From fce61d788c6897484e60e0e1b59d5c4b9c0e71e6 Mon Sep 17 00:00:00 2001
From: Vaishnavi Bhushan <96589133+VB-deeksha@users.noreply.github.com>
Date: Sun, 11 Jun 2023 12:58:54 +0530
Subject: [PATCH] Create Covid_19_data

---
 Data Analytics/Covid_19_data | 507 +++++++++++++++++++++++++++++++++++
 1 file changed, 507 insertions(+)
 create mode 100644 Data Analytics/Covid_19_data

diff --git a/Data Analytics/Covid_19_data b/Data Analytics/Covid_19_data
new file mode 100644
index 00000000..9cc4697d
--- /dev/null
+++ b/Data Analytics/Covid_19_data	
@@ -0,0 +1,507 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "cc9cd027",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "2b0336a0",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "data = pd.read_csv(r\"C:\\Users\\vaish\\OneDrive\\Documents\\Kaggle Datasets\\covid_19_dataset.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "1457edd1",
+   "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>SNo</th>\n",
+       "      <th>ObservationDate</th>\n",
+       "      <th>Province/State</th>\n",
+       "      <th>Country/Region</th>\n",
+       "      <th>Last Update Time</th>\n",
+       "      <th>Confirmed</th>\n",
+       "      <th>Deaths</th>\n",
+       "      <th>Recovered</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>22-01-2020</td>\n",
+       "      <td>Anhui</td>\n",
+       "      <td>Mainland China</td>\n",
+       "      <td>22-01-2020 17:00</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>22-01-2020</td>\n",
+       "      <td>Beijing</td>\n",
+       "      <td>Mainland China</td>\n",
+       "      <td>22-01-2020 17:00</td>\n",
+       "      <td>14</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>22-01-2020</td>\n",
+       "      <td>Fujian</td>\n",
+       "      <td>Mainland China</td>\n",
+       "      <td>22-01-2020 17:00</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>22-01-2020</td>\n",
+       "      <td>Gansu</td>\n",
+       "      <td>Mainland China</td>\n",
+       "      <td>22-01-2020 17:00</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>22-01-2020</td>\n",
+       "      <td>Guangdong</td>\n",
+       "      <td>Mainland China</td>\n",
+       "      <td>22-01-2020 17:00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   SNo ObservationDate Province/State  Country/Region  Last Update Time  \\\n",
+       "0    1      22-01-2020          Anhui  Mainland China  22-01-2020 17:00   \n",
+       "1    2      22-01-2020        Beijing  Mainland China  22-01-2020 17:00   \n",
+       "2    3      22-01-2020         Fujian  Mainland China  22-01-2020 17:00   \n",
+       "3    4      22-01-2020          Gansu  Mainland China  22-01-2020 17:00   \n",
+       "4    5      22-01-2020      Guangdong  Mainland China  22-01-2020 17:00   \n",
+       "\n",
+       "   Confirmed  Deaths  Recovered  \n",
+       "0          1       0          0  \n",
+       "1         14       0          0  \n",
+       "2          6       0          0  \n",
+       "3          1       0          0  \n",
+       "4          0       0          0  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "030a514e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['SNo', 'ObservationDate', 'Province/State', 'Country/Region',\n",
+       "       'Last Update Time', 'Confirmed', 'Deaths', 'Recovered'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "31928232",
+   "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>SNo</th>\n",
+       "      <th>Confirmed</th>\n",
+       "      <th>Deaths</th>\n",
+       "      <th>Recovered</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>50.00000</td>\n",
+       "      <td>50.000000</td>\n",
+       "      <td>50.000000</td>\n",
+       "      <td>50.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>25.50000</td>\n",
+       "      <td>28.240000</td>\n",
+       "      <td>0.820000</td>\n",
+       "      <td>1.280000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>14.57738</td>\n",
+       "      <td>97.839218</td>\n",
+       "      <td>4.119094</td>\n",
+       "      <td>5.838087</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>1.00000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>13.25000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>25.50000</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>37.75000</td>\n",
+       "      <td>14.750000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>50.00000</td>\n",
+       "      <td>549.000000</td>\n",
+       "      <td>24.000000</td>\n",
+       "      <td>31.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            SNo   Confirmed     Deaths  Recovered\n",
+       "count  50.00000   50.000000  50.000000  50.000000\n",
+       "mean   25.50000   28.240000   0.820000   1.280000\n",
+       "std    14.57738   97.839218   4.119094   5.838087\n",
+       "min     1.00000    0.000000   0.000000   0.000000\n",
+       "25%    13.25000    1.000000   0.000000   0.000000\n",
+       "50%    25.50000    4.000000   0.000000   0.000000\n",
+       "75%    37.75000   14.750000   0.000000   0.000000\n",
+       "max    50.00000  549.000000  24.000000  31.000000"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.describe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f4fa263f",
+   "metadata": {},
+   "source": [
+    "# Relating the variables with scatterplots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "5086bca7",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.FacetGrid at 0x2db17eb2ca0>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 500x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    " sns.relplot(x=\"Confirmed\",y=\"Recovered\",data=data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "4e0ed268",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.PairGrid at 0x2db1db56e20>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sns.pairplot(data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "029d6489",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['SNo', 'ObservationDate', 'Province/State', 'Country/Region',\n",
+       "       'Last Update Time', 'Confirmed', 'Deaths', 'Recovered'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.columns"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ce72238f",
+   "metadata": {},
+   "source": [
+    "## LINE PLOT"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "ce7088b8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x1000 with 20 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot([1,3,2,4,1])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2481f82f",
+   "metadata": {},
+   "source": [
+    "## SCATTER PLOT"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "72885863",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(x=data['Confirmed'], y=data['Recovered'])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "b12213fc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(x=data['Confirmed'], y=data['Deaths'])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "7fe96039",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(x=data['Deaths'], y=data['Confirmed'])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f7687d08",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}