWlmIh9aX8C7SjK56Lz0ad3GsNuEW9bmclPZmUFiRU4yd11VzLUrs+ZlkGg43cfrtR383bUlITl/wehaB01KB0KDw1nGJqUjLTgcbO5iaWYSMfaZTzLzJ6Ir609rcJiB4REvb9Wd5uVDrbx4uI099acxBpLjHVxWnMHnizO5vDiDvLTA615Nxh8kbjw/hyf3NHLvczV8+hdvsDInmbuu9gWJ+bTt5ZOVjQDcXBachW9nS0mIIT0xVtc6BEiDw1lKrOmsB5s9XLossv54Vjd72HDe7BYFpSTEcF5mIm+d0LxDoOrae3nxUCsvH27l1ZpTeAaGsYnvFt1dVxVzeXEmZXkpOGYRtM/FYbdx69o8bjp/MRWVjXz/+Rr+5qH5FyQqdjdSnp86+g0/FArdTq0vFiANDmfJdMXhToyNuKT06d5Bmjr7Z7T47Wzleam8dLhNN1w/h30NnfxmVx0vHW7jWJvvm2ZuagI3luVweXEmly7NIMU5tzkbh93GX12Qx81li3lidyPff/4wf/PQG6xa7LvddE0UB4malm4ONHXxf25cGdLPKXIn8tqx9pB+xnyhwWECJVmRt/FP9QzLZkykLD+Vx95qoLGzn9zUhFmfbz7p7B3i3/94kF/sPE68w86G89K5/eJCLi/OZGlmYkT88XXYbbz3wjw2lb8dJO6wgsQXri7h6hWLIqKf01FR2YhN4MbzZ7ZPdKAK3U4e391A/9AI8TGzL+g3n2lwmEBptotHd9Xh9ZqISfz5y2ZMtxrrREa3Da07rcHBYozhd2828K2tVXT0DrL54iK+eE1JRM/oGhskHreCxKe27Iq6IGGM4cnKRjac52ZRcnxIP6vQ7cQYqO/oZdmi2f9bms+mvEkqIvEi8pqIVIrIfhH5utUuInKPiBwSkSoR+fyY9ntFpEZE9ojIBWPOtVlEDluPzWPaLxSRvdZ77pUw/0aXZrvoHRyh4XRfOLtxhupmD+mJsUFJki/PcRFrt+l6B0tVUxcf+NF2/u43lRS4nVR87jL+5eZVER0YxnLYbbzvwjye+9/v4jvvOx9P/zCf2rKLm/77Ff504GTEl+XY29DJsbYeNoVgbcPZ/KW7dT/pqQUychgArjTGdItIDPCKiDwDrADygeXGGK+ILLKOvx4oth4XAfcBF4lIOnA3sA4wwBsiUmGM6bCO+RSwE9gKbASeCdZFTtfYpHT+NHZbC6WqZg+lWRPPj5+uOIedFYuTeWuBBwdP/xDfffYwD26vJTnewb+9dw3vvzA/YkaL0+Ww23j/unxuWZvL42818P3na/jkll2syU3hC1cXc+XyyBxJVOxuJMYubFwV2ltK4Ms5gJbuDsSUIwfj469EF2M9DPAZ4BvGGK91XIt1zCZgi/W+HUCqiOQA1wHPGmParYDwLLDRei3ZGLPD+L7ibAFuCeI1TltJVhJAxOQdvF7DoVnUVJrI2vxU9tZ3Mjyy8Cq0GmN4YncDV/3Hi/z81WN88B35PP+lK/jgOwqiNjCMFWMFiee+9C7+3/vOp7NviE88uIub//svPFcVWSMJr9fw1J4m3lWyaE4S/GnOGFzxDt0yNAABzb0TEbuI7AZa8P2B3wksBT4oIrtE5BkRKbYOzwXqxry93mo7V3v9BO0T9eMO6/N2tbaGroCWKz6G3NSEiJmxdKK9l76hEVYEcdVoWX4KfUMj1LRGbgXaUKhp8fDhn+7krl/vJis5nt9/9lL+9dY1pCVOv8ptpIux2/iAP0i893xO9w3yiQd3sekHf+H56sgIEq/VttPc1R+SchkTERGK3Im6EC4AAQUHY8yIMaYcyAPWi8hqIA7oN8asA34C3B+6bo7248fGmHXGmHWZmbPfV/ZcSrNdEbOf9GjZjCCOHMqsxXC7F8h6h97BYb79TDXXf+9l9jV08s1bVvP4nZeOJufnsxi7jQ9Yo6P/997z6egd5OMP7OILj+wO+94lFZWNJMTYuXrFoqkPDhLfWge9rTSVaa3aMcacBl7AlxOoBx6zXvo9cL71vAFfLsIvz2o7V3veBO1hVZrt4khrN0MRcNulqsmDTaA4iLMrlmQkkhzvoLJ+fgcHYwx/2NfE1f/xIv/z4hE2lefy/N9dwUc3FAZtI5loMTZIfOmaEp7a08R77n0lbBMTBoe9bN3bxLWrsua0SmqRO5H6jr6I+LcdyQKZrZQpIqnW8wTgGqAaeBx4t3XYu4BD1vMK4HZr1tIGoNMY0wRsA64VkTQRSQOuBbZZr3WJyAZrltLtwBPBu8SZKc1yMTRiRhdAhVN1cxdFGYkkxAZvXraIUJafyu66zqCdM9LUtvXwsQde59O/eJPkhBh+8+mL+ff3l41WQV2oYuw2/vaqYh65YwMjXsN773uVH714BK93bm8zvVLTyuneIW4O8qY+UylwOxnxGho6Imc2YiQKJFznAA+KiB1fMHnUGPOUiLwCPCwiXwS6gU9ax28FbgBqgF7gYwDGmHYR+SbwunXcN4wx/qWKnwUeABLwzVIK20wlP/+Mpepmz+jzcKlu9rB6cUrQz7s2P5X/fqFm3tW37x8a4Yd/PsL/vHiEWLuNf75xJZsvLgxZeYtota4ona2fv5wvP7aHbz1TzV+OnOI/3l82ZzXFKnY3kpIQw+XFob1FfLaxM5aKMmZexHK+m/IvgjFmD7B2gvbTwHsmaDfAnZOc634myE0YY3YBqwPo75xZuigRu0041OyBsvD1o2dgmBPtvbz3grypD56msvxUvAb2NXSxfkl60M8fDs9Xn+RfKg5wor2Xm8sW87X3rCArxAurolmKM4YffvgCfvnaCb7x5AGu/97L/OcHynjnDDeUClTf4Ah/PHCSTeWLiXXMbdAuGrOvg5qcfpWaRJzDzpKMxLBPZz100oMxBKWm0tn85bt313UE/dxzrb6jl09t2cXHH9hFjF345Scv4t4PrdXAEAAR4cMXFVLxuctIT4zh9vtf41vPVIX0nvxz1SfpHRwJ+j7Rgch0xZEQY9fgMIX5cy8hBEqzXOxtCO89eX9NpVBsTpKRFEdeWgKVUZx3GBge4acvH+P7zx9GEP5x43I+cdmSOf82Oh+UZrt44s7L+ObTB/jRi0fZcbSd79+2NiRVUp/Y3UhWchwXLZldleGZEBGdsRQA/Rd0DqXZLk6099I7OBy2PlQ3dZEU5whZDSRfUjo6Zyy9criN6//rZb6z7SDvLl3En770Lj5zxVINDLOQEGvnX29dww8/fAHHWrt5z70vU2HtsxAsnX1DvHiwlRvPXxy2GWO+tQ4aHM5F/xWdgz8Rffhk+BaKVTV7KM12hWzlbnleKg2n+2j1DITk/KHQ3NnPnb98k4/8bCcjxvDAx97BfR+5UIsIBtENa3LYetfllGS7+Pyv3uIfflsZtC9J2/Y1MzjinfNZSmMVZjipa+9jZI5naEUTDQ7n4N8VLlwrpY0xVDd1hSTf4Fde8HaF1kg3NOLlJy8d5ar/+DN/OnCSL15dwrYvvJMrSuduAdVCkpfm5JE7NvC5dy/jN2/Uc+P3X2F/4+xvQVZUNlLodnJ+XvBn4AWqMD2RwREvTZ06nXUyGhzOoSDdSXyMLWxJ6eaufrr6h0MaHFYtTsZuk4hfDNfi6efGe1/hnq1VXHSem2e/+C7uurpYa/KHmMNu4++uK+XhT1xEd/8wt/7gVR74y7EZl95o8fTz6pE2bi5bHNYigDpjaWoaHM7BbhOKF4WvjEZ1U/A2+JmMM9ZBSZYr4vMO979SS01rNz/66IX8bPO6kG4lqca7ZFkGz9x1OZcVZ/AvTx7gU1veoKNncNrneXpPE17DnJTnPpfCDK3OOhUNDlMozXaNzhiaa1VWTaXSEI4cwLf5T2Xd6TlfIRuo/qERHnn9BNeuzOK6VdkRWXZ6IXAnxfGzzev4Pzeu5KVDrVz/vZfZcfTUtM5RUdnIipzksG+0k5McT6zDxgkdOUxKg8MUSrNctHoGaJ/Bt6TZqm7ykJuaQHJ8aEsZl+en0NU/HLHfop6sbKSjd4jbLy4Kd1cWPBHh45ct4bHPXkJCrJ2//skO/vPZQwGVfq9r7+WtE6fDmoj2s9mEgnRnxP7ORwINDlMoCWNSurq5ixVBrMQ6mfL8NICIvLVkjOHB7bWUZCWx4bz5sYp7Plidm8KTf3sZt67N497nDvPXP9lJ4xQ7J/qnxN5UFvpNfQJR5HZqzuEcNDhMwZ8Mnuu8w8DwCEdae1gexD0cJrNsURLOWHtEzlh6q+40+xq6uP3iIr2dFGGS4hz8xwfK+K8PlrO/sZPrv/cyf9jXPOnxFbsbWVeYRl5aZOSLCq21DpGwr0Uk0uAwhUWuOFISYuZ8xtKRlh5GvCaoezhMxm4T1uSmROTIYcurtbjiHNy6dsL9n1QEuGVtLk9//nIK0p18+hdv8M+P76N/aOSMYw42ezh40jNnm/oEotDtpH/IS0sUrfGZSxocpiAilGa55vy20ugGPyFORvuVF6RyoKmLgeGRqQ+eI62eAbbubea9F+aRGKeVXiJZUUYiv/vMJXzq8iU8tOM4t/zgLxwe84WqorIBu024YU1k3FIC38gBfKXd1XgaHAJQmu3iULNnToef1c0eYh220fLCoVael8rQiKGqKTJ2vwN45PUTDI54+ejFheHuigpArMPG196zkp9/7B20ega46b9f4devncAYw5OVTVyy1B1Re2mMrnXQ/aQnpMEhACXZLjwDwzR19s/ZZ1Y1dVGSlTRnexCMVmg9ERkVWodHvPxixwkuL85gaWZSuLujpuHdpYt45q7LWVeYzpcf28ttP94xWkI9kuSmJuCwiRbgm4QGhwCUZs39jKXqZs+cJKP9clLiWeSKo7I+Miq0PnvgJM1d/WzW6atRaVFyPFs+vp5/3LicN453EOuwcd3q7HB36wwOu428tARqdcbShPRGbgBGg8NJD+9eHvo6Pm3dA7R6BuYs3wBvbxsaKTOWHtxeS15awpz891ahYbMJn7liKZcXZ3C6dyjk63VmotCdqCOHSejIIQApzhiyk+PnbORwMIR7OJxLeX4qR9t66OwdmtPPPdvBZg87jrbz0Q2FYSvprIJndW4KlxVnhLsbEypyOzne1qvTWSegwSFApdlzN2PJX64j1GUzzlZu5R3CXYRvy/Za4hw2PrAuP6z9UPNfgTsRz8BwWCogRDoNDgEqzXZR09odUJmA2apu6iIjKW7OZ3asyUtBJLzluzv7hnjszQY2lS8mLTE2bP1QC4N/xpLmHcbT4BCgkiwXg8PeOfklqm72zEnZjLMlx8ewNDMprIvhfvdGPX1DI1pHSc0J/1qHE+2adzibBocAzVUZjeERL4dOeuY0GT1WWV4qlfWnw3IP1us1PLTjOBcWprE6N3wbwaiFIz89ARGobdORw9mmDA4iEi8ir4lIpYjsF5GvW+0PiMgxEdltPcqtdhGRe0WkRkT2iMgFY861WUQOW4/NY9ovFJG91nvulQgsorNsURIioZ/OWnuql4Fh75xOYx2rPD+Ftu5B6jvmfoesl2vaONbWw+0nlRQkAAAexklEQVS66E3NkTiHncUpCTpjaQKBjBwGgCuNMWVAObBRRDZYr/29Mabceuy22q4Hiq3HHcB9ACKSDtwNXASsB+4WkTTrPfcBnxrzvo2zvrIgi4+xU+RODHlwGC2bEYbbSvB2hdZwJKW3vFpLRlIc16+OnBILav4rynBqzmECUwYH49Nt/RhjPc51z2ETsMV63w4gVURygOuAZ40x7caYDuBZfIEmB0g2xuwwvnsZW4BbZnFNIVOaFfpd4Q42e7DbhGWLwrMquDTbRazDNudJ6ROnenn+YAt/fVEBsQ6926nmjq51mFhA/wpFxC4iu4EWfH/gd1ov3WPdOvquiPin1uQCdWPeXm+1nau9foL2iFOS7aL2VM+4ipPBVNXk4byMROIc4dkbOdZhY9Xi5DlPSv9i53HsInz4ooI5/VylCtOddPQO0dkX3vU9kSag4GCMGTHGlAN5wHoRWQ18BVgOvANIB/4xZL20iMgdIrJLRHa1traG+uPGKc1y4TVQ09I99cEzVN3cFdI9owNRnp/K3obOOZm2C9A3OMIjr9dx3epsspLj5+QzlfIbnbGkt5bOMK3xuzHmNPACsNEY02TdOhoAfo4vjwDQAIxdvZRntZ2rPW+C9ok+/8fGmHXGmHWZmZnT6XpQlIZ4V7iu/iHqO/rCNlPJrzw/lf4hL4dOhi4IjlVR2UBn3xC3b9BEtJp7RRn+tQ56a2msQGYrZYpIqvU8AbgGqLZyBVgzi24B9llvqQBut2YtbQA6jTFNwDbgWhFJsxLR1wLbrNe6RGSDda7bgSeCe5nBUeR2Emu3hWzjn0OjZTPCGxzK8qwKrXNwa8kYw4OvHmd5tov1S3QbUDX3CtKt0t0aHM4QyMghB3hBRPYAr+PLOTwFPCwie4G9QAbwf63jtwJHgRrgJ8BnAYwx7cA3rXO8DnzDasM65qfWe44Az8z+0oLPYbexdFFSyEYOVdZ5wzWN1a/Q7STVGTMnSek3jndwoEm3AVXh44x1kJUcpzOWzjJlVVZjzB5g7QTtV05yvAHunOS1+4H7J2jfBayeqi+RYHm2ix1HT4Xk3Aebu0iOd5CTEt777iIyuhgu1LZsP44r3sEtayOr1r9aWHTG0ng6Z3CaSrJcNHX2h6RyaXWTbw+HSPgGXZ6fyqGTHnoGhkP2GS1d/Wzd28QH1uXjjNXq8Sp8ity61uFsGhymabSMRktwby0ZY3wb/IQ53+BXnp+K18DehtBt/vOr1+oY9ho+qoloFWaF7kRaPQMh/TIUbTQ4TFNJiGYs1Xf00T0wHPZ8g9/5eb7aRqFKSg+NeHl453GuKM2kKGNu9slWajKFVnXWE7qf9CgNDtO0OCUeV5wj6MHBv4dDpIwc3ElxFKQ7Q5aU3ra/mRbPgG4DqiJCkbXWQfMOb9PgME0iQkm2K+jTWaubfDWV/FuSRoJQbhu65dXjFKQ7eVfJ3K9XUepsBbqvwzgaHGagJMu3K1wwy1pXn/RQ6HaSGBc5idmyvBQaO/tp6eoP6nkPNHbxWm07t19ciE23AVURIDk+BndirI4cxtDgMAOlWUl09g3R4hkI2jmrm7rCvjL6bGsLQrMY7qEdtcTH2Hj/hboNqIochW6n7uswhgaHGSi1ksbByjv0D41wrK1n9LyRYtXiFOw2Cep6h87eIX7/VgO3rs0lxRkTtPMqNVtFutbhDBocZqAky1dOO1jB4fDJbrwGVkTYyCE+xs7ybFdQRw6/eaOO/iEvH91QFLRzKhUMBW4nTV39Ia26HE00OMyAOymOjKS4oCWlq0Y3+ImskQP41jvsqevE6519fsXrNWzZfpz1RemsXBx516oWtiJ3IsZAfYfeWgINDjO2PDt4G/9UN3lIiLGPFgCLJGX5qXgGhjnaNvvh9ouHWjnR3stHdRtQFYH8ax007+CjwWGGSqxd4UaC8I364MkuSrJd2CNw5s7a/OAlpR/cXssiVxzXrcqe9bmUCjb/Wgct3e2jwWGGlme76B/yUjfLFZXGGKqaPBGXb/A7LzOJpDjHrNc71Lb18OeDrboNqIpYqc4YkuMdHNe1DoAGhxnzl9GonmVSurV7gPaewdGNhCKN3SasyU2Z9cjhoR3HcdiEv16v24CqyCQiFGUk6sjBosFhhooX+WYszTbvUN0UGXs4nEt5QSpVTV0znsXROzjMo7vquH5NDot0G1AVwXylu3XkABocZiwxzkFBunPWM5aq/TOVInTkAL6d4Ya9hgNWiY/pevytRjz9w2zWRLSKcIXpThpO9zE0R/unRzINDrPgL6MxG9VNHrKT40lLjA1Sr4Kv3J+UPjH9W0vGGLZsr2VlTjIXFqYFuWdKBVeh28mI19DQ0RfuroSdBodZKM1O4lhbDwPDM180UxVBezhMJjslnuzk+BmtlH69toPqZg+bLymMiE2MlDoXf/l4zTtocJiV0uxkRryGo60z+0UaGvFypKU7ovMNfmX5KTOasfTg9lpSEmK4uSw3+J1SKsj8ax0076DBYVb85bVnemvpWFsPgyPeiM43+JXlp1J7qpeOnsGA39Pc2c+2fc188B35JMTaQ9g7pYIjMykOZ6xdRw5ocJiVJRmJOGwy46R0VZO/bEbkBwd/3mE6t5Z++doJRozhIxdpIlpFBxHRGUsWDQ6zEOuwsTQziUMzHDlUN3uIsQvnZSQFuWfBtyY3BRGorAtsT+nBYS+/3HmCK0sXjW6kolQ0KHI7deSABodZK8l2zXghXHVTF0szk6JixbArPobiRUnsrusI6Phn9jXR1j3A7ZcUhbZjSgVZgdtJfXtfUErjRLMp/yqJSLyIvCYilSKyX0S+ftbr94pI95if40TkERGpEZGdIlI05rWvWO0HReS6Me0brbYaEflycC5tbizPdtFwug9P/9C031vd7GFFBFZinUxZXiqV9Z0B7YC3ZftxlmQkcvmyjDnomVLBU+ROZHDES1Pnwp7OGshX1gHgSmNMGVAObBSRDQAisg44e/L6J4AOY8wy4LvAv1nHrgRuA1YBG4EfiohdROzAD4DrgZXAh6xjo0KJlZQ+dLJ7iiPP1Nk7RFNnf1Qko/3K8lNp7xmkrv3c/2j2NXTyxvEOPrpBtwFV0UdnLPlMGRyMj/8vX4z1MNYf9e8A/3DWWzYBD1rPfwtcJb4J7puAXxtjBowxx4AaYL31qDHGHDXGDAK/to6NCqWjwWF6t5aqI3gPh8mMLoabIim9ZXstCTF23nth3hz0Sqng0uqsPgHd7La+4e8GWoBnjTE7gc8BFcaYprMOzwXqAIwxw0An4B7bbqm32iZrjwp5aQk4Y+3Tns7qz1NE08ihNNtFnMN2zvUOHT2DPLG7kVsvyCUlQbcBVdEnOzmeWIdtwY8cHIEcZIwZAcpFJBX4vYi8E3g/cEUI+zaOiNwB3AFQUBAZ1T1tNqF4BmU0qpu7SHPGsMgVF6KeBV+M3cbqKSq0PrqrjoFhL7drHSUVpWw2oTDdSW0QNriKZtOaJmOMOQ28ALwbWAbUiEgt4BSRGuuwBiAfQEQcQApwamy7Jc9qm6x9os//sTFmnTFmXWZm5nS6HlKlWUnTvq1U1eRheXZy1JWUKM9PZV9D54SFyUa8hod2HOeiJelRsepbqcnoWofAZitlWiMGRCQBuAZ4wxiTbYwpMsYUAb1WAhqgAthsPX8f8LzxTW+pAG6zZjMtAYqB14DXgWIRWSIisfiS1hXBu8TQK81O5lTPIG3dAwEd7/UaDp2M/JpKEynLT2Vg2DvhSOmF6hbqO/rYrNNXVZQrdDs53t4T0My8+SqQ20o5wINWAtoGPGqMeeocx/8MeMgaSbTj+2OPMWa/iDwKHACGgTut21WIyOeAbYAduN8Ys3+mFxQOY8toZCyb+jZRXUcvvYMjrIjCb9fleW9vG7o6N+WM1x7cXkt2cjzXrMwKQ8+UCp4it5P+IS8tngGyFugeJFMGB2PMHmDtFMckjXnejy8fMdFx9wD3TNC+Fdg6VV8iVUm27/IPNnu4NIB5/VX+DX6icOSQn55AemIslXWn+ciGt/MKR1q7eflwG1+6poQYe+Qv6lPqXAr9M5baehZscNB/xUGQmRRHemJswEnp6uYuRKB4UfQFBxGhLC9lXI2lh7YfJ8Yu3KbbgKp5wD+ddSHnHTQ4BIGIUJKVFHABvuomD0vciVFbqbQ8P43DLd2jq8J7Bob53Rv1vGdNDplRNPtKqcksTo3HYZMFvdZBg0OQLM9O5vBJD94A6rFUN3dF5S0lv7L8FIyBvQ2+Iny/f6sBz8Cw1lFS84bDbiM/3akjBzV7JVkuegZHaDh97tISvYPDHG/vjeqpnmVjktL+bUDX5Kaw1lpBrdR8UJDum7G0UGlwCJLSMUnpczl0shtjomtl9NnSEmMpcjuprDvNjqPtHDrZze0X6zagan4pcjs53ta7YKezanAIEn8BvqnyDtXWBj/RVI11ImX5qVTWdbJley1pzhhuKlsc7i4pFVSF7kQ8A8O0T2P3w/lEg0OQuOJjyE1NmHLkUN3sISnOQW5qwhz1LDTK8lJp7urnD/ub+eA7CoiPic7kulKTKcrwVWetXaB5Bw0OQVQSQBmNqqYuSrKSor6UdXmBL78gwIcv0umrav4pHJ3OujDzDhocgqg0O5kjrd0T1h0CMMZQ3eyJqjLdk1mZk0ys3caVy7PIT9dtQNX8k5eWgE0W7sghoKqsKjCl2UkMjRiOtfWM5iDGau7qp7NviBVRnIz2i4+xs+UT61mSkRjurigVEnEOO4tTE3TkoGavZEyNpYlUj5bNiP6RA8CG89wLtrSAWhgK3Qt3rYMGhyBampmE3SaTBwervXQejByUWgh8pbt15KBmKT7GTpHbOel01urmLnJTE0iO1x3SlIoGRW4nHb1DdPYOhbsrc06DQ5Atz06edMZSdZMnqhe/KbXQjM5YWoArpTU4BFlJlosT7b30Dg6f0T4wPMKR1u6orqmk1ELjr866EGcsaXAIstLsJIyBwye7z2g/0tLDsNdEdU0lpRaaAmua9vEFuJ+0BocgK7X++J+dd6hu9pfN0JGDUtEiIdZOdnI8x9t15KBmqSDdSZzDNm7G0sFmD7EO2+gwVSkVHQrczgU5Y0mDQ5DZbULxBGU0qpo9lGQl4dAtNJWKKkVup+YcVHCUZiWPrmnwq27q0nyDUlGo0J1Iq2eAnoHhqQ+eRzQ4hEBpdhKtnoHRUr+nugdo8QzoNFalotBC3U9ag0MI+Mto+G8t+fMPOnJQKvoUuq0ZSwss76DBIQT8QcAfFKr8wUFnKikVdfzBYaHlHaYMDiISLyKviUiliOwXka9b7T+z2vaIyG9FJMlqjxORR0SkRkR2ikjRmHN9xWo/KCLXjWnfaLXViMiXg3+ZcysrOY7keMfodNaDzV1kJMWRkRQX5p4ppabLFR9DRlIsJxbYKulARg4DwJXGmDKgHNgoIhuALxpjyowx5wMngM9Zx38C6DDGLAO+C/wbgIisBG4DVgEbgR+KiF1E7MAPgOuBlcCHrGOjloj4ymhYI4bqZo+ub1AqihWkO6lt05HDGYyPf7lvjPUwxpguAPHtKp8A+Hfh3gQ8aD3/LXCVdcwm4NfGmAFjzDGgBlhvPWqMMUeNMYPAr61jo1pJdhIHT3oYHvFysFlrKikVzYoipDrr8IgXr9dMfWAQBJRzsL7h7wZagGeNMTut9p8DzcBy4PvW4blAHYAxZhjoBNxj2y31Vttk7VGtNMuFp3+YHUfbGRj2jq6cVkpFn0J3Io2d/fQPjYS1H//z4hE+8KPt42q3hUJAwcEYM2KMKQfygPUistpq/xiwGKgCPhiyXlpE5A4R2SUiu1pbW0P9cbPiDwaP724A0JGDUlGsKMOXlK4LYxmNY2093Pt8DVnJ8ThjQ7+J57RmKxljTgMv4MsZ+NtG8N0Keq/V1ADkA4iIA0gBTo1tt+RZbZO1T/T5PzbGrDPGrMvMzJxO1+dcSVYSANv2NWO3CcsWJYW5R0qpmSoMc3VWYwxf+/1e4uw2/s9Nc5OSDWS2UqaIpFrPE4BrgIMissxqE+BmoNp6SwWw2Xr+PuB5Y4yx2m+zZjMtAYqB14DXgWIRWSIisfiS1hXBusBwSXXGkpUch2dgmPMyEomPsYe7S0qpGSoK81qHx95s4NUjp/iH65fP2da8gYxNcoAHrVlFNuBR4GngZRFJBgSoBD5jHf8z4CERqQHa8f2xxxizX0QeBQ4Aw8Cd1qgDEfkcsA2wA/cbY/YH6frCqjQ7mZNdrfNmz2ilFqpUZywpCTFhWSXd3jPI/336ABcUpPLh9QVz9rlTBgdjzB5g7QQvXTrJ8f3A+yd57R7gngnatwJbp+pLtCnNSuKlQ62ab1BqHih0O6kNw8jhnqer8PQP862/Oh+bTebsc3WFdAj5y2joGgelol+hO3HORw6vHmnjd2/Wc8c7z6N0jr9khj7lvYBduyqbwy3dXLI0I9xdUUrNUpHbydN7Ghkc9hLrCP336v6hEb72+30Uup18/qrikH/e2XTkEEIpCTF89YYVmoxWah4odCfiNdBwum9OPu+HL9RwrK2He25ZE5a/IRoclFIqAEWjBfhCn3c4fNLDfS8e4da1uVxWHJ47DxoclFIqAP61DidCnHfweg1f/f1eEuMc/NN7VoT0s85Fg4NSSgUgIymWxFh7yEcOj+yq4/XaDr56wwrcYazkrMFBKaUCICIUhHjGUounn29trWLDeem8/8K8kH1OIDQ4KKVUgIpCvNbhm09V0T/k5Z5b1+ArPhE+GhyUUipAhe5E6tp7GQlB2ew/H2zhycpG7nz3MpZmhr8WmwYHpZQKUJHbydCIoTHI01l7B4f5p8f3sTQzkU9fcV5Qzz1TGhyUUipA/hlLwc47fO9Ph6nv6ONfb11DnCMy1kVpcFBKqQD593U4HsT9pPc3dvLTV47xwXX5XHSeO2jnnS0NDkopFaAsVzxxDlvQRg4jXsNXH9tLmjOGr9ywPCjnDBYNDkopFSCbTShId1LbFpyRw0Pba6ms7+Sfb1xJqjM2KOcMFg0OSik1DcGqztrU2cd3th3k8uIMbi5bHISeBZcGB6WUmoYit5Pj7T14Zzmd9e4n9jNiDPfcEv41DRPR4KCUUtNQmJFI/5CXFs/AjM+xbX8zfzxwkruuKqHAKugXaTQ4KKXUNMy2Omv3wDB3P7Gf5dkuPnn5kmB2Lag0OCil1DQUzbI6679vO8hJTz/f+qs1xNgj909w5PZMKaUiUE5KPDF2mdHIobLuNA9ur+WjGwpZW5AW/M4FkQYHpZSaBofdRl6ac9ozloZHvHzlsb0scsXx99eVhqh3waN7SCul1DQVzqA66/1/OcaBpi7+5yMX4IqPCVHPgkdHDkopNU1F1loHYwKbzlrX3st3nz3M1SuyuG5Vdoh7FxxTBgcRiReR10SkUkT2i8jXrfaHReSgiOwTkftFJMZqFxG5V0RqRGSPiFww5lybReSw9dg8pv1CEdlrvedeicRJv0opZSl0O+keGOZUz+CUxxpj+Ocn9mET+MamVRG5pmEigYwcBoArjTFlQDmwUUQ2AA8Dy4E1QALwSev464Fi63EHcB+AiKQDdwMXAeuBu0XEn5G5D/jUmPdtnPWVKaVUiBRNozrrU3ua+PPBVr50bSmLUxNC3bWgmTI4GJ9u68cY62GMMVut1wzwGuDf024TsMV6aQeQKiI5wHXAs8aYdmNMB/AsvkCTAyQbY3ZY59oC3BLUq1RKqSAqtNY6HJ8i79DZO8TXnzzAmtwUNl9SNAc9C56Acg4iYheR3UALvj/wO8e8FgN8FPiD1ZQL1I15e73Vdq72+gnalVIqIuWlObEJ1E4xcvj2H6pp7xngW3+1BrstOm4n+QUUHIwxI8aYcnyjg/UisnrMyz8EXjLGvByKDo4lIneIyC4R2dXa2hrqj1NKqQnFOmwsTk0458jh9dp2fvXaCT5+6RJW56bMYe+CY1qzlYwxp4EXsHICInI3kAn87zGHNQD5Y37Os9rO1Z43QftEn/9jY8w6Y8y6zMzM6XRdKaWCqsidOOnIYXDYy1cf20tuagJfvKZkjnsWHIHMVsoUkVTreQJwDVAtIp/El0f4kDHGO+YtFcDt1qylDUCnMaYJ2AZcKyJpViL6WmCb9VqXiGywZindDjwRzItUSqlgK3Q7Jx05/OjFIxxu6eabt6wiMS46l5MF0usc4EERseMLJo8aY54SkWHgOLDdmpr1mDHmG8BW4AagBugFPgZgjGkXkW8Cr1vn/YYxpt16/lngAXyznp6xHkopFbGK3Imc7h2is3eIFOfbi9qOtnbz/RdqeM+aHK5cnhXGHs7OlMHBGLMHWDtB+4TvtWYc3TnJa/cD90/QvgtYPf4dSikVmUZnLLX3cL4zFfCtafja7/cR57Bx900rw9m9WdMV0kopNQNFGb61DmPzDr97s4HtR0/xjxuXsyg5PlxdCwoNDkopNQMF6dbIwdpPur1nkHuePsCFhWn89fqCcHYtKDQ4KKXUDMTH2MlOjh8dOdzzdBWe/mH+9dY12KJsTcNENDgopdQM+WcsvVrTxu/erOdv3nUepdmucHcrKDQ4KKXUDBW5Ezna1sPXHt9HkdvJ315ZHO4uBU10TsBVSqkIUJjhpL1nkPaeQR7+5EXEx9jD3aWg0ZGDUkrNkL8661+tzeXSZRlh7k1w6chBKaVm6LLiDD52aRGfn0e3k/w0OCil1Awlx8dw902rwt2NkNDbSkoppcbR4KCUUmocDQ5KKaXG0eCglFJqHA0OSimlxtHgoJRSahwNDkoppcbR4KCUUmoc8W3cFn1EpBXfNqWRLgNoC3cnQmg+X59eW/Saz9c3m2srNMZkBnJg1AaHaCEiu4wx68Ldj1CZz9en1xa95vP1zdW16W0lpZRS42hwUEopNY4Gh9D7cbg7EGLz+fr02qLXfL6+Obk2zTkopZQaR0cOSimlxtHgECIiki8iL4jIARHZLyJ3hbtPwSYidhF5S0SeCndfgk1EUkXktyJSLSJVInJxuPsULCLyRet3cp+I/EpE4sPdp9kQkftFpEVE9o1pSxeRZ0XksPW/aeHs40xNcm3fsX4v94jI70UkNRSfrcEhdIaBLxljVgIbgDtFZGWY+xRsdwFV4e5EiHwP+IMxZjlQxjy5ThHJBT4PrDPGrAbswG3h7dWsPQBsPKvty8Bzxphi4Dnr52j0AOOv7VlgtTHmfOAQ8JVQfLAGhxAxxjQZY960nnvw/XHJDW+vgkdE8oD3AD8Nd1+CTURSgHcCPwMwxgwaY06Ht1dB5QASRMQBOIHGMPdnVowxLwHtZzVvAh60nj8I3DKnnQqSia7NGPNHY8yw9eMOIC8Un63BYQ6ISBGwFtgZ3p4E1X8B/wB4w92REFgCtAI/t26b/VREEsPdqWAwxjQA/w6cAJqATmPMH8Pbq5DIMsY0Wc+bgaxwdiaEPg48E4oTa3AIMRFJAn4HfMEY0xXu/gSDiNwItBhj3gh3X0LEAVwA3GeMWQv0EL23Jc5g3XvfhC8ALgYSReQj4e1VaBnflMx5Ny1TRL6G7/b1w6E4vwaHEBKRGHyB4WFjzGPh7k8QXQrcLCK1wK+BK0XkF+HtUlDVA/XGGP9I77f4gsV8cDVwzBjTaowZAh4DLglzn0LhpIjkAFj/2xLm/gSViPwv4EbgwyZE6xE0OISIiAi+e9ZVxpj/DHd/gskY8xVjTJ4xpghfMvN5Y8y8+fZpjGkG6kSk1Gq6CjgQxi4F0wlgg4g4rd/Rq5gnyfazVACbreebgSfC2JegEpGN+G7p3myM6Q3V52hwCJ1LgY/i+1a923rcEO5OqYD9LfCwiOwByoF/DXN/gsIaDf0WeBPYi+9vQFSvJhaRXwHbgVIRqReRTwDfBq4RkcP4RkvfDmcfZ2qSa/tvwAU8a/1d+Z+QfLaukFZKKXU2HTkopZQaR4ODUkqpcTQ4KKWUGkeDg1JKqXE0OCillBpHg4NSExARM3Zhn4g4RKR1phVorSqvnx3z8xXzsZqtmj80OCg1sR5gtYgkWD9fAzTM4nypwGenPEqpCKHBQanJbcVXeRbgQ8Cv/C9Y+wU8btXU3yEi51vt/2LV4P+ziBwVkc9bb/k2sNRatPQdqy1pzJ4RD1srlpWKCBoclJrcr4HbrM1wzufMqrpfB96yaup/Fdgy5rXlwHXAeuBuq8bWl4EjxphyY8zfW8etBb4ArATOw7eqXqmIoMFBqUkYY/YARfhGDVvPevky4CHruOcBt4gkW689bYwZMMa04Sv4Nlm56NeMMfXGGC+w2/ospSKCI9wdUCrCVeDb/+AKwB3gewbGPB9h8n9ngR6n1JzTkYNS53Y/8HVjzN6z2l8GPgy+mUdA2xT7dXjwFUtTKiroNxWlzsEYUw/cO8FL/wLcb1Vt7eXt8tCTneeUiPzF2ij+GeDpYPdVqWDSqqxKKaXG0dtKSimlxtHgoJRSahwNDkoppcbR4KCUUmocDQ5KKaXG0eCglFJqHA0OSimlxtHgoJRSapz/D5t4tyQBGptlAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now I will create a simple plot of the dataframe indicating the count of calls per month.\n",
    "# Could be any column\n",
    "\n",
    "byMonth['twp'].plot() #That's it. I got it!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "_uuid": "dc87572fc0b24adaa28c65f2fc3c7c57b31c696e"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f87bdbf06a0>"
      ]
     },
     "execution_count": 22,
     "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": [
    "# I will see if I can use seaborn's lmplot() to create a linear fit on the number of calls per month. \n",
    "# I can't forget that I need to reset the index to a column.\n",
    "\n",
    "\n",
    "sns.lmplot(x='Month',y='twp',data=byMonth.reset_index())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "_uuid": "53f4d9c091e8ec376e25bd46234540ec4e03cee1"
   },
   "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>Reason</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day of Week</th>\n",
       "      <th>Date</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 17:10:52</td>\n",
       "      <td>NEW HANOVER</td>\n",
       "      <td>REINDEER CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "      <td>2015-12-10</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 17:29:21</td>\n",
       "      <td>HATFIELD TOWNSHIP</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "      <td>2015-12-10</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 14:39:21</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>HAWS AVE</td>\n",
       "      <td>1</td>\n",
       "      <td>Fire</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "      <td>2015-12-10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         lat        lng     ...     Day of Week        Date\n",
       "0  40.297876 -75.581294     ...             Thu  2015-12-10\n",
       "1  40.258061 -75.264680     ...             Thu  2015-12-10\n",
       "2  40.121182 -75.351975     ...             Thu  2015-12-10\n",
       "\n",
       "[3 rows x 14 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# I will create a new column called 'Date' that contains the date from the timeStamp column.\n",
    "# As I sad before, these news columns helps better unsderstand the informations.\n",
    "\n",
    "df['Date']=df['timeStamp'].apply(lambda t: t.date())\n",
    "\n",
    "# Let's check!\n",
    "\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "_uuid": "98e41bb48bbff75a43716f1f1b8c3ee49799b70f"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now groupby this Date column with the count() aggregate and create a plot of counts of 911 calls.\n",
    "\n",
    "plt.figure(figsize=(14,6)) # To better distinguish the legends.\n",
    "df.groupby('Date').count()['twp'].plot()\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "_uuid": "e06bca86fd4412975562e015f59443e11b6100e4"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now I will recreate this plot, but creating 3 separate plots with each plot representing a Reason for the 911 call.\n",
    "\n",
    "plt.figure(figsize=(14,6))\n",
    "df[df['Reason']=='Traffic'].groupby('Date').count()['twp'].plot()\n",
    "plt.title('Traffic')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "_uuid": "92903459dbfce37651ad60790cc03c2a215ea911"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,6))\n",
    "df[df['Reason']=='Fire'].groupby('Date').count()['twp'].plot()\n",
    "plt.title('Fire')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "_uuid": "ebf79f40d486ebeb00c224b22a28d082a6ca973c"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,6))\n",
    "df[df['Reason']=='EMS'].groupby('Date').count()['twp'].plot()\n",
    "plt.title('EMS')\n",
    "plt.tight_layout()\n",
    "\n",
    "# we can conclude that the 'Fire' has the lowest rate of call and 'EMS' has the uppest.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "_uuid": "23f6407ffe69f3303afe972933fc955f845e31b5"
   },
   "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>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Fri</th>\n",
       "      <td>1185</td>\n",
       "      <td>1001</td>\n",
       "      <td>930</td>\n",
       "      <td>832</td>\n",
       "      <td>821</td>\n",
       "      <td>1051</td>\n",
       "      <td>1676</td>\n",
       "      <td>2689</td>\n",
       "      <td>3185</td>\n",
       "      <td>3295</td>\n",
       "      <td>3494</td>\n",
       "      <td>3667</td>\n",
       "      <td>3879</td>\n",
       "      <td>4002</td>\n",
       "      <td>4150</td>\n",
       "      <td>4514</td>\n",
       "      <td>4711</td>\n",
       "      <td>4489</td>\n",
       "      <td>3616</td>\n",
       "      <td>3254</td>\n",
       "      <td>2789</td>\n",
       "      <td>2445</td>\n",
       "      <td>2210</td>\n",
       "      <td>1866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mon</th>\n",
       "      <td>1207</td>\n",
       "      <td>974</td>\n",
       "      <td>857</td>\n",
       "      <td>784</td>\n",
       "      <td>871</td>\n",
       "      <td>1124</td>\n",
       "      <td>1729</td>\n",
       "      <td>2829</td>\n",
       "      <td>3588</td>\n",
       "      <td>3685</td>\n",
       "      <td>3422</td>\n",
       "      <td>3600</td>\n",
       "      <td>3752</td>\n",
       "      <td>3571</td>\n",
       "      <td>3547</td>\n",
       "      <td>3975</td>\n",
       "      <td>4063</td>\n",
       "      <td>4003</td>\n",
       "      <td>3512</td>\n",
       "      <td>2821</td>\n",
       "      <td>2418</td>\n",
       "      <td>2005</td>\n",
       "      <td>1698</td>\n",
       "      <td>1283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <td>1515</td>\n",
       "      <td>1332</td>\n",
       "      <td>1206</td>\n",
       "      <td>1012</td>\n",
       "      <td>936</td>\n",
       "      <td>985</td>\n",
       "      <td>1230</td>\n",
       "      <td>1640</td>\n",
       "      <td>2211</td>\n",
       "      <td>2766</td>\n",
       "      <td>3119</td>\n",
       "      <td>3428</td>\n",
       "      <td>3544</td>\n",
       "      <td>3524</td>\n",
       "      <td>3479</td>\n",
       "      <td>3284</td>\n",
       "      <td>3348</td>\n",
       "      <td>3274</td>\n",
       "      <td>3174</td>\n",
       "      <td>3036</td>\n",
       "      <td>2632</td>\n",
       "      <td>2432</td>\n",
       "      <td>2073</td>\n",
       "      <td>1913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <td>1520</td>\n",
       "      <td>1331</td>\n",
       "      <td>1263</td>\n",
       "      <td>1033</td>\n",
       "      <td>954</td>\n",
       "      <td>941</td>\n",
       "      <td>1119</td>\n",
       "      <td>1568</td>\n",
       "      <td>1933</td>\n",
       "      <td>2421</td>\n",
       "      <td>2776</td>\n",
       "      <td>2787</td>\n",
       "      <td>3078</td>\n",
       "      <td>2887</td>\n",
       "      <td>2992</td>\n",
       "      <td>2828</td>\n",
       "      <td>2855</td>\n",
       "      <td>2872</td>\n",
       "      <td>2829</td>\n",
       "      <td>2679</td>\n",
       "      <td>2362</td>\n",
       "      <td>1994</td>\n",
       "      <td>1632</td>\n",
       "      <td>1470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thu</th>\n",
       "      <td>1115</td>\n",
       "      <td>873</td>\n",
       "      <td>920</td>\n",
       "      <td>775</td>\n",
       "      <td>784</td>\n",
       "      <td>1091</td>\n",
       "      <td>1801</td>\n",
       "      <td>2913</td>\n",
       "      <td>3468</td>\n",
       "      <td>3457</td>\n",
       "      <td>3533</td>\n",
       "      <td>3514</td>\n",
       "      <td>3796</td>\n",
       "      <td>4031</td>\n",
       "      <td>3904</td>\n",
       "      <td>4139</td>\n",
       "      <td>4053</td>\n",
       "      <td>4412</td>\n",
       "      <td>3578</td>\n",
       "      <td>2923</td>\n",
       "      <td>2579</td>\n",
       "      <td>2230</td>\n",
       "      <td>1784</td>\n",
       "      <td>1486</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Hour           0     1     2     3    4   ...     19    20    21    22    23\n",
       "Day of Week                               ...                               \n",
       "Fri          1185  1001   930   832  821  ...   3254  2789  2445  2210  1866\n",
       "Mon          1207   974   857   784  871  ...   2821  2418  2005  1698  1283\n",
       "Sat          1515  1332  1206  1012  936  ...   3036  2632  2432  2073  1913\n",
       "Sun          1520  1331  1263  1033  954  ...   2679  2362  1994  1632  1470\n",
       "Thu          1115   873   920   775  784  ...   2923  2579  2230  1784  1486\n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now let's move on to creating heatmaps with seaborn and our data. \n",
    "# We'll first need to restructure the dataframe, so that the columns become the Hours and the Index becomes the Day of the Week.\n",
    "\n",
    "dayHour = df.groupby(by=['Day of Week','Hour']).count()['Reason'].unstack()\n",
    "\n",
    "# Let'see...\n",
    "dayHour.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "_uuid": "3a4ea7a068e445e146f502246228d28a58db4dce"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f87bcf89438>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Abje2+X2/4q523yMjYcy7xWdzhfwxcBRwO0BVXQj8YsM6SZIkjbH0sI2u2SSXm6rqjq3ONfyzW5IkSYvVbPpyL03yH4DlSQ4FXg58pW21JEmSxpTd4rwMOAy4B/gH4A7gFS0rJUmSNLa8iXptAN6Q5M3dviRJkuZrzGeLb7flMsljknwb+E53/PAkf9m8ZpIkSWPItcXhVODXgB8BVNVFwONbVkqSJEmL06xuzlhV1211r8WJNtWRJEkacyPe8rhQs0kur0vyGKCSrAROAi5rWy1JkqQxNeZjLmeTXP5n4P8ABwI3AGcDL2lZKUmSpHGVpdpymWTvqrqtqm4BnjfEOkmSJI2vpZpcAt9NcgvwZQY3Tf9yVV0+nGpJkiRpMZo2uayq/ZI8EHhMt706yb7A1xgkmm8bUh0lSZLGx1Iec9m1VF4OvDvJ/YGnMJjQ82TA5FKSJGmulmq3eDdD/DHAo4GDgCsZtFo+H/jGUGonSZI0bpZqcgn8PwZJ5KnAR1z6UZIkSdszU3J5AD8fb/mfkqxgkGx+FfhqVV05hPpJkiSNl6XacllVNwFndhtJdgFeBJwCHAIsH0YFJUmSxspSndCTZE8G4y23tF4+ArgC+BiD2xNJkiRpjpbsTdSB9XRd4MAbga9X1U+GUitJkqRxtVSTy6rad5gVkSRJ0uI3m7XFFyTJcuA+U8uqqmtblytJkqTha5pcJnkZcDLwA2CyO13Aw1qWK0mSNKrGfczlsukeSPLW7t9nLSD+ScCDquqwqvqlbps2sUyyNsn5Sc7//vXnLaBYSZKkEVVZ+DbCpk0ugackCfC6BcS/Drhjtk+uqnVVdWRVHXnAmqMWUKwkSdKIqh62ETZTt/ingNuA3ZLcCYTBjxOgqmqPWcS/Evh8kk8A92w5WVXvmH+VJUmSNKqmbbmsqtdU1V7AJ6pqj6rafeq/s4x/LXAOsArYfcomSZK0NC3hlksAquqEJPcBHtWdOreqfjib4FV1ykIqJ0mSNG7GfULPdpPLbkLP24HPM+gS//Mkr6mqD83itZ9jG/l1VR0z96pKkiSNgaWeXAL/DXhUVd0MkGRf4F+A7SaXwB9M2d8ZeCawea6VlCRJ0uIwm+Ry2ZbEsvMjZp5l/jNVdcFWp76cxHsMSZKkpcuWSz6V5NPAGd3xs4FPziZ4kn2mHC4DjgT2nFMNJUmSxsiSH3NZVa9J8pvAL3en1lXVR2YZ/wJ+np9vBq4GXjzXSkqSJI2NEb8J+kLNavnHqjoTOHO2QZM8Criuqg7pjk9kMN7yauDbc6+mJEnSmBjzlstZjZ2ch78BNgIkeTzwv4DTGazWs65RmZIkSdrBZtVyOQ/Lq+rWbv/ZDLrSPwx8OMmFjcqUJEkaeeM+5nK7LZdJfiPJXFs4lyfZkrgeC3x2ymOtElpJkqTRN+Yr9MwmaXw2cEWStyV58CzjngF8IclHgZ8AXwJI8gAGXeOSJElLUmrh2yibzWzx5yfZA3gu8O4kBbwLOKOqfjzNa96c5DPA/sDZVbXlbVgGvKyfqkuSJGnUzPZm6HcyWJHn/QwSxmcA30gybaJYVV+rqo9U1d1Tzl1eVd9YYJ0lSZIWr6XeLZ7kaUk+wmBt8ZXAUVV1PPBw4NVtqydJkjRmxjy5nM3kmmcCp1bVF6eerKoNSbwhuiRJ0hyM+pjJhZrNmMsTZ3jsM/1WR5IkSYvZbLrFj07y9SR3JdmYZCLJncOonCRJkhaX2Uzo+QsGM8WvAFYDvwf835aVkiRJGluNx1wmOSjJ55J8O8mlSU7a6vFXJ6kk9+6Ok+TPkqxP8q0kR0x57olJrui2aXuzp5rtbPH1DFbdmaiqdwHHzeZ1kiRJ+teGcJ/LzcCrq+ohwNHAS5I8BAaJJ/Bk4Nopzz8eOLTb1gJ/1T13H+Bk4N8DRwEnJ9l7e4XPZkLPhiSrgAuTvA24kXZrkv/MTlffut3nzEfd0iZuVrRbeGjyx9u8nejIWrbmgGaxb3/kfk3ifv9XJ5rEPeTg7zeJC7CatIm7YlOTuJPVpr4Ah+7xwzZxV9/cJO4tm3ZrEhfggatvahL39oldmsR93C6XN4l78jUnNIkL8K0rDmoSd+PGlU3iLv9pk7AAbLqjTTqw4u7tP2dRazyhp6puZJCvUVU/TnIZcCDwbeBU4LXAR6e85ATgPd19yb+WZK8k+wNPAM7ZsqR3knMYNDCeMVP5s/lU/E73vJcCdwMHMZhBLkmSpLka4q2IkhwMPAI4N8kJwA1VddFWTzsQuG7K8fXduenOz2g2s8WvSbJvt3/K9p4vSZKktpKsZdCFvcW6qlq31XN2Az4MvIJBV/nrGXSJNzVtcpkkDPrZX8qg5TJJNgN/XlVvbF0xSZKkcdTHfS67RHLddI8nWckgsXxfVZ2Z5JeAQ4CLBikeaxistngUcAODnukt1nTnbmDQNT71/Oe3V7eZusVfCTwWeFRV7VNVezMY0PnYJK/cXmBJkiRtQ/vZ4gHeCVxWVe8AqKqLq2q/qjq4qg5m0MV9RFXdBJwF/G43a/xo4I5u3OangScn2bubyPPk7tyMZuoW/x3gSVV1y8/ei6orkzwfOJvBgFBJkiTNwRBW6Hksgzzu4iQXdudeX1WfnOb5nwSeAqwHNgAvBKiqW5O8Cfh697w3bpncM5OZksuVUxPLLarqh11TqyRJkkZMVf0/mPmWIl3r5Zb9Al4yzfNOA06bS/kzJZcb5/mYJEmSprOE1xZ/+DTLPAbYuVF9JEmSxttSTS6ravkwKyJJkrQUDGHM5Q7VblkZSZIk/Vtjnlw2X8ZRkiRJS4ctl5IkScM05i2XJpeSJElD5JhLSZIk9cfkUpIkSX0Z95ZLJ/RIkiSpN7ZcSpIkDdOYt1yaXEqSJA2TyaUkSZL6kh1dgcYccylJkqTeNGu5THIV22j4rapfbFWmJEnSyLNbfN6OnLK/M/AsYJ+G5UmSJI08b0U0T1X1oynbDVX1p8BTZ3pNkrVJzk9y/nV3XNSqapIkSTtO9bCNsJbd4kdMOVzGoCVzxvKqah2wDuD4Q1874m+dJEnSPIx5htOyW/xPpuxvBq4GfrtheZIkSdrBmiWXVfXEVrElSZIWq3Efc9myW3wn4JnAwVPLqao3tipTkiRp5JlczttHgTuAC4B7GpYjSZK0aNhyOX9rquq4hvElSZIWnzFPLluu0POVJL/UML4kSZJGTO8tl0kuASa72C9MciWDbvEAVVUP67tMSZKkxcJu8bk7EDi8QVxJkqTFz+Ryzq6qqmsaxJUkSVr8TC7nbL8kr5ruwap6R4MyJUmSNAJaJJfLgd0YjLGUJEnSFI65nLsbvVG6JEnSNEwu58wWS0mSpGmkxju7bJFcHtsgpiRJ0ngY79yy/5uoV9WtfceUJEnS4tBy+UdJkiRtxQk9kiRJ6o/JpSRJkvpiy6UkSZL6M+bJZe8TeiRJkrR02XIpSZI0RHaL7yiNbjCaFW1+5MkNG5rEbarRe8Fkw6tmkd2i/z673NUs9l2bVjWJu3FyeZO4e636aZO4AHdsWt0k7qWTBzSJu+vye5rEBfjp5MomcQ/d6aYmcScadaDdZ/WPm8QFyLI2v+OWTTQJy7JNbeIOYrd5L5ZvaFjpUWByKUmSpL6Me8ulYy4lSZLUG1suJUmShsm1xSVJktSXce8WN7mUJEkaJpNLSZIk9SWTO7oGbTmhR5IkSb2x5VKSJGmY7BaXJElSX5zQI0mSpP54KyJJkiT1ZdxbLp3QI0mSpN7YcilJkjRMY95yaXIpSZI0ROPeLW5yKUmSNExjPqHHMZeSJEnqjcmlJEnSEKUWvm23jOS0JDcnuWSr8y9L8p0klyZ525Tzr0uyPsl3k/zalPPHdefWJ/nD2fx8dotLkiQN03B6xd8N/AXwni0nkjwROAF4eFXdk2S/7vxDgOcAhwEHAP+S5IHdy/4v8CTgeuDrSc6qqm/PVLDJpSRJ0hANY0JPVX0xycFbnf594C1VdU/3nJu78ycA7+/OX5VkPXBU99j6qroSIMn7u+fOmFzaLS5JkjRMk7XwbX4eCDwuyblJvpDkUd35A4Hrpjzv+u7cdOdn1Cy5TPKAJJ9OclF3/LAkr2tVniRJ0lKRZG2S86dsa2fxshXAPsDRwGuADyZJ33Vr2XL5d8ApwGR3fDHw/IblSZIkjb5a+FZV66rqyCnbulmUfD1wZg2cxyBHuzdwA3DQlOet6c5Nd35GLZPLXavqK1sOqqqATQ3LkyRJGnnDmC0+jX8CngjQTdhZBdwCnAU8J8lOSQ4BDgXOA74OHJrkkCSrGEz6OWt7hbSc0POjroIFkOTpwE0zvaBr0l0LcNi+T+KgPR7esHqSJEk7wBBuop7kDOAJwL2TXA+cDJwGnNbdnmgjcGLX+Hdpkg8ymKizGXhJVU10cV4KfBpYDpxWVZdur+yWyeVLgXcCD05yDXAj8NyZXtA16a4DOP4Brxnv29dLkqQlaUizxafLubY5RLGq3gy8eRvnPwl8ci5lN0suq2o9cEySPYFU1e2typIkSdJoaJZcJnn9VscAVNX/bFWmJEnSyBvzvtmW3eITU/Z3Bp4KbLefXpIkaZxlCGMud6SW3eJvnXqc5K3Ap1qVJ0mStChMbv8pi9kwV+jZicH9kSRJkjSmem+5TLKiqjYn+SY/H1WwHNgfcLylJEla0uwWn7vzgCOA35pybjNw05aF0iVJkpas8c4tmySXAaiq7zWILUmStLjZcjln+yZ51XQPVtU7GpQpSZK0KAzjJuo7UovkcjmwG10LpiRJkpaOFsnljVX1xgZxJUmSFj+7xefMFktJkqRpZMzvc9kiuTy2QUxJkqTxMOYtl73fRL2qbu07piRJkhaHlmuLS5IkaWvj3XBpcilJkjRMrtAjSZKk/phcSpIkqTdjPlu89wk9kiRJWrpsuZQkSRoix1xKkiSpPyaXO8g9G9vEXb4IRwKkTZ0nN2xoEnfZ5ESTuADZ3Cbu8tVtAt+1aVWTuACbq83nYtPE8iZxJxsu3rV6+aYmce+ZaPMrcs3OtzWJC7DLsnuaxD1oxe1N4u7caKmSH92za5O4ADXZ5rM8sVObhGNyZbtrb2KnNrFrRZvfQyPD5FKSJEm9cUKPJEmSNDu2XEqSJA2RE3okSZLUH5NLSZIk9WbMk0vHXEqSJKk3tlxKkiQN05i3XJpcSpIkDdOY34rI5FKSJGmInC0uSZKk/ox5cumEHkmSJPXGlktJkqRhmhzvlkuTS0mSpGEa825xk0tJkqRhMrmUJElSb8Y8uXRCjyRJknpjy6UkSdIwOaFHkiRJvanxXqLH5FKSJGmYHHMpSZIkzY4tl5IkScPkmMu5S/KqmR6vqne0KFeSJGnkjXm3eKuWy927fx8EPAo4qzv+DeC8RmVKkiSNPpPLuauqUwCSfBE4oqp+3B3/MfCJ6V6XZC2wFuCwvY7hoN0e2qJ6kiRJO86YJ5etJ/TcB9g45Xhjd26bqmpdVR1ZVUeaWEqSJC0+rSf0vAc4L8lHuuOnA6c3LlOSJGl0TXqfy3mrqjcn+Wfgcd2pF1bVN1uWKUmSNNLGvFt8GLci2gW4s6relWTfJIdU1VVDKFeSJGn0mFzOX5KTgSMZzBp/F7AS+HvgsS3LlSRJGlljfp/L1hN6ngE8DbgboKq+z89vUyRJkqQx07pbfGNVVZICSLJr4/IkSZJGWpUTehbig0n+BtgryX8EXgT8beMyJUmSRteYd4u3Wv7xFcBXgD8FngjcyWDc5R9V1TktypQkSVoUnNAzL2sYJJYPBi4Gvswg2bygUXmSJEkaAa2Wf/wDgCSrGMwWfwzwQmBdktur6iEtypUkSRp5Y34T9dazxVcDewB7dtv3gXMblylJkjS6qha+bUeSVya5NMklSc5IsnOSQ5Kcm2R9kg90jYAk2ak7Xt89fvBCfrwmyWWSdUm+DHwAeDSDLvFndeuGv7BFmZIkSYtBTU4ueJtJkgOBlwNHVtVDgeXAc4C3AqdW1QOA24AXdy95MXBbd/7U7nnz1qrl8n7ATsBNwA3A9cDtjcqSJElaPIbQcslg6OPqJCsYrJZ4I3AM8KHu8dOBp3f7J3THdI8fmyTz/fFajbk8rqvUYQzGW74aeGiSW4GvVtXJLcqe8D36AAALAElEQVSVJEla6qrqhiRvB64FfgKczWBS9e1Vtbl72vXAgd3+gcB13Ws3J7kDuBdwy3zKbzbmsgYuAT4J/DODGeP3B05qVaYkSdLIm6wFb0nWJjl/yrZ2S/gkezNojTwEOADYFThuWD9eq/tcvpxBi+VjgE0Mxlx+BTiNwa2JJEmSlqYeVuipqnXAumke/lXgqqr6IUCSM4HHMljUZkXXermGwdBFun8PAq7vutH3BH4037q1us/lwcA/Aq+sqhsblSFJkrToVPsVeq4Fjk6yC4Nu8WOB84HPAb8FvB84Efho9/yzuuOvdo9/tmr+d3pvNebyVS3iSpIkLXqN1xavqnOTfAj4BrAZ+CaDVs5PAO9P8j+6c+/sXvJO4L1J1gO3MphZPm+t1xaXJEnSkHWTp7eeQH0lcNQ2nvtT4Fl9lW1yKUmSNERD6BbfoUwuJUmShqlxt/gOV1WLfgPWLrbYiy3uYqyz74Xvhe/FeMVdjHX2vVjc74Xb/LbWa4sPy9rtP2XkYi+2uC1jL7a4LWMvtrgtYy+2uC1jG7d97MUWt2XsxRa3dWzN0bgkl5IkSRoBJpeSJEnqzbgkl9PdoX6UYy+2uC1jL7a4LWMvtrgtYy+2uC1jG7d97MUWt2XsxRa3dWzNUbqBsJIkSdKCjUvLpSRJkkbAok8ukxyX5LtJ1if5wx7jnpbk5iSX9BWzi3tQks8l+XaSS5Oc1FPcnZOcl+SiLu4pfcSdEn95km8m+XjPca9OcnGSC5Oc32PcvZJ8KMl3klyW5NE9xHxQV88t251JXtFTfV/Z/b9dkuSMJDv3EbeLfVIX99KF1Hdb10SSfZKck+SK7t+9e4z9rK7Ok0mO7DHu/+4+F99K8pEke/UU901dzAuTnJ3kgL7qPOWxVyepJPfuqc5/nOSGKZ/pp/RV3yQv697nS5O8ba5xZ6jzB6bU9+okF/YU9/AkX9vyuyjJv1nFZJ5xH57kq93vuY8l2WMecbf5vbHQ62+GuH1ce9PFXtD1N0PcXq4/9WRH3wtpIRuwHPge8IvAKuAi4CE9xX48cARwSc913h84otvfHbi8jzoDAXbr9lcC5wJH91jvVwH/AHy85/fjauDeDT4bpwO/1+2vAvbqOf5y4CbgF3qIdSBwFbC6O/4g8IKe6vlQ4BJgFwaLJvwL8IB5xvo31wTwNuAPu/0/BN7aY+x/BzwI+DxwZI9xnwys6PbfOp86TxN3jyn7Lwf+uq86d+cPAj4NXDOfa2aaOv8x8AcL/IxtK+4Tu8/aTt3xfn2+F1Me/xPgj3qq89nA8d3+U4DP9xT368CvdPsvAt40j7jb/N5Y6PU3Q9w+rr3pYi/o+pshbi/Xn1s/22JvuTwKWF9VV1bVRuD9wAl9BK6qLzJYvL1XVXVjVX2j2/8xcBmD5GKhcauq7uoOV3ZbLwNqk6wBngr8XR/xWkuyJ4Nf8u8EqKqNVXV7z8UcC3yvqq7pKd4KYHWSFQwSwe/3FPffAedW1Yaq2gx8AfjN+QSa5po4gUEiT/fv0/uKXVWXVdV35xNvO3HP7t4LgK8Ba3qKe+eUw12Z5/U3w++eU4HXNoi7INPE/X3gLVV1T/ecm3uMDUCSAL8NnNFT3AK2tCruyTyuwWniPhD4Yrd/DvDMecSd7ntjQdffdHF7uvami72g62+GuL1cf+rHYk8uDwSum3J8PT0kasOS5GDgEQxaGfuIt7zrIroZOKeqeokL/CmDL7UW61UVcHaSC5L0dRPcQ4AfAu/KoCv/75Ls2lPsLZ7DPL7UtqWqbgDeDlwL3AjcUVVn9xGbQavl45LcK8kuDFpkDuopNsB9qurGbv8m4D49xh6GFwH/3FewJG9Och3wPOCPeox7AnBDVV3UV8wpXtp1J54232EN2/BABp+7c5N8Icmjeoo71eOAH1TVFT3FewXwv7v/v7cDr+sp7qX8vNHjWSzw+tvqe6O366/v76NZxl7Q9bd13FbXn+ZusSeXi1aS3YAPA6/Y6i+ueauqiao6nMFfgkcleehCYyb5deDmqrpgwRXctl+uqiOA44GXJHl8DzFXMOia+quqegRwN4Muo14kWQU8DfjHnuLtzeDL5xDgAGDXJM/vI3ZVXcag6+ls4FPAhcBEH7G3UVaxiFoLkrwB2Ay8r6+YVfWGqjqoi/nSPmJ2fxS8njZfln8F3B84nMEfNn/SU9wVwD7A0cBrgA92LY19ei49/YHX+X3gld3/3yvpej568CLgvyS5gEE37sb5Bprpe2Mh11+L76PtxV7o9betuC2uP83PYk8ub+Bf/xW4pjs30pKsZHBRvK+qzuw7ftcF/DnguB7CPRZ4WpKrGQw7OCbJ3/cQF/hZq92WbrOPMBjqsFDXA9dPabn9EINksy/HA9+oqh/0FO9Xgauq6odVtQk4E3hMT7GpqndW1SOr6vHAbQzGKPXlB0n2B+j+nVf357AleQHw68Dzui/lvr2PeXR/TuP+DP7wuKi7DtcA30hy34UGrqofdH+UTgJ/Sz/XHwyuwTO74TrnMej1mPMkpOl0w0d+E/hAXzGBExlcezD4w7GX96KqvlNVT66qRzJIhr83nzjTfG8s+Ppr+X00XeyFXn+zqHOf15/mYbEnl18HDk1ySNea9BzgrB1cpxl1f72/E7isqt7RY9x9t8y6S7IaeBLwnYXGrarXVdWaqjqYwfv72arqpVUtya5Jdt+yz2Cg94Jn51fVTcB1SR7UnToW+PZC407Rd4vJtcDRSXbpPh/HMhhH1Isk+3X/3o/BF/I/9BWbwfV2Yrd/IvDRHmM3keQ4BsM8nlZVG3qMe+iUwxPo4foDqKqLq2q/qjq4uw6vZzCh4aaFxt6SmHSeQQ/XX+efGEzqIckDGUyqu6Wn2DD4g+w7VXV9jzG/D/xKt38M0Et3+5Trbxnw34C/nkeM6b43FnT9tfo+min2Qq+/GeI2uf40TzXkGUR9bwzGkF3O4K/BN/QY9wwG3USbGPwyf3FPcX+ZQdfFtxh0UV4IPKWHuA8DvtnFvYR5zKCcRRlPoMfZ4gxm+V/UbZf2/P93OHB+9378E7B3T3F3BX4E7Nnze3sKg1+GlwDvpZtl21PsLzFIri8Cjl1AnH9zTQD3Aj7D4Iv4X4B9eoz9jG7/HuAHwKd7iruewVjtLdffnGeVThP3w93/37eAjzGYZNDLe7HV41czv9ni26rze4GLuzqfBezfU9xVwN9378c3gGP6fC+AdwP/uefP8i8DF3TXybnAI3uKexKD76jLgbfQLV4yx7jb/N5Y6PU3Q9w+rr3pYi/o+pshbi/Xn1s/myv0SJIkqTeLvVtckiRJI8TkUpIkSb0xuZQkSVJvTC4lSZLUG5NLSZIk9cbkUtJISnLXVscvSPIXO6o+kqTZMbmUtKR0q7tIkhoxuZS06CQ5OMlnk3wryWe61YdI8u4kvzXleXd1/z4hyZeSnEW/qzVJkrbiX/CSRtXqJBdOOd6Hny/v+ufA6VV1epIXAX8GPH078Y4AHlpVV/VfVUnSFiaXkkbVT6rq8C0HSV4AHNkdPprBOukwWMLwbbOId56JpSS1Z7e4pHGyme73WpJlDNa43uLuHVIjSVpiTC4lLUZfAZ7T7T8P+FK3fzXwyG7/acDK4VZLkmRyKWkxehnwwiTfAn4HOKk7/7fAryS5iEHXua2VkjRkqaodXQdJkiSNCVsuJUmS1BuTS0mSJPXG5FKSJEm9MbmUJElSb0wuJUmS1BuTS0mSJPXG5FKSJEm9MbmUJElSb/4/A0q33l9qeGoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now I will create a HeatMap using this new DataFrame.\n",
    "\n",
    "plt.figure(figsize=(12,6))\n",
    "sns.heatmap(dayHour,cmap='viridis')\n",
    "\n",
    "# We can notice that the higher volume of call happens Wednesday and Friday between 15h and 17h."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "_uuid": "23d906d559b5151317d93209ff36acda35458e3b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.matrix.ClusterGrid at 0x7f87bcfd37f0>"
      ]
     },
     "execution_count": 30,
     "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": [
    "# Now I will create a clustermap using this DataFrame.\n",
    "\n",
    "\n",
    "sns.clustermap(dayHour,cmap='viridis')\n",
    "\n",
    "# We can notice better is this clustermap graph that the higher volume of call happens only on Friday between 15h and 17h."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "_uuid": "6209fe962ee260c8d9308e4e6f6398e116ae22b1"
   },
   "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>Month</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>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Fri</th>\n",
       "      <td>5532</td>\n",
       "      <td>4848</td>\n",
       "      <td>7344</td>\n",
       "      <td>5195</td>\n",
       "      <td>4989</td>\n",
       "      <td>5867</td>\n",
       "      <td>5380</td>\n",
       "      <td>5312</td>\n",
       "      <td>6010</td>\n",
       "      <td>5179</td>\n",
       "      <td>4525</td>\n",
       "      <td>5570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mon</th>\n",
       "      <td>5716</td>\n",
       "      <td>5214</td>\n",
       "      <td>4663</td>\n",
       "      <td>5154</td>\n",
       "      <td>5019</td>\n",
       "      <td>5045</td>\n",
       "      <td>5792</td>\n",
       "      <td>5212</td>\n",
       "      <td>4675</td>\n",
       "      <td>6385</td>\n",
       "      <td>4157</td>\n",
       "      <td>4286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <td>5103</td>\n",
       "      <td>4431</td>\n",
       "      <td>4914</td>\n",
       "      <td>4947</td>\n",
       "      <td>4275</td>\n",
       "      <td>4868</td>\n",
       "      <td>4883</td>\n",
       "      <td>4355</td>\n",
       "      <td>5023</td>\n",
       "      <td>5051</td>\n",
       "      <td>4043</td>\n",
       "      <td>5200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <td>4882</td>\n",
       "      <td>3806</td>\n",
       "      <td>3569</td>\n",
       "      <td>4628</td>\n",
       "      <td>3940</td>\n",
       "      <td>4019</td>\n",
       "      <td>5114</td>\n",
       "      <td>3963</td>\n",
       "      <td>4245</td>\n",
       "      <td>4852</td>\n",
       "      <td>3210</td>\n",
       "      <td>3896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thu</th>\n",
       "      <td>4985</td>\n",
       "      <td>4708</td>\n",
       "      <td>6010</td>\n",
       "      <td>4637</td>\n",
       "      <td>5469</td>\n",
       "      <td>5951</td>\n",
       "      <td>4954</td>\n",
       "      <td>5328</td>\n",
       "      <td>5300</td>\n",
       "      <td>4940</td>\n",
       "      <td>5978</td>\n",
       "      <td>4899</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Month          1     2     3     4     5   ...     8     9     10    11    12\n",
       "Day of Week                                ...                               \n",
       "Fri          5532  4848  7344  5195  4989  ...   5312  6010  5179  4525  5570\n",
       "Mon          5716  5214  4663  5154  5019  ...   5212  4675  6385  4157  4286\n",
       "Sat          5103  4431  4914  4947  4275  ...   4355  5023  5051  4043  5200\n",
       "Sun          4882  3806  3569  4628  3940  ...   3963  4245  4852  3210  3896\n",
       "Thu          4985  4708  6010  4637  5469  ...   5328  5300  4940  5978  4899\n",
       "\n",
       "[5 rows x 12 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now I will repeat these same plots and operations for Month as the column.\n",
    "# I'm trying to get more and better informations and visualizations from data.\n",
    "\n",
    "dayMonth = df.groupby(by=['Day of Week','Month']).count()['Reason'].unstack()\n",
    "\n",
    "# Let's check!\n",
    "\n",
    "dayMonth.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "_uuid": "3cb52edea0c9d95f20662f3bcbc9640676dcc98b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f87b25710f0>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heatmap\n",
    "\n",
    "plt.figure(figsize=(12,6))\n",
    "sns.heatmap(dayMonth,cmap='viridis')\n",
    "\n",
    "# We can notice that 'Friday' appears again, but, joining the informations from the last heatmap, the higher calls happens in March, on friday and between 15h/17h."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "_uuid": "de6a0fa3e4e7ef928ed3ea7bee6f2c71ff2482b3"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.matrix.ClusterGrid at 0x7f87b25c4550>"
      ]
     },
     "execution_count": 33,
     "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": [
    "# Clustermap\n",
    "\n",
    "sns.clustermap(dayMonth,cmap='viridis')\n",
    "\n",
    "# This map reinforce the last conclusion."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_uuid": "4ef6321ee07ab2cdc26f2de1a59c4c89c98dcab7"
   },
   "source": [
    "# That's it!\n",
    "# See you in the next Project!! 😀😎🐍"
   ]
  }
 ],
 "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": 1
}