9-25 SNS3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "\n",
    "df = pd.read_csv('911.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 663522 entries, 0 to 663521\n",
      "Data columns (total 9 columns):\n",
      " #   Column     Non-Null Count   Dtype  \n",
      "---  ------     --------------   -----  \n",
      " 0   lat        663522 non-null  float64\n",
      " 1   lng        663522 non-null  float64\n",
      " 2   desc       663522 non-null  object \n",
      " 3   zip        583323 non-null  float64\n",
      " 4   title      663522 non-null  object \n",
      " 5   timeStamp  663522 non-null  object \n",
      " 6   twp        663229 non-null  object \n",
      " 7   addr       663522 non-null  object \n",
      " 8   e          663522 non-null  int64  \n",
      "dtypes: float64(3), int64(1), object(5)\n",
      "memory usage: 45.6+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>zip</th>\n",
       "      <th>e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>663522.000000</td>\n",
       "      <td>663522.000000</td>\n",
       "      <td>583323.000000</td>\n",
       "      <td>663522.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>40.158162</td>\n",
       "      <td>-75.300105</td>\n",
       "      <td>19236.055791</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.220641</td>\n",
       "      <td>1.672884</td>\n",
       "      <td>298.222637</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-119.698206</td>\n",
       "      <td>1104.000000</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>40.100344</td>\n",
       "      <td>-75.392735</td>\n",
       "      <td>19038.000000</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>40.143927</td>\n",
       "      <td>-75.305143</td>\n",
       "      <td>19401.000000</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>40.229008</td>\n",
       "      <td>-75.211865</td>\n",
       "      <td>19446.000000</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>51.335390</td>\n",
       "      <td>87.854975</td>\n",
       "      <td>77316.000000</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 lat            lng            zip         e\n",
       "count  663522.000000  663522.000000  583323.000000  663522.0\n",
       "mean       40.158162     -75.300105   19236.055791       1.0\n",
       "std         0.220641       1.672884     298.222637       0.0\n",
       "min         0.000000    -119.698206    1104.000000       1.0\n",
       "25%        40.100344     -75.392735   19038.000000       1.0\n",
       "50%        40.143927     -75.305143   19401.000000       1.0\n",
       "75%        40.229008     -75.211865   19446.000000       1.0\n",
       "max        51.335390      87.854975   77316.000000       1.0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "205"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['zip'].unique().size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19401.0    45606\n",
       "19464.0    43910\n",
       "19403.0    34888\n",
       "19446.0    32270\n",
       "19406.0    22464\n",
       "Name: zip, dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['zip'].value_counts().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LOWER MERION    55490\n",
       "ABINGTON        39947\n",
       "NORRISTOWN      37633\n",
       "UPPER MERION    36010\n",
       "CHELTENHAM      30574\n",
       "Name: twp, dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['twp'].value_counts().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['twp'].value_counts().head().plot.line()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['twp'].value_counts().head().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "68"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['twp'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Traffic: VEHICLE ACCIDENT -    148372\n",
       "Traffic: DISABLED VEHICLE -     47909\n",
       "Fire: FIRE ALARM                38336\n",
       "EMS: FALL VICTIM                34676\n",
       "EMS: RESPIRATORY EMERGENCY      34248\n",
       "Name: title, dtype: int64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['title'].value_counts().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['title'].value_counts().head().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Reason'] = df['title'].apply(lambda title: title.split()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0             EMS:\n",
       "1             EMS:\n",
       "2            Fire:\n",
       "3             EMS:\n",
       "4             EMS:\n",
       "            ...   \n",
       "663517    Traffic:\n",
       "663518        EMS:\n",
       "663519        EMS:\n",
       "663520       Fire:\n",
       "663521    Traffic:\n",
       "Name: Reason, Length: 663522, dtype: object"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Reason']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EMS:        332692\n",
       "Traffic:    230208\n",
       "Fire:       100622\n",
       "Name: Reason, dtype: int64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Reason'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['timeStamp_dt'] = pd.to_datetime(df['timeStamp'])\n",
    "df['Year'] = pd.DatetimeIndex(df['timeStamp']).year\n",
    "df['Month'] = pd.DatetimeIndex(df['timeStamp']).month\n",
    "df['Time'] = pd.DatetimeIndex(df['timeStamp']).time\n",
    "df['dayOfWeek'] = pd.DatetimeIndex(df['timeStamp']).dayofweek\n",
    "df['date'] = pd.DatetimeIndex(df['timeStamp']).date\n",
    "df['DayOfWeek'] = df['dayOfWeek'].map({0:'Mon',1:'Tue',2:'Wen',3:'Thur',4:'Fri',5:'Sat',6:'Sun'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='DayOfWeek', ylabel='count'>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='DayOfWeek', data=df, hue='Reason')\n",
    "#1. Max calls for what day?\n",
    "#A: Friday"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Month', ylabel='count'>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='Month', data=df)\n",
    "#2. Max calls in which 3 months\n",
    "#A: Jan Feb June\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Year', ylabel='count'>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='Year', data=df)\n",
    "#3. Max calls in which year\n",
    "#A: 2018"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.12 ('base')",
   "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": "3.9.12"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "f6ed3f38b1ef4c16f8a5be48bf66a1aded4ea0eb199bbc31dab9e5edd4e77510"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}