Data Analysis 911.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Performing data analysis first"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing necessary libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd                                           #importing pandas library\n",
    "import matplotlib.pyplot as mpt                    #importing python maths plot library\n",
    "import seaborn as sb                                         #to work with more efficient statistical graph plots\n",
    "import datetime as dt                                       #to import pandas timeStamp library\n",
    "from decimal import Decimal                         #decimal library is used for more accuracy in arithmetic operations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "sb.set()                                                                  #applying default seaborn scaling and themes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reading data and storing it in a variable named data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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",
       "    </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                                               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 17:10:52        NEW HANOVER   \n",
       "1  19446.0  EMS: DIABETIC EMERGENCY  2015-12-10 17:29:21  HATFIELD TOWNSHIP   \n",
       "2  19401.0      Fire: GAS-ODOR/LEAK  2015-12-10 14:39:21         NORRISTOWN   \n",
       "3  19401.0   EMS: CARDIAC EMERGENCY  2015-12-10 16:47:36         NORRISTOWN   \n",
       "4      NaN           EMS: DIZZINESS  2015-12-10 16:56:52   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": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"Dataset.csv\")\n",
    "data.head()                                                             #default value of head is 5, and it displays top 5 rows of data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Knowing the dimensions of our dataset by using the shape facility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(423909, 9)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "423909"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape[0]                                        #gives the number of rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape[1]                                          #gives the number of columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Knowing the information of the columns in the datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "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": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Making a list of all the columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "column_names = list(data.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['lat', 'lng', 'desc', 'zip', 'title', 'timeStamp', 'twp', 'addr', 'e']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "column_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Making another column having the types of call"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.title.head()                                         #now we seperate the type of call from the title column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def call_seperator(x):\n",
    "    x= x.split(':')                         #here : is the delimeter\n",
    "    return x[0]                          #this returns the value at 0th index after splitting, which is call type in this case"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['call_type'] = data['title'].apply(call_seperator)                               #inserting values in another column- call_type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <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>call_type</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",
       "    <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",
       "      <td>EMS</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",
       "      <td>EMS</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 17:10:52        NEW HANOVER   \n",
       "1  19446.0  EMS: DIABETIC EMERGENCY  2015-12-10 17:29:21  HATFIELD TOWNSHIP   \n",
       "2  19401.0      Fire: GAS-ODOR/LEAK  2015-12-10 14:39:21         NORRISTOWN   \n",
       "3  19401.0   EMS: CARDIAC EMERGENCY  2015-12-10 16:47:36         NORRISTOWN   \n",
       "4      NaN           EMS: DIZZINESS  2015-12-10 16:56:52   LOWER POTTSGROVE   \n",
       "\n",
       "                         addr  e call_type  \n",
       "0      REINDEER CT & DEAD END  1       EMS  \n",
       "1  BRIAR PATH & WHITEMARSH LN  1       EMS  \n",
       "2                    HAWS AVE  1      Fire  \n",
       "3          AIRY ST & SWEDE ST  1       EMS  \n",
       "4    CHERRYWOOD CT & DEAD END  1       EMS  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['call_type'].nunique()                 #shows the number of unique type of calls "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['EMS', 'Fire', 'Traffic'], dtype=object)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['call_type'].unique()                                      #shows the different values or calls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EMS        208676\n",
       "Traffic    151458\n",
       "Fire        63775\n",
       "Name: call_type, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['call_type'].value_counts()                           #counts all the unique value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## We need to convert data to pandas datetime datatype as it does not have one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['timeStamp'] = pd.to_datetime(data['timeStamp'], infer_datetime_format = True)         #infer_datatime_format is used when we want the default format and not our own"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   2015-12-10 17:10:52\n",
       "1   2015-12-10 17:29:21\n",
       "2   2015-12-10 14:39:21\n",
       "3   2015-12-10 16:47:36\n",
       "4   2015-12-10 16:56:52\n",
       "Name: timeStamp, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['timeStamp'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting details of timestamp, with months, year and other things seperately."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['year'] = data['timeStamp'].dt.year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['month'] = data['timeStamp'].dt.month_name()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['day'] = data['timeStamp'].dt.day_name()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['hour'] = data['timeStamp'].dt.hour"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fetching the call details"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Making a function to get the type of emergency from the title column of the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def type_of_emergency(x):\n",
    "    x = x.split(':')\n",
    "    x= x[1]\n",
    "    return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['emergecy_type'] = data['title'].apply(type_of_emergency)                        #creating a column named emergency_type to store fetched data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>call_type</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>hour</th>\n",
       "      <th>emergecy_type</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>2015</td>\n",
       "      <td>December</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>17</td>\n",
       "      <td>BACK PAINS/INJURY</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>2015</td>\n",
       "      <td>December</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>17</td>\n",
       "      <td>DIABETIC EMERGENCY</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>2015</td>\n",
       "      <td>December</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>14</td>\n",
       "      <td>GAS-ODOR/LEAK</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",
       "      <td>EMS</td>\n",
       "      <td>2015</td>\n",
       "      <td>December</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>16</td>\n",
       "      <td>CARDIAC EMERGENCY</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",
       "      <td>EMS</td>\n",
       "      <td>2015</td>\n",
       "      <td>December</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>16</td>\n",
       "      <td>DIZZINESS</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 17:10:52        NEW HANOVER   \n",
       "1  19446.0  EMS: DIABETIC EMERGENCY 2015-12-10 17:29:21  HATFIELD TOWNSHIP   \n",
       "2  19401.0      Fire: GAS-ODOR/LEAK 2015-12-10 14:39:21         NORRISTOWN   \n",
       "3  19401.0   EMS: CARDIAC EMERGENCY 2015-12-10 16:47:36         NORRISTOWN   \n",
       "4      NaN           EMS: DIZZINESS 2015-12-10 16:56:52   LOWER POTTSGROVE   \n",
       "\n",
       "                         addr  e call_type  year     month       day  hour  \\\n",
       "0      REINDEER CT & DEAD END  1       EMS  2015  December  Thursday    17   \n",
       "1  BRIAR PATH & WHITEMARSH LN  1       EMS  2015  December  Thursday    17   \n",
       "2                    HAWS AVE  1      Fire  2015  December  Thursday    14   \n",
       "3          AIRY ST & SWEDE ST  1       EMS  2015  December  Thursday    16   \n",
       "4    CHERRYWOOD CT & DEAD END  1       EMS  2015  December  Thursday    16   \n",
       "\n",
       "         emergecy_type  \n",
       "0    BACK PAINS/INJURY  \n",
       "1   DIABETIC EMERGENCY  \n",
       "2        GAS-ODOR/LEAK  \n",
       "3    CARDIAC EMERGENCY  \n",
       "4            DIZZINESS  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Performing data visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "call_types = data['call_type'].value_counts()              #counting different types of calls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EMS        208676\n",
       "Traffic    151458\n",
       "Fire        63775\n",
       "Name: call_type, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "call_types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mpt.figure(figsize = (12,8))\n",
    "ax = call_types.plot.bar()\n",
    "for p in ax.patches:                                                                                                         #patches is used to create whatever type of patch we want for eg. rectangular patch\n",
    "    ax.annotate(Decimal(str(p.get_height())), (p.get_x(), p.get_height()))       #to annotate all the points on the plot\n",
    "mpt.xticks(rotation=0)                                                                                                   #this is used to give label on the axis\n",
    "mpt.savefig(\"Emergency type vs Frequency.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 423909 entries, 0 to 423908\n",
      "Data columns (total 15 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 datetime64[ns]\n",
      "twp              423750 non-null object\n",
      "addr             423909 non-null object\n",
      "e                423909 non-null int64\n",
      "call_type        423909 non-null object\n",
      "year             423909 non-null int64\n",
      "month            423909 non-null object\n",
      "day              423909 non-null object\n",
      "hour             423909 non-null int64\n",
      "emergecy_type    423909 non-null object\n",
      "dtypes: datetime64[ns](1), float64(3), int64(3), object(8)\n",
      "memory usage: 48.5+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()                            #fetching info again to visualize in some other way"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using groupby function to group specific feilds of data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "calls_data = data.groupby(['month', 'call_type'])['call_type'].count()           #grouped acc. to the types of calls in diff. months"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "month   call_type\n",
       "April   EMS          17255\n",
       "        Fire          4983\n",
       "        Traffic      11345\n",
       "August  EMS          17965\n",
       "        Fire          5717\n",
       "Name: call_type, dtype: int64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calls_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculating percentage of calls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "call_percentage = calls_data.groupby(level = 0).apply(lambda x: round(100*x/float(x.sum())))              #applying lambda funcs to calculate percentage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "month   call_type\n",
       "April   EMS          51.0\n",
       "        Fire         15.0\n",
       "        Traffic      34.0\n",
       "August  EMS          50.0\n",
       "        Fire         16.0\n",
       "Name: call_type, dtype: float64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "call_percentage.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting a graph accordingly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "font = {\n",
    "    'size': 'x-large',\n",
    "    'weight': 'bold'\n",
    "}\n",
    "month_order = ['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "call_percentage = call_percentage.reindex(month_order,  level=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "call_percentage = call_percentage.reindex(['EMS', 'Traffic', 'Fire'], level=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "month     call_type\n",
       "January   EMS          49.0\n",
       "          Traffic      36.0\n",
       "          Fire         15.0\n",
       "February  EMS          51.0\n",
       "          Traffic      35.0\n",
       "Name: call_type, dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "call_percentage.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Calls/Month')"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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qMDBQgwcPVseOHdWsWTNPlgYAAHDBs3IxfnlYvYD/6NEj+vOf43XJJU1KLO/bt78+/HCeAgIC9OGHie7lRUVF6tOnp2JirtNjjz2prKws/fOfL+jnn3+SJNWtG6mEhEfUsGGjimzHMo8G7V9++UWSdM899ygjI0O33XabgoOD1alTJ4WFhUmSevXqpZUrV2r06NGeLA0AAABVQN26EWedAvDDD+epoKBAP/+8R02bnjohu3nzJkmGe5vZs2eqSZOmeuKJZyRJX3yxUk88MUFz5sz3SO2/59GgffLkScXExGjy5MkqLCzUkCFDdNNNNykiIsK9TWRkpLZt21am/Zb1Lj3nKyIi1KPHs9PZevGl/s7Gl/r7fS/e0JuzsFiBAY5ybecN/Z0Pb+jPyvtX2jb0V/nK25839HY+LuT+UlP95O/vmUv2rBzH4fA757bdunXX+vWrFR19uSTpyy9XqXv3HsrPz5e/v5/S00+oTp3a8vOT/Pz81KtXb4WEBJe5Rz8/vwr5vfBo0G7durVat27tfj5w4EA9//zzGjFihHuZaZoyDONsLy8Vt2A/k9Vfjt/34i39lZe39Fee98+berPy35KfvtTPK/srL2/pz8r79/v37vTr6K/ylac/b+mtvC70/lwuly23MD8bK8cpLnbp2LE03Xnn4BLLJ09+SpIUG3uDpk59XsOG3afCwkLt3r1bAwcO0tatW1RU5NJdd92jiRMf1uLFi9SmTXu1b99RPXveVOYeXS7XGT+3Kn8L9s2bN6uwsFAxMTGSToXqBg0aKC0tzb1NWlqaIiMjPVkWAAAAqojSho5IUkREpIKDQ7Rv314dPnxIHTt2KrG+efMW+uijpfr++/9q8+ZNWrDgfS1dmqjXX5/jvj7Qkzw6vV9WVpZefPFFFRQUKDs7W0uWLNE//vEPbdiwQSdOnFBeXp5WrVqlrl27erIsAAAAeIlu3Xpo7drV+uqrL9SjR0/3ctM0NXXq8youLlbr1m3117+O0LvvLlBGRrp++mlXpdTq0WjfrVs3/fe//1X//v3lcrl0++23q23btkpISNCQIUNUWFiogQMH6pprrvFkWQAAAPAS3bv30IMPjlZgYJCio5tr165TIdowDO3bt1cffjhPQ4bcIz8/Px05cljFxcVq0ODiSqnV4+fQx40bp3HjxpVY1rdvX/Xt29fTpQAAAOA38guK9OlL/WzZr1XHjqVp6NDbSyxr1ep/1/jVrRuhkJBQtW7d9ozXPvnkc5ox4yX96U+3qHr16goODtETTzyjmjVrlb/48+D5wSoAAACokrJO5lma79ouUVEXae3ab866bty4R9yPX331LffjuLi+ios7dcK2bt26+vvfn7e3yDLgFuwAAACADS7YM9pWbjF6od4uFED58d0CVA6rtw7n81c1+fkZ8vM79/TOLpfpsemcK8oFG7St3GLU6u1CAeA0vluAymH11uF8/qomPz9Dew5mnHObZg3DvC5oM3QEAAAAsAFBGwAAALABQRsAAACwwQU7RhsAAAAlhdcKlH9gUIXvt8hZoPRM5zm3mfvWK9q9c7uKioqU8uthNbi4sSSp183xiu120x8e49dff1VCwkgFBVXTzJlv6IEHRsjpLNAtt8QrMzNDw4ffXyG9lAVBGwAAAJIk/8Ag/fLsgArfb5PHFks6d9AeOvwBSVJa6q969skEPTf1zTIdY+vWzYqObqEnn3xW//nPdwoICNDbb88rb8kVgqANAACAKmvxR3O1Z/cOZWUe04ABg3TJJZfqjTdeVUFBvrKzszVmTILq14/Sm2++pry8PD333N/13/9u1YkTx/XoowmKje2urVu36LHHntS3327UzJkvyzRdql8/Sk888YyCg0Nsq50x2gAAAKjSCgudWrBgsW69daAWL16o8eMna86c+Zo4cbLefPM1XXZZtIYPv1/XXddVEyc+oUcfnaTo6BZ64YVp7n04nU499dRkTZr0pN57b6GaNGmmzz5bbmvdnNEGAABAldbsshbux5MnP63k5K+1Zs2X+vHH7crLs3YDol9+2aOIiAhddlm0JOn++0fbUutvcUYbAAAAVVpAYKD78ahRf9WOHT8oOrq5hg79i0zT2k1sHA5/Sf+7+2R2drZSU1MqutQSCNoAAADwCidPZurgwf36y1/uV6dOnbV+/Vq5XC5Lr23UqLEyMtK1d+8vkqT589/VJ58strNcho4AAADglCJnwf/PEFLx+60INWvWUp8+/XTXXbfJ399f7dp1UH5+vqXhI0FBQZo8+Sk988wTKioq1EUXXazJk5+qkLpKQ9AGAACAJP3/XNfnnobPbhGR9fXyqx+6nw+4bWiJ9WPGPKgxYx6UJPn7++nBBx+VJMXF9VVcXF9JUps27dSmTbszlrdu3dajU/4xdAQAAACwAUEbAAAAsAFBGwAAALABY7ThlUJrVle1oHP/+uYXFCnrpLW5NQEAACoaQRteqVqQv/o+tPSc23z6Uj9leageAACA32PoCAAAAGADzmgDAABAkhQaFqRqAYF/vGEZ5Rc6lZVRMXNpexOCNgAAACRJ1QICddvCERW+348GvaYs/XHQTkv9VQ+PHaIGFzcusbzxpc3UN663rr22S4XXZieCNgAAAKqM8Np19NzUN89Y3qxhmIqKrN1uvaogaAMAAKBKmz3zBcV2iVHLlm300ENjVKtWmIKCgvTKK7M0Y8Y0bd26RcXFLsXF9dGgQXdUdrluBG0AAABUGeknjmviw391P7+2yw0l1h84sF+LFs1QVNRFWro0UZI0Z858OZ1OPfjgaDVvfoVatmzt0ZpLQ9AGAACo4i6k+0ecbejI7Jkv/G99eG1FRV0kSfr2243avXuXtmzZLEnKy8vVzz/vIWgDAADAGu4f8T9BQUHuxy6XSyNHjlVsbHdJUkZGhqpXr15ZpZ2BebQBAADgldq2ba9lyz5RUVGRcnNzNXLkX/TDD99XdllunNEGAACApFPzXX806DVb9muH+PgBOnBgv4YNu13FxcWKi+urNm3a2XKs8iBoAwAAQJKUlVFgab5ru0RE1tfLr354xvL7Rj/qnt7v448/dS/39w/QuHGPeLLEMmHoCAAAAGADgjYAAABgA4I2AADABcw0zcouoUqpyJ8HQRsAAOAC5e8fqJyck4Tt/2eapnJyTsrfP7BC9sfFkAAAABeo8PAIpaenKTs7o1Lr8PPzU/bJ3HNuc+RIplwu1xmv+/2y8+XvH6jw8IiK2VeF7AUAAABex+HwV926UZVdhiIiQjXewg150tJK3pInIiL0jGVVCUNHAAAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABtUStB+4YUXNH78eEnSjh07FB8fr169eumxxx5TUVFRZZQEAAAAVCiPB+0NGzZoyZIl7uePPPKIHn/8cX3++ecyTVMfffSRp0sCAAAAKpxHg3ZGRoamTZum+++/X5J0+PBh5efnq1WrVpKk+Ph4rVy50pMlAQAAALbw9+TBHn/8cSUkJOjo0aOSpNTUVEVERLjXR0REKCUlpcz7rVMnpMJq/L2IiFBLy7wV/Xm33/fiS71Jvt3fhfa7Wdoyb3Wh9edLvUm+25+ryGnpd9NV5JSff6CnyqpQ3vbZ81jQXrRokaKiohQTE6PExERJksvlkmEY7m1M0yzx3Krjx7Plcplleo3VNyUtLeuM1/1+WVVEf6dcSP35Wm+Sb/d3If1unn4d/VU+vltO8dX+/PwD9cuzA/5wuyaPLa5yPXvDZ8/PzyjzyV2PBe0VK1YoLS1N/fr1U2ZmpnJzc2UYhtLS0tzbHDt2TJGRkZ4qCQAAALCNx4L2O++8436cmJioTZs26fnnn1efPn20ZcsWtW3bVkuXLlXXrl09VRIAAABgG4+O0T6bqVOnatKkScrOztaVV16pIUOGVHZJAAAAwHmrlKAdHx+v+Ph4SVLz5s318ccfV0YZAAAAgG24MyQAAABgA4I2AAAAYAOCNgAAAGADgjYAAABgA4I2AAAAYAOCNgAAAGADgjYAAABgA4I2AAAAYAOCNgAAAGADgjYAAABgA4I2AAAAYAOCNgAAAGADgjYAAABgA4I2AAAAYAOCNgAAAGADgjYAAABgA4I2AAAAYAOCNgAAAGADgjYAAABgA//KLgCwi6vIqYiI0DOW/3ZZkbNA6ZlOT5YFAADKwcrf61LV+rudoA2f5ecfqF+eHXDObZo8tlhS1fgwAgCA0ln5e12qWn+3M3QEAAAAsAFBGwAAALBBuYN2Xl6eDh48WJG1AAAAAD7DctBeuHCh5s2bJ0n68ssvFRMTo549e2ro0KHKy8uzrUAAAADAG1kK2osWLdKTTz6ppKQkmaapp59+Wvn5+TJNUxs3btTcuXNtLhMAAADwLpaC9ocffihJuvzyy/X9998rJSVFbdq00TPPPCPTNLVixQpbiwQAAAC8jaXp/Q4ePKgaNWooISFBc+bMkSTFxcVp4MCB+sc//qHDhw/bWmRl8cb5GgFfcbbPn6989vhuASqPL3+3oOqxFLTz8vIUEhIiwzD07bffyjAMtWrVSsXFxXI6nQoMDLS7zkrhjfM1Ar7Cl+dB57sFqDy+/N2CqsfS0JEGDRooMzNTM2fO1IYNG1SrVi1dfvnlevHFF5WXl6dLLrnE5jIBAAAA72IpaMfFxck0Tc2aNUsFBQXq06ePJGnevHkyDEODBg2ytUgAAADA21gaOjJ69GgVFRVp7dq1uvLKK/XQQw8pMDBQjRs3Vq9evRQfH293nQAAAIBXsRS0HQ6HHnroIT300EMlli9ZskTVqlWzpTAAAADAm5UatPfs2VOmHTVr1uy8iwEAAAB8RalBu0+fPjIMw9JODMPQjz/+WGFFAQAAAN7unENHTNP0VB2oBMzlC8AOfLd4N+aZBipOqUH7vffe82QdqATM5QvADny3eDfmmQYqTqlBu0OHDp6sAwAAAPAppQbtdevWlWlHsbGx510MAAAA4CtKDdr33XcfF0MCAAAA5cTFkAAAAIANSg3aq1ev9mQdAAAAgE8pNWg3aNDAk3UAAAAAPsXSLdgladu2bdq6datycnLkcrkknRpakpmZqeTkZK1YscK2IgGciblugcphZZ5wPnsAJItBe/ny5XrkkUfOus40TcsXTQKoOMx1C1QOPnsArPKzstHcuXNlmqaioqIUGhqqOnXqqGXLlvL395dhGLr//vvtrhMAAADwKpaC9t69exUYGKjly5crPj5ejRo10oIFC/TGG2/INE0dPXrU7joBAAAAr2IpaBcVFSk0NFQ1atRQ69at9eOPP8rlcikmJka1atXSN998Y3edAAAAgFexNEY7MjJShw4d0urVq3XVVVcpPz9fy5YtU7169XTy5Ek5nYxDAwAAAH7L0hntnj17yjRNTZs2TQ0aNFCjRo00YcIE3XPPPZKkSy+91NYiAQAAAG9jKWg/8MAD6tevn5o3by5JSkhIkGEYMk1TAQEBSkhIsLVIAAAAwNtYGjoSGBioF154QcXFxZKkm266SdHR0dq9e7euvvpqbm4DAAAA/I7lG9ZIksPhcD9u0qSJmjRpUuEFAQAAAL7gnENHjh8/roSEBM2bN++MdQMGDNC0adO4EBIAAAA4i1LPaGdlZem2227TkSNHVFxcrLvuusu97qefftIPP/ygH3/8Udu2bdPs2bMVGBjokYIBAAAAb1DqGe233npLhw8flsPhOGNWET8/P11//fUyTVPffPONPv74Y9sLBQAAALxJqUH7yy+/lGEYeuqpp86YVaRp06Z6/fXXlZCQINM09cknn9heKAAAAOBNSg3ahw4dUrVq1RQfH1/qi//yl78oMDBQ+/fvt6U4AAAAD4ivAAAgAElEQVQAwFuVGrQdDodM05TL5Sr1xQ6HQw6HQwUFBbYUBwAAAHirUoP2JZdcooKCAq1Zs6bUF69fv155eXlq2LChLcUBAAAA3qrUoH3jjTfKNE1NnDhRn332WYlp/JxOp1auXKnx48fLMAzdeOONHikWAAAA8BalTu83ZMgQLVmyRAcOHNCDDz4oh8OhOnXqyDRNnThxQsXFxTJNUw0aNNA999zjyZoBAACAKq/UM9rBwcF6++23FR0dLdM0VVRUpJSUFKWmpqqoqEimaapp06Z6++23FRIS4smaAQAAgCrvnLdgb9iwoT755BOtXr1aSUlJ7pvX1KtXT507d1avXr1K3JYdAAAAwCnnDNqSZBiGevTooR49eniiHgAAAMAnlDp0BAAAAED5EbQBAAAAGxC0AQAAABuUGrSLioo8WQcAAADgU0oN2gMGDFD//v0lSTNnztTcuXM9VRMAAADg9UoN2vv371daWpqkU0H73Xff9VhRAAAAgLcrdXo/wzB04sQJjR07VpKUkZGhCRMmlLrtc889Z0+FAAAAgBcqNWi3adNGSUlJ+uKLL2QYhvLz8/XJJ5+csZ1pmmUK2q+88oo+//xzGYahgQMHatiwYUpOTtbzzz+vgoIC3XTTTUpISCh/RwAAAEAVUGrQfuKJJzR16lQdPXpU33//vQICAnT55Zef18E2bdqkb775RsuWLVNRUZHi4uIUExOjiRMnat68eYqKitJ9992ndevWKTY29ryOBQAAAFSmUoN2o0aNNH36dElS8+bNVadOHS1evPi8DtahQwe999578vf3V0pKioqLi3Xy5Ek1btxYDRs2lCT17dtXK1euJGgDAADAq/3hLdglaefOne7HTqdTmZmZCgsLU0BAQJkPGBAQoOnTp2vOnDnq3bu3UlNTFRER4V4fGRmplJSUMu8XAAAAqEosBW1JSklJ0bPPPqu1a9eqsLBQAQEB6tGjhyZMmFAiKFsxduxY/fWvf9X999+vffv2yTAM97rTY77Lok6dkDJtb4eIiNDKLsFWvtyfL/cm0Z+3oz/v5cu9SfTn7ejPMywF7ePHj+u2225TamqqTNOUdOrM9meffaZt27Zp0aJFCg8P/8P9/Pzzz3I6nWrRooWqV6+unj17auXKlXI4HO5t0tLSFBkZWaYmjh/Plstlluk1Ff0GpKVlVej+zhf9WVfVepN8uz9+N8uG/jzLlz97km/3x+9m2dBf2fn5GWU+uWvpFuwzZsxQSkqKwsLClJCQoJdfflkPPvigwsPDdfjwYc2aNcvSwQ4dOqRJkybJ6XTK6XRq9erVGjx4sPbu3av9+/eruLhYy5cvV9euXcvUBAAAAFDVWDqjvXbtWhmGobfffltXXHGFe/l1112n+Ph4ffnll5o0adIf7ic2Nlbbtm1T//795XA41LNnT918882qXbu2xowZo4KCAsXGxqp3797l7wgAAACoAiwPHQkJCSkRsiXpiiuuUGhoqE6cOGH5gGPGjNGYMWNKLIuJidGyZcss7wMAAACo6iwNHYmIiFB2drZ+/PHHEst37NihrKysMl8MCQAAAPg6S2e0r7/+en3wwQcaPny4hg4dqsaNG+vAgQOaO3euDMPQ9ddfb3OZAAAAgHexFLRHjx6tVatW6dixY5o2bZp7uWmaql27tkaMGGFbgQAAAIA3sjR0pHbt2vr444/Vs2dPORwOmaYph8Ohbt26aeHChapbt67ddQIAAABexfINa+rXr6/p06erqKhIGRkZCg8PLzH/NQAAAID/sRy03S/w9+cMNgAAAPAHLA0dAQAAAFA2BG0AAADABgRtAAAAwAYEbQAAAMAGZQramzZt0rRp0zR+/HhJUnJysoqKimwpDAAAAPBmlmYdKSwsVEJCglavXu1eNmXKFP3tb39TVFSU5syZo9DQUNuKBAAAALyNpTPas2fP1pdffqmwsDD5+5/K5jk5OTp+/Li2b9+u6dOn21okAAAA4G0sBe1PP/1UDodDH330kWrXri1JCg4O1vz58yWpxJluAAAAABaD9pEjR1SrVi01bNiwxPI2bdooNDRUaWlpthQHAAAAeCtLQTs8PFyZmZk6cuRIieVff/21Tp48qYiICFuKAwAAALyVpaDdu3dvFRcXa9CgQUpPT5ck3X333RoxYoQMw1CPHj1sLRIAAADwNpaC9rhx49SqVSulpaXJ6XTKNE1t3LhRRUVFatGihcaMGWN3nQAAAIBXsTS9X40aNfT+++9r2bJlSkpKUkZGhiIjI9WxY0f17dtXDofD7joBAAAAr2IpaEuSv7+/4uPjFR8fb2c9AAAAgE+wFLQnTJhQ6jrDMFSjRg1dfPHFuummm1SvXr0KKw4AAADwVpaC9pIlS2QYxh9uN2vWLL333ntq0aLFeRcGAAAAeDNLF0P26dNH9erVk2maioiI0DXXXKO6devKNE3VrFlTLVq0UGhoqLKysjRr1iy7awYAAACqPEtBu3v37kpJSdHDDz+s9evXa+HChVq/fr3Gjh2rnJwcJSQkaPHixfLz89N3331nd80AAABAlWcpaE+fPl01atTQ8OHD3csMw9DIkSMVEBCgqVOnqmHDhgoPD9fJkydtKxYAAADwFpZvwZ6Xl6eUlJQSy1NSUlRQUKB9+/bJ6XQqNzdXAQEBthQKAAAAeBNLF0M2bdpUO3fu1JAhQ3TnnXeqfv36Onr0qObPny/TNHXJJZdo/vz5ysvL02WXXWZ3zQAAAECVZylojxs3TiNGjNCBAwf03HPPuZebpimHw6GxY8e6x2b37NnTnkoBAAAAL2Jp6EhsbKxef/11XXHFFZJOBWw/Pz+1a9dOb7/9tm644QaFhIRo+PDhGjVqlK0FAwAAAN7A8p0hu3btqq5duyovL09ZWVmqU6dOiVuvjxgxwpYCAQAAAG9k6Yz2b1WvXl2RkZHukJ2ZmakVK1ZUeGEAAACAN7N0Rvv48eOaMGGCtm7dqpycHJmmWWK9YRiKi4uzpUAAAADAG1kK2lOnTtX69etLXR8eHl5hBQEAAAC+wNLQkaSkJBmGoUmTJqlTp05q166d3nrrLfXo0UOGYWjixIl21wkAAAB4FUtBOz09XWFhYbrzzjvVvXt3HTlyRNddd52mTJmigIAAzZ071+YyAQAAAO9iKWgHBwcrPz9fTqdTV111lY4ePaqUlBQFBQXJ399fe/futbtOAAAAwKtYCtrR0dHKz8/XqFGjdOWVVyogIEBjxozR8OHDlZubq+rVq9tdJwAAAOBVLAXt0aNHKzAwUAUFBQoKCtKNN96obdu2adOmTZKk7t2721okAAAA4G0szTrSvn17JSYmuoeIPP7445KkXbt2qW3btnr00UftqxAAAADwQpaC9pEjRxQSEqIePXpIkmrVqqWXXnpJpmlq165d2r9/v1q0aGFroQAAAIA3sRS0u3fvrqioKK1Zs+aMdXfccYfCw8P15ZdfVnhxAAAAgLc6a9A2TVNvvvmmnE6ne1lWVpZmzpxZYrucnBzl5eWpqKjI3ioBAAAAL3PWoG0YhtLT093zYxuGoZycHM2aNeuMbU3TVKNGjWwtEgAAAPA2pQ4dGTlypL744gtlZ2crMzNTfn5+Cg0Nda83DEMOh0ONGjXS2LFjPVIsAAAA4C1KDdqhoaHucdfNmzdXRESE1q5d66m6AAAAAK9m6WLInTt32l0HAAAA4FMsBW1J2rFjh9auXaucnBy5XK4z1v/tb3+r0MIAAAAAb2YpaC9evFiTJk065zYEbQAAAOB/LAXtN954Q6ZpSjp1s5rg4GBbiwIAAAC8naWgffToURmGoTlz5igmJsbumgAAAACv52dloyZNmig0NJSQDQAAAFhkKWg/8MADys7O1uLFi+2uBwAAAPAJloaOrFq1SlFRUZo0aZJeeeUV1alTRw6Hw73eMAwtWrTItiIBAAAAb2MpaC9ZskSGYcg0TaWmpio1NbXEesMwbCkOAAAA8FaWgnb//v0J0wAAAEAZWAraU6ZMsbsOAAAAwKdYuhjytNzcXCUlJbkvikxPT7elKAAAAMDbWb4F+7vvvqvp06crNzdXhmFowIABuv3229WlSxdNnDjRzhoBAAAAr2MpaC9fvlzPP/98iWVOp1P79u3Tvn371KBBA9199922FAgAAAB4I0tDR9555x0ZhqFZs2apXr16kiR/f38lJCTINE2m9gMAAAB+x1LQ3rNnj2rVqqUbbrjhfy/089O9996rWrVq6eDBg7YVCAAAAHgjS0E7KChIubm5ysvLK7H84MGDOnnypGrUqGFLcQAAAIC3shS0O3XqpMLCQo0ePVo5OTmSpFmzZrnHZXfo0MG+CgEAAAAvZCloP/LII6pZs6aSkpLcQXvmzJk6cuSIQkJC9MADD9haJAAAAOBtLAXthg0bKjExUf3791fdunXl7++vqKgo3XrrrUpMTFSTJk3srhMAAADwKpbn0W7QoAF3iAQAAAAssnxnyPXr12vkyJHu5z/++KNuueUWrV271o66AAAAAK9mKWh//fXXGjFihNasWaPs7GxJp6b82717t0aNGqXk5GRbiwQAAAC8jaWgPXv2bBUXF+vaa69VUVGRJOnKK69UbGysiouLNXv2bFuLBAAAALyNpaC9e/duVa9eXa+99prCwsIkSU2bNtWMGTNUvXp17dy509YiAQAAAG9j6WJIp9MpSXI4HGesKy4uVkFBQcVWBQAAAHg5S2e0L7/8chUUFOixxx7T3r17lZmZqd27d+vRRx+V0+nUZZddZnedAAAAgFexdEZ72LBhSkhI0NKlS7V06dIS6wzD0LBhw2wpDgAAAPBWls5o33TTTRo/fryqVasm0zTdf6pVq6ZHH31UcXFxlg84c+ZM3Xzzzbr55pv14osvSpKSk5PVt29f9ezZU9OmTStfJwAAAEAVYumMtsvl0tChQzVw4EBt3bpV6enpCg8PV+vWrRUSEmL5YMnJyfr3v/+tJUuWyDAMDR8+XMuXL9fUqVM1b948RUVF6b777tO6desUGxtb7qYAAACAymYpaMfHx6tZs2Z67LHH1KVLl3IfLCIiQuPHj1dgYKCkUzOX7Nu3T40bN1bDhg0lSX379tXKlSsJ2gAAAPBqloL2wYMHdfjwYU2dOvW8Dvbbiyb37dunzz77THfeeaciIiLcyyMjI5WSklKm/dapY/2sul0iIkIruwRb+XJ/vtybRH/ejv68ly/3JtGft6M/z7AUtDt37qyvvvpK33//va6++urzPuhPP/2k++67T3/729/kcDi0b98+9zrTNGUYRpn2d/x4tlwus0yvqeg3IC0tq0L3d77oz7qq1pvk2/3xu1k29OdZvvzZk3y7P343y4b+ys7PzyjzyV1LQbtBgwYyDEODBg3S5Zdfrnr16ikoKMgdiA3D0Msvv2zpgFu2bNHYsWM1ceJE3Xzzzdq0aZPS0tLc69PS0hQZGVmmJgAAAICqxlLQfuedd2QYhkzT1M6dO7Vr1y73urKcgT569KhGjRqladOmKSYmRpLUsmVL7d27V/v379fFF1+s5cuXa8CAAeVoBQAAAKg6LAXt9u3bV8jB3n77bRUUFGjKlCnuZYMHD9aUKVM0ZswYFRQUKDY2Vr17966Q4wEAAACVxVLQnjdvXoUcbNKkSZo0adJZ1y1btqxCjgEAAABUBZZuWHNabm6ukpKStHjxYklSenq6LUUBAAAA3s7SGW1JevfddzV9+nTl5ubKMAwNGDBAt99+u7p06aKJEyfaWSMAAADgdSwF7eXLl+v5558vsczpdGrfvn3at2+fGjRooLvvvtuWAgEAAABvZGnoyOlZR2bNmqV69epJkvz9/ZWQkCDTNLVo0SJbiwQAAAC8jaWgvWfPHtWqVUs33HDD/17o56d7771XtWrV0sGDB20rEAAAAPBGloJ2UFCQcnNzlZeXV2L5wYMHdfLkSdWoUcOW4gAAAABvZSlod+rUSYWFhRo9erRycnIkSbNmzXKPy+7QoYN9FQIAAABeyFLQfuSRR1SzZk0lJSW5g/bMmTN15MgRhYSE6IEHHrC1SAAAAMDbWAraDRs2VGJiovr376+6devK399fUVFRuvXWW5WYmKgmTZrYXScAAADgVSzPo92gQYMSt04HAAAAULpzBu09e/bo/fff15EjR9SwYUMNHTpUDRs29FRtAAAAgNcqNWhv27ZNQ4YMUUFBgXvZp59+qoULF+rSSy/1SHEAAACAtyp1jPYrr7yi/Px8maap8PBwmaaprKwsvfnmm56sDwAAAPBKpQbt7du3yzAMvfTSS0pOTtZTTz0l0zSVnJzsyfoAAAAAr1Rq0M7JyVH16tV18803S5L+9Kc/KSgoSOnp6R4rDgAAAPBWpQbt4uJiBQcHu58bhqHQ0FAVFhZ6pDAAAADAm5UatE3TlMPhKLHM4XDINE3biwIAAAC83Tmn98vMzCxx18fMzExJOuNOkIZh6OWXX7ahPAAAAMA7nTNo5+fna9WqVe7np89m/36ZYRg2lQcAAAB4p1KDdvv27T1ZBwAAAOBTSg3a8+bN82QdAAAAgE8p9WJIAAAAAOVH0AYAAABsQNAGAAAAbEDQBgAAAGxA0AYAAABscM55tAEAlcdZXKiIiNBzbpNf6FRWRoGHKqpYvtyfld4k7+0PgDUEbQCoogIdAbpt4YhzbvPRoNeUJe8Mar7cn5XeJO/tD4A1DB0BAAAAbEDQBgAAAGxA0AYAAABsQNAGAAAAbEDQBgAAAGxA0AYAAABswPR+FcCX54KVfLs/X5/r1pffOwCVx9e/W3y9P3gOQbsC+PJcsJJv9+frc9368nsHoPL4+neLr/cHz2HoCAAAAGADgjYAAABgA4I2AAAAYAOCNgAAAGADgjYAAABgA4I2AAAAYAOCNgAAAGAD5tEG4LW4qQQAlJ2vf3dWpf4I2gC8FjeVAICy8/XvzqrUH0NHAAAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAG1RK0M7OzlafPn106NAhSVJycrL69u2rnj17atq0aZVREgAAAFChPB60//vf/+rPf/6z9u3bJ0nKz8/XxIkT9eqrr2rFihXavn271q1b5+myAAAAgArl8aD90Ucf6YknnlBkZKQkadu2bWrcuLEaNmwof39/9e3bVytXrvR0WQAAAECF8vf0AZ999tkSz1NTUxUREeF+HhkZqZSUlDLts06dkAqpzW4REaGVXYKt6M97+XJvEv15O/rzXr7cm0R/3s4T/Xk8aP+ey+WSYRju56ZplnhuxfHj2XK5zDK9pjJ+edLSsjx2LPqreL7cny/3JtFfRaK/iufL/flybxL9VSRv6M/Pzyjzyd1Kn3Wkfv36SktLcz9PS0tzDysBAAAAvFWlB+2WLVtq79692r9/v4qLi7V8+XJ17dq1sssCAAAAzkulDx0JCgrSlClTNGbMGBUUFCg2Nla9e/eu7LIAAACA81JpQfurr75yP46JidGyZcsqqxQAAACgwlX60BEAAADAFxG0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbELQBAAAAGxC0AQAAABsQtAEAAAAbVJmg/emnnyouLk49e/bU/PnzK7scAAAA4Lz4V3YBkpSSkqJp06YpMTFRgYGBGjx4sDp27KhmzZpVdmkAAABAuVSJoJ2cnKxOnTopLCxMktSrVy+tXLlSo0ePtvR6Pz+jXMeNDK/+h9v414qwtK+IGrX/cJvy1lle9GetPyu9Sb7dX1XsTfLt/vjsneLL/fHdUjV7k3y7Pz57p9jRX3l+HoZpmmaZX1XBZs+erdzcXCUkJEiSFi1apG3btunpp5+u5MoAAACA8qkSY7RdLpcM43//SjBNs8RzAAAAwNtUiaBdv359paWluZ+npaUpMjKyEisCAAAAzk+VCNrXXnutNmzYoBMnTigvL0+rVq1S165dK7ssAAAAoNyqxMWQ9erVU0JCgoYMGaLCwkINHDhQ11xzTWWXBQAAAJRblbgYEgAAAPA1VWLoCAAAAOBrCNoAAACADQjaAAAAgA0I2gAAAIANCNoAAACADS64oJ2YmKjx48dXdhkV4tChQ7rqqqvUr1+/En+OHj161u1nzJihGTNmeLjKinfo0CFFR0fr8ccfL7F8x44dio6OVmJi4nntf/z48ee9Dzvs3r1b0dHR+vzzz8v82n79+kmqur8Ddr+nlc2XvnfO5Y/6rKqfrd86n89Zed11113lfu3KlSsVHx+vW265RX379tVbb71Vrv2sWbNG77zzTrnrOO3QoUPq3r37ee/HipycHP3973/XjTfeqFtuuUW33367NmzYUOr2WVlZGjVq1B/uNzo6uiLLPKfT331JSUkllnfv3l2HDh3yWB0bN248r9/D0vw+p/Tq1UsTJkzQsWPHKvxY52JXf1ZUiXm0UX6RkZFaunRpZZfhcWFhYfr6669VXFwsh8MhSVqxYoVq165dyZXZZ/Hixerdu7cWLlyoXr16lem13vA7ciG+p6h6zudzVl6bNm0q1+tSUlL0wgsvKDExUeHh4crJydFdd92lSy+9VDfccEOZ9rV9+/Zy1VBZTNPU/fffrxYtWuhf//qXAgMD9eOPP+ree+/VSy+9pI4dO57xmszMTO3YsaMSqj23gIAATZ48WcuWLVNISEhll1PhfptTTNPUP//5T40dO1YffPBBJVfmGRds0N60aZOmTZum/Px8nTx5UhMmTFCPHj00fvx4hYSE6IcfflBKSopGjRqlAQMGuM8CjhkzRtKpf22+9957CgsL08SJE5WSkqLU1FTFxPxfe3ceF1XVP3D8M7IkSBG5kAioaaIiIm4gm4LUC3EpJJE0UiNbUH+mhJGJ4QNqSqjkWumTgkuWLAJaIKYiuYGZqKSWCZqWIIq8AIdt5vfHvOY+DAwoKuFy3n/p3HOHc+6de8/3nvu95w5h4cKFHDt2jMjISBQKBd26deP48eNs2LCBrl27Ul5ezogRI0hLS+Opp5564G27fv068+fP559//kEmkxEUFISjoyMAOTk5jBs3jvLycnx9fZk0aRJHjx6V6vriiy9ibm7+0Le1TZs29OzZk6ysLBwcHAD4+eefpXZu3ryZnTt3cvv2bfT09IiKiuKFF17A3d2dvn378ttvv7F161aSk5PZtm0bOjo6uLm5ERwcDMD+/fvZunUrRUVFvPfee4wfP/6B1f1eVFVVkZyczJYtW/Dz8+PSpUtYWlri7u6Op6cnhw4dAmDRokX07t0bf39/jI2N+f3331mxYgWvvvoq586da9E23Mm97NNr164RHR3Nt99+C6hGVE+ePMmCBQtarB2N8ff3Z/r06djb2/PXX3/x5ptv8tNPPzV43ikrK+M///kPv//+OzU1NUydOpVRo0a1dDPuqKF2qq1YsQKlUsmsWbMA1Ui3q6srXl5eLVVloPHjLCYmBnNzc44ePcqqVauIjY3l/PnzhISEUFNTw8CBA8nIyGDPnj2EhIQwePBgxo4dC6hGSM+dO8fhw4eJjIwEwNjYmKioKNasWQPAuHHj+P7775tU35s3b1JVVYVcLgdUx9Bnn33GU089RU5ODosXL0Yul2NiYsKCBQuwsLDA39+fnj17kp2dTUVFBXPnzuX555+XjiEzMzM8PT21/u7i4+PZv38/xcXFFBQU4Ofnx5UrVzhy5AjPPvusNJpeUVHBzJkzuXjxIpaWlixcuBBjY+NG61T7fNWrV687tv3YsWNcvXqVmJgYZDIZAL179+b9999nzZo1PPPMM8yfPx+5XI6xsTGff/45ERERFBQUMG3aNFavXk1cXBzffPMNMpkMa2trQkNDadOmDQChoaHk5ORgYmLCokWLMDMzIz8/n7CwMIqLi2ndujWhoaH07t2bkJAQiouLyc/PJzg4uMkj+h06dMDR0ZElS5YQHh6usWzdunUkJSWho6ODk5MTwcHBLF26FFNTU9566y1A1VePGTMGOzs7rX3/ypUruXr1Knl5edy4cYP333+fw4cPc/LkSXr27Mny5cul31NAQAAFBQX07duXTz/9FH19fTIyMvjiiy+orq7G3Nyc8PBwTExM6vWnbdu2vWNbZTIZM2bMwMnJibNnz5KRkcEPP/xATU0Nzs7OBAcHI5PJ2LhxY72+uaHY5mFqn0lhnroAABeCSURBVDZPXOqI2ubNm4mIiCAhIYGIiAiio6OlZf/88w9bt25l7dq1LF26tNHv2b9/P7169WL79u2kpqaSlZXFmTNnAMjLy2PTpk1ERkby6quvkpSUBEBaWhrDhg17IIFnQUGBRtrI+vXrWbhwIT4+PsTHx7N27Vrmz59PaWkpAIWFhWzatInt27ezZcsW6epeXdclS5Y8tG2ta8SIEdLt3ZycHKysrNDT06O0tJT09HRiY2NJSUlh2LBhbNmyRVrP1dWV1NRUrly5wtatW9mxYwdJSUmcOXNGGtWprKzk+++/58svv5QO0pZ04MABzMzM6Nq1Kx4eHmzfvl1aZmhoSGJiIv/3f//HRx99JH2uvv19N53Ww6Kp+9TBwYHCwkIuXboEQGJiohTcPGq0nXfWrl2LtbU18fHxbNmyhXXr1nH58uUWrun98/HxITk5GaVSye3btzly5EiTR2CbQ2PHmTYhISHMnDmTnTt3YmFhQU1NTaPl16xZQ1hYGPHx8Tg6OpKbm8u8efMAmhxkA/Ts2ZPhw4fj4eHBa6+9Jg14dOzYkXnz5hEVFUVCQgJTpkwhNDRUWq+0tJSEhASioqIICQnB0tISPz8//Pz88PHxafR3d+rUKdasWcOGDRtYvHgxrq6uJCcnA3Dw4EEAioqK8Pf3JykpCQsLC1avXk1lZWWjdWrq+erUqVP06dNHCrLVBg0axKlTp/jwww8JDAwkOTkZLy8vNm3axLx58+jQoQOrV6/m3LlzrFu3jtjYWJKTkzEwMGDVqlUa37Nz505eeuklFi5cCMBHH31EcHAwCQkJhIeHSxeKoLoj98MPP9xz2kxISAiZmZkaKSQZGRn89NNPxMXFkZCQQH5+Pt9++y2vvPIKKSkpgGpfnjhxgqFDhzba958/f57Y2FjCw8P5+OOPmTp1KikpKeTm5kqDMH/99Zc0sl5WVsa2bdu4ceMGUVFRbNiwgcTERJydnfn888+lOqr706YEofr6+nTu3JmzZ89y+vRpduzYQWJiIteuXSMpKYmcnBytffOj0r66ntgR7cjISPbt28ePP/7IyZMnKSsrk5Y5OTkhk8no0aMHxcXFjX7PqFGjyMnJYePGjfz5558UFxdTXl4OQNeuXXn66acBGDt2LFOmTGHmzJkkJCQwe/bsB9IObakj9vb2/Pnnn3zxxRcAVFdXSydJLy8vDA0NAXBzc+PYsWP07NlTo64Pa1vrcnd3Z8WKFSgUCn744QdGjBjB7t27MTIyIioqil27dpGXl8fBgwc1Tt62trYAZGVl4ebmJtV748aNUpnhw4cjk8l48cUXuXnzZrPUvyni4uKkkUwvLy8+/PBDZs6cCYCvry+g2h4hISHcuHEDgL59+7ZMZe9DU/epTCbD29ubpKQkxo4dS1FRkbR/HzXazjuHDh1CLpcTFxcHQHl5Ob///jsWFhYtWdX7ZmFhQadOncjKyuLq1asMHTq0WS7Gm6qx46yu4uJirly5wtChQwHVxUNMTEyj3z98+HCmT5+Oh4cHw4cPx8nJ6b7rvGDBAgIDA8nMzCQzMxNfX1/eeecdLl++zPvvvy+VUwck8L9zRq9evWjfvn29u10N/e4A+vfvj5GRkZTiMGTIEAA6depESUkJoOoPBg4cCKieDwkJCSEvL6/ROjX1fCWTybRe2FRVVaFQKCgsLMTNzQ2ACRMmAGjkPKvP/yYmJgCMHz+ejz/+GIDWrVszZswYqf4rVqygrKyM06dPS2XU20XdP9zv+dbIyIjw8HApEAQ4cuQII0eOxMDAAFD9xhITE5k4cSKVlZXk5+dz4sQJ3N3d0dfX59ChQw32/U5OTujq6mJmZkb79u3p3r07AKampty6dQuAgQMH0qVLFwBGjx5NfHw8lpaW/P3337z55psAKBQKjI2NpXrf6/lWJpMRExPDjRs3pMERuVyOmZkZ169f19o3P0rtq+2JCLSzs7OxsLDA1NQUpVKJjo4OEyZMwN7eHnt7e4YMGcKHH34olVef8GtfKctkMhQKhfT/qqoqAGJjY0lNTcXX1xdHR0fOnz+P+q32rVu3lsqbm5tjZmZGWlpaswcDCoWCTZs28eyzzwKqUe+2bduSnp6Orq6uRjn1/2vX9VFpqzrV4Pjx4xw5coSgoCB2797N33//zfjx43njjTdwdXWlXbt2Gnl56v2rq6ursY+vXbsmndDUOcJ1R0taQlFREQcPHuTMmTPExMSgVCopKSlhz549APX2qbrutffJo+Je9qm3tzdvv/02+vr60kOfDwNt5x1AOmaqq6s1yms77ygUCiIjI7G2tgZUaWG1O4GHQVPbqebj40NKSgpXr16V0tRa0p2Os7rt0dHRkT6rSyaTScvU50+AyZMn4+bmxr59+4iMjCQnJ0cj8Gyq/fv3U15ejpeXFz4+Pvj4+PDdd9+RnJyMubm5NAhTU1Oj8fCZeh+BZj9Q+zNtv7vk5GT09PQ0ytZdt+5nSqUSXV1dFApFo3Vq6vnK1taW2NhYqqqqNOr066+/YmNjw/nz56XPKioqKCgoqHds1aZUKqV926pVK43P1fXX19fXGNj6559/pH72QZxvnZ2dpRQSbXWE//3+xowZw+7duzlx4gTvvPOOVL6hvr/2NtK2z+p+rm53TU0N/fv3Z926dYBqW9YemLyXC+TKykouXryIvb09o0ePZsqUKQCUlJSgo6PDjh07tPbNj0r76noiUkfi4uJIT08H4Ny5c1hYWJCXl8fMmTNxdXVl7969d7zlZ2Jiwh9//AGobmkXFhYCqhzS8ePHM2bMGCoqKjh79qzWgwNUHUtERIR0pdxcHBwcpIcM/vjjD0aPHs3t27cBSE1NpbKyklu3brF//34pF7a2R6mtI0aMICoqij59+kgHkaGhIZ07d2by5MnY2NiQnp6udf8OHDiQAwcOUFZWRnV1NUFBQQ/lA0E7d+7EwcFBuo24b98+3nvvPSmncteuXQDs2bOHbt26PXSBWFM1dZ926tRJyjF9mAJtbeed2seWelljHBwc2LZtG6DqVMaMGdPgrEIt5V7b6enpyeHDh7l+/fpDcReiseOsdnv27t0LwNNPP42FhQUHDhwAkNInQJVGoK3948aNo6ysjMmTJzN58mRyc3MBVeDb0AVJY1q3bk1UVJQ0UqtUKvntt9/o168ft27dIjs7G1Dto9qDSbt37wZU6RclJSX06NFDow73+7u7cOGC1La4uDgcHR154YUXGq1TUw0cOJDu3buzaNEi6WLm9OnTrF27lunTp2NqakpmZiag2rfR0dHo6upKbRw8eDA//fSTdPfou+++kx6gLC8vl/azuv5PP/00Xbp0kQLtn3/+mYkTJ95z/RuiTiEpKCjAwcGBXbt2IZfLqa6uJi4uTuqzR48eze7du8nPz2fAgAFA433/3Th+/DhXr15FoVCQmJiIo6Mjtra2/Prrr1y8eBFQpT/dKaW2MQqFgpUrV2Jra4uPjw87d+6U+uBp06aRmpraYN/8KLRPmydiRPudd95hzpw5bN68meeff54VK1Zw8+ZNRo4cia6uLg4ODsjlcikNQhsvLy9SU1Px8vLC2tqa3r17AzBp0iTCwsL46quvMDIyws7Ojr/++gtLS8t63/Hyyy8TGhra7MHAvHnzmD9/PqNHjwZg6dKl0m0+MzMz/Pz8qKio4N1336Vbt271ptl5lNrq5ubGJ598onF7V09PD4VCgZeXF0qlkkGDBkm3PWuztrbmjTfewM/PD4VCwUsvvYSjo6N02+5hkZCQoJELCDBx4kTWr1+PkZERv/zyCzt27MDAwIDPPvushWr54NzLPvXy8iItLQ1TU9OWqLJW2s47+fn5hISEEBcXd1c5ydOnTycsLIxRo0ZRU1NDcHCw1uOtJd1rO1u3bk2/fv3o0aPHv1xj7Ro7zubMmcPChQtZtWoVzs7O0vKlS5cyd+5cVqxYgZWVlTSq+frrr/PBBx8wevRoHBwcaN++PQCzZ88mJCQEXV1dDA0NiYiIAFQpJa+88grx8fFNGkFzcHBg+vTpvPfee1Kw6eLiwowZM3B3d2fhwoVUVFRgZGSk8fzN5cuX8fb2BmD58uXo6OgwaNAgPvroI9q1a9fg704dJN+JpaUlq1ev5tKlS/To0YNZs2ahr69PdHR0g3W6F6tWrWL58uWMGjUKHR0djI2NiYyMxN7ensjISMLCwoiMjMTExISlS5diYmKCmZkZ/v7+xMbG8u677+Lv709VVRXW1tbSQ9TPPPMM6enpREdHY2pqyuLFiwGk71y/fj16enosX778gd/1VKeQBAQEMGzYMEpKSvDx8aG6uhpnZ2feeOMNADp27IiJiQl2dnZSHRrr++9G9+7dmTt3LoWFhTg4OPDaa6+ho6PDokWL+OCDD1AoFJiamkoP9N4t9bNkoAq0e/XqxbJlyzA2Nubs2bP4+vpSU1ODi4sL3t7eyGQyrX1zt27dHsr23YlM2dC9L+GBUiqVZGRksG3bNukWxePqSWprS6s9G8KTqrq6mjlz5uDp6cnLL7/c0tUR7oJSqaSsrIzx48ezceNGKRB91KxatQpfX186dOhAWloaycnJD+U89bXVnhFGEITm90SMaD8MFi1axL59+/j6669buirN7klqq9CylEolLi4uODo64uHh0dLVEe7SqVOnePvtt5k2bdojG2SD6g7hW2+9ha6uLs8884w0O4UgCIKaGNEWBEEQBEEQhGbwRDwMKQiCIAiCIAj/NhFoC4IgCIIgCEIzEIG2IAjCE6ShKTmfRGJbCILQ3ESgLQjCI8/f3x8rKysGDBjAtWvXNJYdPXoUKysrrKysNN4M97hITEzE09OTPn36YG9vL701ra6amhq2bdtW702t6m2zefPmZquj+m9YWVnh6Oio8aIXpVKJo6OjRpnmlpeXR2BgoMZ0dStXrsTKykrMxiEIwgMlAm1BEB4bpaWlT9TMDyUlJcydO1d62YKOjk6D8zCHhoYSFhZGUVHRv1nFeoqKijh79qz0/3Pnzv2rdbp06RKjRo1i7969Db7ZURAE4UERgbYgCI+V1NRU9u3b19LV+FcUFBRIb8iMjo7m0KFDvPvuu1rLlpaW/ptV00r9mmT1G/tA9Ya92suam1wu13gtuiAIQnMSgbYgCI+d8PDwRt/0CpCVlcWkSZOwt7enT58+uLi48PHHH2u8KdXd3R0rKyvi4uJYtmwZTk5O2NnZMXv2bEpKSkhJScHT0xMbGxu8vb3JysrS+BtnzpwhICAAOzs77OzsmDhxokaQ2ZjDhw8TEBDA4MGDsbW1xdvbm2+//VYahY2Pj2fkyJFS+cDAwAbTY/z9/UlNTQXg2LFjWFlZER8fr1Gmurqa5cuX4+zsjK2tLQEBAeTl5T2w9gDSq9bVwTXAoUOHAOjXr5/WdUpLS1m2bBkvv/wyNjY2ODk5ERwcTH5+vkY59b7asWMHX3/9Ne7u7tjY2ODr68uJEycAVRqR+q1yAG+++Sbu7u71/ubp06eZMGECffv2xc3NjfXr1991GwVBEGoTgbYgCI8Na2trdHV1uXLlSqNv6Ltw4QIBAQEcOXIEuVxOmzZtKCgoID4+npCQkHrlly1bxvr16ykvL6e8vJxdu3bh5+dHUFAQ169fp7KyktzcXAIDA6WR45ycHCZMmEBmZiYKhQIdHR2ys7OZOnWqFPQ25LvvvmPKlClkZmZSVlaGTCYjNzeXTz/9VKqfgYEB7dq1k9YxMTHB1NQUXd367yEzMTGRXg+up6eHqakpBgYGGmXWrl3L119/TXl5OXK5nMzMTIKCgqTl99MeNQcHBwCOHz+OXC6nsrJSypNWL6uttLQUX19fvvzyS/Lz89HX1+f69eskJSUxduxYcnNz662zbt06oqKiuHXrFpWVlZw8eZLp06cjl8vR19evt83qvjCnvLwcf39/zp07R2VlJVevXiUyMpIDBw7cVRsFQRBqE4G2IAiPjR49ejBp0iQAYmJi+O2337SWu3jxIra2tjg7O3P06FGOHj3KvHnzAKTRz9qqqqrYvXs32dnZ0sNyFy5cYNasWWRnZxMREQGocqbV+ceRkZHI5XJeffVVsrKyyM7O5pNPPkGhULBkyZIG84Nv3LhBREQESqUSd3d3jh49yi+//MLMmTMB1cOPe/fuZcSIEXzzzTfSetHR0WRkZPD888/X+84vvviCoUOHAmBnZ0dGRgYjRozQKGNoaMiePXvIzs5m4sSJgGpkt7Cw8L7aU1unTp3o1KkTlZWVHDt2TAq4LSwsMDMzq1d+9erVXLhwAX19fTZs2MDx48fZs2cPnTt3prS0lE8++aTeOjdv3iQuLo7s7GwCAwMBuH79OqdPn8bOzq7eNtu+fbvG+pWVlQQEBJCVlUVaWhqGhoYA7N27947tEwRBqEsE2oIgPFZmzJiBubk51dXVhIaGap3CzcPDg9jYWFavXk1ubi4xMTGkp6cDUFZWVq/80KFD6dKlCzo6OlKKQ6tWrZg8eTIA/fv3l8qWlZUhl8s5fvw4APv378fDwwNXV1e++uorAK5cuSI9wFjXvn37qKioAGDBggUYGRnRqlUrAgMD6dKlCwBpaWn3sGUaN2bMGDp16kSrVq2koBxUFw/305661CPXP//8s5RCom00G+DHH38EwNvbG2dnZwAsLS2ZMWMGALm5uVy+fFljnWHDhmFtbY1MJsPT01P6XNt+1UZHR4epU6fSqlUrLC0t6d69O6DaDoIgCE0lAm1BEB4rBgYGhIWFAXDq1Cm2bt1ar0xxcTFBQUEMGjSI119/nf/+97/SA3LaRmZNTEykf6sf2jMyMpLSMWrP9KFQKCgpKZEeUiwuLubatWtcu3ZNGh0G6k1DqKaegcPAwIAOHTpoLOvcuTOAxvc8KG3btpX+rW4XqKYFvJ/21KUOqg8dOiTlZzcUaKvz5S0tLTU+V28HqL8tnnvuOenf6tFouPs5s42MjDT2p3pbiDm3BUG4F/WT+QRBEB5xLi4ujBo1ipSUFK2jv+Hh4aSkpGBjY8PKlSvp2LEjBw8e5O2339b6fTo6OvU+a9Wq4XGK5557Dl1dXaqrq/nss8/w9vYGVGkJMpms0Rk21DnEt2/fprCwUCOH+NKlSwD1AvAHobnaU5c69eb8+fPIZDJAFWhnZGTUK9u+fXuuXLkitVut9v/rbovaOerq769N22dNWS4IgtAUYkRbEITH0ty5c3n22We1LlPnURsYGNC2bVtKS0s1cnXvd/RSV1dXSieJiYmhqKgIpVLJokWL6NevHz4+PlRWVmpd19XVVQoWw8LCKC0tRaFQ8OWXX0rpGXXzq++2TvC/af6aMsXd/bSnLlNTU7p27Qqo7h50795d4wHF2tQzgiQmJkqj35cvX5YedLWxscHc3Pyu2wGaF02lpaViqj9BEJqVCLQFQXgstW3bluDgYK3LBgwYAKimurO3t2fIkCHs2bNHWn7r1q37/vuzZ89GT0+P3NxcXFxcGDRoENu2baO6upqRI0eir6+vdb127dpJ9U5PT8fe3p7+/fuzbNkyAMaNG6eRQ323LCwsAFVe88CBA9myZcu/0h5tar99cciQIQ2WmzZtGpaWllRUVDBlyhQGDBiAh4cHeXl5GBsb39PLiUxNTaW6zpo1i2HDhjX5OwRBEO6WCLQFQXhsvfbaawwePLje53PmzMHX11fKS37xxReJjIyUcrFrz/N8r+zs7IiNjcXFxQVDQ0Oqq6vp3bs3S5Ys4a233mp03cmTJ7NhwwZcXFxo06YNNTU19O7dm4iICGmGk6Z6/fXXGTx4MAYGBujq6tKmTZt/rT111c7Jbig/G1S58fHx8UydOpUuXbpQWVlJ27ZteeWVV4iLi7un17W3adOGoKAgOnbsCKguyKqrq5v8PYIgCHdDphTvoBUEQRAEQRCEB06MaAuCIAiCIAhCMxCBtiAIgiAIgiA0AxFoC4IgCIIgCEIzEIG2IAiCIAiCIDQDEWgLgiAIgiAIQjMQgbYgCIIgCIIgNAMRaAuCIAiCIAhCMxCBtiAIgiAIgiA0g/8H1o9zMUH7lTwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.set(rc={'figure.figsize':(12, 8)})\n",
    "call_percentage.unstack().plot(kind='bar')                                             #making an unstacked graph\n",
    "mpt.xlabel('Name of the Month', fontdict=font)\n",
    "mpt.ylabel('Percentage of Calls', fontdict=font)\n",
    "mpt.xticks(rotation=0)\n",
    "mpt.title('Calls/Month', fontdict=font)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating a pie chart of the same"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "call_percentage = call_percentage.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mpt.figure(figsize=(12,8))\n",
    "mpt.pie(call_percentage,  labels = call_percentage.index, autopct=\"%.2f\")\n",
    "mpt.savefig(\"call percentage pie chart.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing hourly data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "hours_data = data.groupby(['hour', 'call_type'])['call_type'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "hour  call_type\n",
       "0     EMS          5263\n",
       "      Fire         1341\n",
       "      Traffic      2046\n",
       "1     EMS          4711\n",
       "      Fire         1104\n",
       "Name: call_type, dtype: int64"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hours_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculating percentage of hours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "hours_percentage = hours_data.groupby(level=0).apply(lambda x: round(100*x/float(x.sum())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "hour  call_type\n",
       "0     EMS          61.0\n",
       "      Fire         16.0\n",
       "      Traffic      24.0\n",
       "1     EMS          64.0\n",
       "      Fire         15.0\n",
       "Name: call_type, dtype: float64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hours_percentage.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "hours_percentage = hours_percentage.reindex(['EMS', 'Traffic', 'Fire'], level=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating a plot accordingly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.set(rc={'figure.figsize':(18, 8)})\n",
    "hours_percentage.unstack().plot(kind='bar')\n",
    "mpt.xlabel('Hour of the day', fontdict=font)\n",
    "mpt.ylabel('Percentage of Calls', fontdict=font)\n",
    "mpt.xticks(rotation=0)\n",
    "mpt.title('Calls/Hour', fontdict=font)\n",
    "mpt.savefig(\"Percentage of calls vs hours.png\")"
   ]
  },
  {
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}