covid_data_analysis.ipynb

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  "metadata": {
    "colab": {
      "name": "covid data analysis.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qJSTuv7DFEP4"
      },
      "source": [
        "COVID DATA ANALYSIS\n",
        "\n",
        "shaili patel"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f6ULdbgROCWS"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4oLeN3EIOhym"
      },
      "source": [
        "confirm_data=pd.read_csv('/content/drive/My Drive/Data Science project/covid data analysis/covid19_Confirmed_dataset.csv')\n",
        "death_data=pd.read_csv('/content/drive/My Drive/Data Science project/covid data analysis/covid19_deaths_dataset.csv')\n",
        "happiness_report=pd.read_csv('/content/drive/My Drive/Data Science project/covid data analysis/worldwide_happiness_report.csv')"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WgxH6EA_PNAZ",
        "outputId": "b281115a-9892-4732-d4ab-f57e8484827b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "print(\"we are given {} days of data for confirmed cases\".format(len(confirm_data.columns[4:])))\n",
        "print(\"we are given {} days of data for death cases\".format(len(death_data.columns[4:])))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "we are given 100 days of data for confirmed cases\n",
            "we are given 100 days of data for death cases\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q5oU5AOPPaYt"
      },
      "source": [
        "#check for null values\n",
        "confirm_data.isnull().any()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uFB43rmaRCRH"
      },
      "source": [
        "confirm_data[confirm_data['Province/State'].isnull()==True].head(3) #it means that for data cleaning we can remove Province/State feature."
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2nIANTJeRc1I"
      },
      "source": [
        "confirm_data.describe()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9R7rrRM5SVn4"
      },
      "source": [
        "#the best thing to do right now is to group the data but first we will remove uneseccary features\n",
        "confirm_data.drop(columns=['Province/State','Lat','Long'],axis=1,inplace=True)"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vLukTO1aUIWv"
      },
      "source": [
        "#we cn now use groupby function to roup the data country or region wise\n",
        "confirm_agg=confirm_data.groupby('Country/Region').sum()"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t6JBqSF8wNWG",
        "outputId": "327c2179-6c52-478e-eeef-a0d474c47401",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 224
        }
      },
      "source": [
        "confirm_agg.head(3)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <th>4/16/20</th>\n",
              "      <th>4/17/20</th>\n",
              "      <th>4/18/20</th>\n",
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              "      <th>4/21/20</th>\n",
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              "      <th>4/28/20</th>\n",
              "      <th>4/29/20</th>\n",
              "      <th>4/30/20</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country/Region</th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>40</td>\n",
              "      <td>40</td>\n",
              "      <td>74</td>\n",
              "      <td>84</td>\n",
              "      <td>94</td>\n",
              "      <td>110</td>\n",
              "      <td>110</td>\n",
              "      <td>120</td>\n",
              "      <td>170</td>\n",
              "      <td>174</td>\n",
              "      <td>237</td>\n",
              "      <td>273</td>\n",
              "      <td>281</td>\n",
              "      <td>299</td>\n",
              "      <td>349</td>\n",
              "      <td>367</td>\n",
              "      <td>423</td>\n",
              "      <td>444</td>\n",
              "      <td>484</td>\n",
              "      <td>521</td>\n",
              "      <td>555</td>\n",
              "      <td>607</td>\n",
              "      <td>665</td>\n",
              "      <td>714</td>\n",
              "      <td>784</td>\n",
              "      <td>840</td>\n",
              "      <td>906</td>\n",
              "      <td>933</td>\n",
              "      <td>996</td>\n",
              "      <td>1026</td>\n",
              "      <td>1092</td>\n",
              "      <td>1176</td>\n",
              "      <td>1279</td>\n",
              "      <td>1351</td>\n",
              "      <td>1463</td>\n",
              "      <td>1531</td>\n",
              "      <td>1703</td>\n",
              "      <td>1828</td>\n",
              "      <td>1939</td>\n",
              "      <td>2171</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Albania</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>89</td>\n",
              "      <td>104</td>\n",
              "      <td>123</td>\n",
              "      <td>146</td>\n",
              "      <td>174</td>\n",
              "      <td>186</td>\n",
              "      <td>197</td>\n",
              "      <td>212</td>\n",
              "      <td>223</td>\n",
              "      <td>243</td>\n",
              "      <td>259</td>\n",
              "      <td>277</td>\n",
              "      <td>304</td>\n",
              "      <td>333</td>\n",
              "      <td>361</td>\n",
              "      <td>377</td>\n",
              "      <td>383</td>\n",
              "      <td>400</td>\n",
              "      <td>409</td>\n",
              "      <td>416</td>\n",
              "      <td>433</td>\n",
              "      <td>446</td>\n",
              "      <td>467</td>\n",
              "      <td>475</td>\n",
              "      <td>494</td>\n",
              "      <td>518</td>\n",
              "      <td>539</td>\n",
              "      <td>548</td>\n",
              "      <td>562</td>\n",
              "      <td>584</td>\n",
              "      <td>609</td>\n",
              "      <td>634</td>\n",
              "      <td>663</td>\n",
              "      <td>678</td>\n",
              "      <td>712</td>\n",
              "      <td>726</td>\n",
              "      <td>736</td>\n",
              "      <td>750</td>\n",
              "      <td>766</td>\n",
              "      <td>773</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Algeria</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>201</td>\n",
              "      <td>230</td>\n",
              "      <td>264</td>\n",
              "      <td>302</td>\n",
              "      <td>367</td>\n",
              "      <td>409</td>\n",
              "      <td>454</td>\n",
              "      <td>511</td>\n",
              "      <td>584</td>\n",
              "      <td>716</td>\n",
              "      <td>847</td>\n",
              "      <td>986</td>\n",
              "      <td>1171</td>\n",
              "      <td>1251</td>\n",
              "      <td>1320</td>\n",
              "      <td>1423</td>\n",
              "      <td>1468</td>\n",
              "      <td>1572</td>\n",
              "      <td>1666</td>\n",
              "      <td>1761</td>\n",
              "      <td>1825</td>\n",
              "      <td>1914</td>\n",
              "      <td>1983</td>\n",
              "      <td>2070</td>\n",
              "      <td>2160</td>\n",
              "      <td>2268</td>\n",
              "      <td>2418</td>\n",
              "      <td>2534</td>\n",
              "      <td>2629</td>\n",
              "      <td>2718</td>\n",
              "      <td>2811</td>\n",
              "      <td>2910</td>\n",
              "      <td>3007</td>\n",
              "      <td>3127</td>\n",
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              "      <td>3649</td>\n",
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              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3 rows × 100 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                1/22/20  1/23/20  1/24/20  ...  4/28/20  4/29/20  4/30/20\n",
              "Country/Region                             ...                           \n",
              "Afghanistan           0        0        0  ...     1828     1939     2171\n",
              "Albania               0        0        0  ...      750      766      773\n",
              "Algeria               0        0        0  ...     3649     3848     4006\n",
              "\n",
              "[3 rows x 100 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e8HvgDbEv2k9",
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        }
      },
      "source": [
        "#here we will plot the rise in cases of india with respect to china,russia and UK\n",
        "plt.figure(figsize=(10,4))  #adjusting figure size\n",
        "ax =confirm_agg.loc['India'].plot(color='orange',label='India')\n",
        "confirm_agg.loc['China'].plot(color='red',label='China')\n",
        "confirm_agg.loc['Russia'].plot(color='blue',label='Russia')\n",
        "confirm_agg.loc['United Kingdom'].plot(color='green',label='UK')\n",
        "ax.tick_params(axis='x', colors='white') #colour the axis to adjust the dark theme\n",
        "ax.tick_params(axis='y', colors='white')\n",
        "plt.xlabel('DATE',color='white')    #setting labels\n",
        "plt.ylabel('No.Of Cases',color='white')\n",
        "plt.legend()   \n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "dark"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cLzRrK-D0KXH"
      },
      "source": [
        "The above graph shows how cases started to rise from january onwards.\n",
        "but it doesnot show the peak value to get the rate of promulgation of virus. For example cases in china were increaseing rapidly from january to march and then it became constant or might have decresed . so we need to find the date at which the cases where on the peak. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KIBLmH4zwJx_",
        "outputId": "6d06896d-c028-45e3-e2d8-d9ab629f905e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "source": [
        "#to find the rate of spread of virus we have to take the first derivative of the curve.s = pd.Series([2, 2, 3, 4, 5])\n",
        "s = pd.Series([2, 2, 3, 7, 5,10,9,2,3,1,5,34,56,12,-34,-56,-78,23,56,89,110,-40,-23,9])\n",
        "plt.subplot(121)\n",
        "s.diff().plot(marker='*')\n",
        "plt.subplot(122)\n",
        "s.plot(marker='^')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f502c296f28>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 54
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5g3zAtOc44Fa",
        "outputId": "78a53c2f-d9da-45bf-c8a8-3ef9ef36abca",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        }
      },
      "source": [
        "confirm_agg.loc['India'].diff().plot(color='orange',label='Bharat')\n",
        "confirm_agg.loc['China'].diff().plot(color='darkblue',label='China')\n",
        "x=confirm_agg.loc['China'].diff().max()\n",
        "plt.plot(22,x,'r^')\n",
        "confirm_agg.loc['Russia'].diff().plot(color='deeppink',label='Russia')\n",
        "plt.xticks(color='azure')\n",
        "plt.yticks(color='azure')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "dark"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_owCxENm7KvJ"
      },
      "source": [
        "df=pd.DataFrame(confirm_agg.loc['China']['2/11/20':'2/29/20'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s-6BGsif8CZY"
      },
      "source": [
        "df['diff']=df.diff()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-N8wnN2D8iGv",
        "outputId": "25990ff7-ebe8-4ef3-9173-2096a1948c57",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 445
        }
      },
      "source": [
        "df.style.background_gradient(cmap='Dark2')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "        }    #T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row12_col1 {\n",
              "            background-color:  #1b9e77;\n",
              "            color:  #000000;\n",
              "        }    #T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row13_col0 {\n",
              "            background-color:  #666666;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row13_col1 {\n",
              "            background-color:  #1b9e77;\n",
              "            color:  #000000;\n",
              "        }    #T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row14_col0 {\n",
              "            background-color:  #666666;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row14_col1 {\n",
              "            background-color:  #1b9e77;\n",
              "            color:  #000000;\n",
              "        }    #T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row15_col0 {\n",
              "            background-color:  #666666;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row15_col1 {\n",
              "            background-color:  #1b9e77;\n",
              "            color:  #000000;\n",
              "        }    #T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row16_col0 {\n",
              "            background-color:  #666666;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row16_col1 {\n",
              "            background-color:  #1b9e77;\n",
              "            color:  #000000;\n",
              "        }    #T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row17_col0 {\n",
              "            background-color:  #666666;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row17_col1 {\n",
              "            background-color:  #1b9e77;\n",
              "            color:  #000000;\n",
              "        }    #T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row18_col0 {\n",
              "            background-color:  #666666;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row18_col1 {\n",
              "            background-color:  #1b9e77;\n",
              "            color:  #000000;\n",
              "        }</style><table id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >China</th>        <th class=\"col_heading level0 col1\" >diff</th>    </tr></thead><tbody>\n",
              "                <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >2/11/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row0_col0\" class=\"data row0 col0\" >44386</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row0_col1\" class=\"data row0 col1\" >nan</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >2/12/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row1_col0\" class=\"data row1 col0\" >44759</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row1_col1\" class=\"data row1 col1\" >373.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >2/13/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row2_col0\" class=\"data row2 col0\" >59895</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row2_col1\" class=\"data row2 col1\" >15136.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >2/14/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row3_col0\" class=\"data row3 col0\" >66358</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row3_col1\" class=\"data row3 col1\" >6463.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >2/15/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row4_col0\" class=\"data row4 col0\" >68413</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row4_col1\" class=\"data row4 col1\" >2055.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >2/16/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row5_col0\" class=\"data row5 col0\" >70513</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row5_col1\" class=\"data row5 col1\" >2100.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >2/17/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row6_col0\" class=\"data row6 col0\" >72434</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row6_col1\" class=\"data row6 col1\" >1921.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >2/18/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row7_col0\" class=\"data row7 col0\" >74211</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row7_col1\" class=\"data row7 col1\" >1777.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >2/19/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row8_col0\" class=\"data row8 col0\" >74619</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row8_col1\" class=\"data row8 col1\" >408.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >2/20/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row9_col0\" class=\"data row9 col0\" >75077</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row9_col1\" class=\"data row9 col1\" >458.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row10\" class=\"row_heading level0 row10\" >2/21/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row10_col0\" class=\"data row10 col0\" >75550</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row10_col1\" class=\"data row10 col1\" >473.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row11\" class=\"row_heading level0 row11\" >2/22/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row11_col0\" class=\"data row11 col0\" >77001</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row11_col1\" class=\"data row11 col1\" >1451.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row12\" class=\"row_heading level0 row12\" >2/23/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row12_col0\" class=\"data row12 col0\" >77022</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row12_col1\" class=\"data row12 col1\" >21.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row13\" class=\"row_heading level0 row13\" >2/24/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row13_col0\" class=\"data row13 col0\" >77241</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row13_col1\" class=\"data row13 col1\" >219.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row14\" class=\"row_heading level0 row14\" >2/25/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row14_col0\" class=\"data row14 col0\" >77754</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row14_col1\" class=\"data row14 col1\" >513.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row15\" class=\"row_heading level0 row15\" >2/26/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row15_col0\" class=\"data row15 col0\" >78166</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row15_col1\" class=\"data row15 col1\" >412.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row16\" class=\"row_heading level0 row16\" >2/27/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row16_col0\" class=\"data row16 col0\" >78600</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row16_col1\" class=\"data row16 col1\" >434.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row17\" class=\"row_heading level0 row17\" >2/28/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row17_col0\" class=\"data row17 col0\" >78928</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row17_col1\" class=\"data row17 col1\" >328.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002level0_row18\" class=\"row_heading level0 row18\" >2/29/20</th>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row18_col0\" class=\"data row18 col0\" >79356</td>\n",
              "                        <td id=\"T_9837df48_ffbc_11ea_8ab5_0242ac1c0002row18_col1\" class=\"data row18 col1\" >428.000000</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f502ca5e0b8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 127
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xGKSqR5dEfLU"
      },
      "source": [
        "#let us find the maximum infection rate of all the countries\n",
        "country=[i for i in confirm_agg.index]\n",
        "maximum_rate=[]\n",
        "for i in country:\n",
        "    maximum_rate.append(confirm_agg.loc[i].diff().max())\n",
        "confirm_agg['maximum_rate']=maximum_rate"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5xmOOhwsFKtt"
      },
      "source": [
        "confirm_agg.head(3)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MghO3_NsFk69",
        "outputId": "cd6ef0ad-e73f-4de8-cbb4-e1f979764c93",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        }
      },
      "source": [
        "confirm_agg['maximum_rate'].plot()\n",
        "plt.xticks(rotation=90,color='white')\n",
        "plt.yticks(color='white')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "dark"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CQ8bWBJBKl_p",
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              "                        <td id=\"T_66dd186a_ffc5_11ea_8ab5_0242ac1c0002row1_col0\" class=\"data row1 col0\" >26849.000000</td>\n",
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              "                        <td id=\"T_66dd186a_ffc5_11ea_8ab5_0242ac1c0002row7_col0\" class=\"data row7 col0\" >7099.000000</td>\n",
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              "<pandas.io.formats.style.Styler at 0x7f5029758780>"
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        }
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      "cell_type": "code",
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        "id": "1zQd-eF1NgB5",
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        "colab": {
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        }
      },
      "source": [
        "confirm_agg['maximum_rate'].to_frame().sort_values(by=['maximum_rate'],ascending=False)[-10:].style.background_gradient(cmap='Greens')"
      ],
      "execution_count": null,
      "outputs": [
        {
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              "            background-color:  #f7fcf5;\n",
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              "        }</style><table id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >maximum_rate</th>    </tr>    <tr>        <th class=\"index_name level0\" >Country/Region</th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
              "                <tr>\n",
              "                        <th id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >Western Sahara</th>\n",
              "                        <td id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002row0_col0\" class=\"data row0 col0\" >4.000000</td>\n",
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              "            <tr>\n",
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              "                        <td id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002row1_col0\" class=\"data row1 col0\" >3.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >Namibia</th>\n",
              "                        <td id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002row2_col0\" class=\"data row2 col0\" >3.000000</td>\n",
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              "                        <th id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >Laos</th>\n",
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              "                        <td id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002row4_col0\" class=\"data row4 col0\" >3.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >Seychelles</th>\n",
              "                        <td id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002row5_col0\" class=\"data row5 col0\" >2.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >Mauritania</th>\n",
              "                        <td id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002row6_col0\" class=\"data row6 col0\" >2.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >Nicaragua</th>\n",
              "                        <td id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002row7_col0\" class=\"data row7 col0\" >2.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >Bhutan</th>\n",
              "                        <td id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002row8_col0\" class=\"data row8 col0\" >1.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >Comoros</th>\n",
              "                        <td id=\"T_af870328_ffc5_11ea_8ab5_0242ac1c0002row9_col0\" class=\"data row9 col0\" >1.000000</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f5029758400>"
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          "metadata": {
            "tags": []
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          "execution_count": 196
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "10lYd9E6NNuV"
      },
      "source": [
        "from the above curve we conclude that rate of spread of this virus is maximum in US followed by china and france and minimum in bhuta and east african countries like comoros and saychelles.\n",
        "\n",
        "we don't have sufficient data to analzye like gender,age etc.\n",
        "this was all about analysis of confirm cases.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WcIrab4lQaSY",
        "outputId": "1e2293f4-801d-473f-c631-da9be9abb8ef",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 192
        }
      },
      "source": [
        "death_data.head(3)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Albania</td>\n",
              "      <td>41.1533</td>\n",
              "      <td>20.1683</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>8</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>11</td>\n",
              "      <td>15</td>\n",
              "      <td>15</td>\n",
              "      <td>16</td>\n",
              "      <td>17</td>\n",
              "      <td>20</td>\n",
              "      <td>20</td>\n",
              "      <td>21</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>23</td>\n",
              "      <td>23</td>\n",
              "      <td>23</td>\n",
              "      <td>23</td>\n",
              "      <td>23</td>\n",
              "      <td>24</td>\n",
              "      <td>25</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>27</td>\n",
              "      <td>27</td>\n",
              "      <td>27</td>\n",
              "      <td>27</td>\n",
              "      <td>28</td>\n",
              "      <td>28</td>\n",
              "      <td>30</td>\n",
              "      <td>30</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Algeria</td>\n",
              "      <td>28.0339</td>\n",
              "      <td>1.6596</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>17</td>\n",
              "      <td>17</td>\n",
              "      <td>19</td>\n",
              "      <td>21</td>\n",
              "      <td>25</td>\n",
              "      <td>26</td>\n",
              "      <td>29</td>\n",
              "      <td>31</td>\n",
              "      <td>35</td>\n",
              "      <td>44</td>\n",
              "      <td>58</td>\n",
              "      <td>86</td>\n",
              "      <td>105</td>\n",
              "      <td>130</td>\n",
              "      <td>152</td>\n",
              "      <td>173</td>\n",
              "      <td>193</td>\n",
              "      <td>205</td>\n",
              "      <td>235</td>\n",
              "      <td>256</td>\n",
              "      <td>275</td>\n",
              "      <td>293</td>\n",
              "      <td>313</td>\n",
              "      <td>326</td>\n",
              "      <td>336</td>\n",
              "      <td>348</td>\n",
              "      <td>364</td>\n",
              "      <td>367</td>\n",
              "      <td>375</td>\n",
              "      <td>384</td>\n",
              "      <td>392</td>\n",
              "      <td>402</td>\n",
              "      <td>407</td>\n",
              "      <td>415</td>\n",
              "      <td>419</td>\n",
              "      <td>425</td>\n",
              "      <td>432</td>\n",
              "      <td>437</td>\n",
              "      <td>444</td>\n",
              "      <td>450</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3 rows × 104 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "  Province/State Country/Region      Lat  ...  4/28/20  4/29/20  4/30/20\n",
              "0            NaN    Afghanistan  33.0000  ...       58       60       64\n",
              "1            NaN        Albania  41.1533  ...       30       30       31\n",
              "2            NaN        Algeria  28.0339  ...      437      444      450\n",
              "\n",
              "[3 rows x 104 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 198
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s_wMQ_11QelZ"
      },
      "source": [
        "china_data=death_data[death_data['Country/Region']=='China']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FphV1lW8Qy_8"
      },
      "source": [
        "death_data.drop(columns=['Province/State','Lat','Long'],axis=1,inplace=True)"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "imkWqL3uRQ_-"
      },
      "source": [
        "death_agg=death_data.groupby('Country/Region').sum()"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bwJKPmAiRYOU",
        "outputId": "b171c47b-d453-4c89-f4ca-55bd99003858",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 224
        }
      },
      "source": [
        "death_agg.head(3)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>4/29/20</th>\n",
              "      <th>4/30/20</th>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
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              "      <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",
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              "      <th></th>\n",
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              "      <th></th>\n",
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              "      <th></th>\n",
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              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>11</td>\n",
              "      <td>14</td>\n",
              "      <td>14</td>\n",
              "      <td>15</td>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>21</td>\n",
              "      <td>23</td>\n",
              "      <td>25</td>\n",
              "      <td>30</td>\n",
              "      <td>30</td>\n",
              "      <td>30</td>\n",
              "      <td>33</td>\n",
              "      <td>36</td>\n",
              "      <td>36</td>\n",
              "      <td>40</td>\n",
              "      <td>42</td>\n",
              "      <td>43</td>\n",
              "      <td>47</td>\n",
              "      <td>50</td>\n",
              "      <td>57</td>\n",
              "      <td>58</td>\n",
              "      <td>60</td>\n",
              "      <td>64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Albania</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>8</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>11</td>\n",
              "      <td>15</td>\n",
              "      <td>15</td>\n",
              "      <td>16</td>\n",
              "      <td>17</td>\n",
              "      <td>20</td>\n",
              "      <td>20</td>\n",
              "      <td>21</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>23</td>\n",
              "      <td>23</td>\n",
              "      <td>23</td>\n",
              "      <td>23</td>\n",
              "      <td>23</td>\n",
              "      <td>24</td>\n",
              "      <td>25</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>27</td>\n",
              "      <td>27</td>\n",
              "      <td>27</td>\n",
              "      <td>27</td>\n",
              "      <td>28</td>\n",
              "      <td>28</td>\n",
              "      <td>30</td>\n",
              "      <td>30</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Algeria</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>17</td>\n",
              "      <td>17</td>\n",
              "      <td>19</td>\n",
              "      <td>21</td>\n",
              "      <td>25</td>\n",
              "      <td>26</td>\n",
              "      <td>29</td>\n",
              "      <td>31</td>\n",
              "      <td>35</td>\n",
              "      <td>44</td>\n",
              "      <td>58</td>\n",
              "      <td>86</td>\n",
              "      <td>105</td>\n",
              "      <td>130</td>\n",
              "      <td>152</td>\n",
              "      <td>173</td>\n",
              "      <td>193</td>\n",
              "      <td>205</td>\n",
              "      <td>235</td>\n",
              "      <td>256</td>\n",
              "      <td>275</td>\n",
              "      <td>293</td>\n",
              "      <td>313</td>\n",
              "      <td>326</td>\n",
              "      <td>336</td>\n",
              "      <td>348</td>\n",
              "      <td>364</td>\n",
              "      <td>367</td>\n",
              "      <td>375</td>\n",
              "      <td>384</td>\n",
              "      <td>392</td>\n",
              "      <td>402</td>\n",
              "      <td>407</td>\n",
              "      <td>415</td>\n",
              "      <td>419</td>\n",
              "      <td>425</td>\n",
              "      <td>432</td>\n",
              "      <td>437</td>\n",
              "      <td>444</td>\n",
              "      <td>450</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3 rows × 100 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                1/22/20  1/23/20  1/24/20  ...  4/28/20  4/29/20  4/30/20\n",
              "Country/Region                             ...                           \n",
              "Afghanistan           0        0        0  ...       58       60       64\n",
              "Albania               0        0        0  ...       30       30       31\n",
              "Algeria               0        0        0  ...      437      444      450\n",
              "\n",
              "[3 rows x 100 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 208
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DK2kiO6QRo3L",
        "outputId": "d1ce8313-83dd-4146-8589-86c4f1c515c9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        }
      },
      "source": [
        "# this plot is about the number of death of people  from china , india ,UK and Russia\n",
        "plt.figure(figsize=(10,4))\n",
        "death_agg.loc['China'].plot(color='magenta',label='China')\n",
        "death_agg.loc['India'].plot(color='orange',label='India')\n",
        "death_agg.loc['Russia'].plot(color='darkmagenta',label='Russia')\n",
        "death_agg.loc['United Kingdom'].plot(color='orchid',label='UK')\n",
        "plt.xticks(color='azure')\n",
        "plt.yticks(color='azure')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "dark"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l2x58v3-90-u",
        "outputId": "f74c68f8-ae40-4c2f-fa6a-50cdeb2f7e85",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        }
      },
      "source": [
        "#lets plot china's death rate\n",
        "death_agg.loc['China'].diff().plot(label='death cases')\n",
        "x=death_agg.loc['China'].diff().max()\n",
        "plt.plot(86,x,'g^',label='max_deathrate')\n",
        "confirm_agg.loc['China'].diff().plot(color='darkblue',label='confirm cases')\n",
        "x=confirm_agg.loc['China'].diff().max()\n",
        "plt.plot(22,x,'r^',label='max_spreadrate')\n",
        "plt.xticks(color='azure')\n",
        "plt.yticks(color='azure')\n",
        "plt.title('CHINA',color='white')\n",
        "plt.legend()\n",
        "plt.show()\n",
        "# observe that though china had maximum spread on 13th feb 2020, but the death rate was low.\n",
        "#there was sudden rise in death rate after 11th april 2020 though the spread rate was low."
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "dark"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qMKaRFXYEVw8"
      },
      "source": [
        "df=pd.DataFrame(confirm_agg.loc['China']['4/11/20':])"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R5PuLi2aGTZw"
      },
      "source": [
        "df['maximum_death_rate']=df.diff()"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TVCdZLzOGULR",
        "outputId": "6e77005b-d038-443a-9ef7-aaaec00d789f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 467
        }
      },
      "source": [
        "df.style.background_gradient(cmap='rainbow')\n",
        "#the maximum death happend on 17 th april."
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "            background-color:  #1fd3e1;\n",
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              "            background-color:  #3e65fa;\n",
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              "            background-color:  #52f5cb;\n",
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              "            background-color:  #ff3b1e;\n",
              "            color:  #f1f1f1;\n",
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              "            background-color:  #6e1cff;\n",
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              "            background-color:  #ff2613;\n",
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              "            background-color:  #7610ff;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row15_col0 {\n",
              "            background-color:  #ff2211;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row15_col1 {\n",
              "            background-color:  #8000ff;\n",
              "            color:  #f1f1f1;\n",
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              "            background-color:  #ff1f10;\n",
              "            color:  #f1f1f1;\n",
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              "            background-color:  #7c06ff;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row17_col0 {\n",
              "            background-color:  #ff0d06;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row17_col1 {\n",
              "            background-color:  #6629fe;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row18_col0 {\n",
              "            background-color:  #ff0905;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row18_col1 {\n",
              "            background-color:  #8000ff;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row19_col0 {\n",
              "            background-color:  #ff0000;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row19_col1 {\n",
              "            background-color:  #7413ff;\n",
              "            color:  #f1f1f1;\n",
              "        }</style><table id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >China</th>        <th class=\"col_heading level0 col1\" >maximum_death_rate</th>    </tr></thead><tbody>\n",
              "                <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >4/11/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row0_col0\" class=\"data row0 col0\" >83014</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row0_col1\" class=\"data row0 col1\" >nan</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >4/12/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row1_col0\" class=\"data row1 col0\" >83134</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row1_col1\" class=\"data row1 col1\" >120.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >4/13/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row2_col0\" class=\"data row2 col0\" >83213</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row2_col1\" class=\"data row2 col1\" >79.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >4/14/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row3_col0\" class=\"data row3 col0\" >83306</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row3_col1\" class=\"data row3 col1\" >93.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >4/15/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row4_col0\" class=\"data row4 col0\" >83356</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row4_col1\" class=\"data row4 col1\" >50.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >4/16/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row5_col0\" class=\"data row5 col0\" >83403</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row5_col1\" class=\"data row5 col1\" >47.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >4/17/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row6_col0\" class=\"data row6 col0\" >83760</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row6_col1\" class=\"data row6 col1\" >357.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >4/18/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row7_col0\" class=\"data row7 col0\" >83787</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row7_col1\" class=\"data row7 col1\" >27.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >4/19/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row8_col0\" class=\"data row8 col0\" >83805</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row8_col1\" class=\"data row8 col1\" >18.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >4/20/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row9_col0\" class=\"data row9 col0\" >83817</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row9_col1\" class=\"data row9 col1\" >12.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row10\" class=\"row_heading level0 row10\" >4/21/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row10_col0\" class=\"data row10 col0\" >83853</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row10_col1\" class=\"data row10 col1\" >36.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row11\" class=\"row_heading level0 row11\" >4/22/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row11_col0\" class=\"data row11 col0\" >83868</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row11_col1\" class=\"data row11 col1\" >15.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row12\" class=\"row_heading level0 row12\" >4/23/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row12_col0\" class=\"data row12 col0\" >83884</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row12_col1\" class=\"data row12 col1\" >16.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row13\" class=\"row_heading level0 row13\" >4/24/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row13_col0\" class=\"data row13 col0\" >83899</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row13_col1\" class=\"data row13 col1\" >15.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row14\" class=\"row_heading level0 row14\" >4/25/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row14_col0\" class=\"data row14 col0\" >83909</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row14_col1\" class=\"data row14 col1\" >10.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row15\" class=\"row_heading level0 row15\" >4/26/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row15_col0\" class=\"data row15 col0\" >83912</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row15_col1\" class=\"data row15 col1\" >3.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row16\" class=\"row_heading level0 row16\" >4/27/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row16_col0\" class=\"data row16 col0\" >83918</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row16_col1\" class=\"data row16 col1\" >6.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row17\" class=\"row_heading level0 row17\" >4/28/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row17_col0\" class=\"data row17 col0\" >83940</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row17_col1\" class=\"data row17 col1\" >22.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row18\" class=\"row_heading level0 row18\" >4/29/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row18_col0\" class=\"data row18 col0\" >83944</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row18_col1\" class=\"data row18 col1\" >4.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002level0_row19\" class=\"row_heading level0 row19\" >4/30/20</th>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row19_col0\" class=\"data row19 col0\" >83956</td>\n",
              "                        <td id=\"T_e28d44f8_00ab_11eb_a9da_0242ac1c0002row19_col1\" class=\"data row19 col1\" >12.000000</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fedb181a390>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "10YpcKmDGgXW"
      },
      "source": [
        "#lets plot the maximum death rate of each country\n",
        "country=[i for i in death_agg.index]\n",
        "max_death_rate=[]\n",
        "for i in country:\n",
        "    max_death_rate.append(death_agg.loc[i].diff().max())\n",
        "death_agg['max_dead']=max_death_rate"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PbImdytTIj5H",
        "outputId": "e5eadf15-ad0d-4c60-f57c-4634d0e583ec",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        }
      },
      "source": [
        "death_agg['max_dead'].plot()\n",
        "plt.xticks(rotation=90,color='white')\n",
        "plt.yticks(color='white')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "dark"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m64-7GZ7Iwp1",
        "outputId": "a543c757-f8cb-4d59-fc39-786a20b6d819",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 275
        }
      },
      "source": [
        "death_agg['max_dead'].to_frame().sort_values(by=['max_dead'],ascending=False)[:10].style.background_gradient(cmap='Oranges')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<style  type=\"text/css\" >\n",
              "    #T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row0_col0 {\n",
              "            background-color:  #7f2704;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row1_col0 {\n",
              "            background-color:  #fd8c3b;\n",
              "            color:  #000000;\n",
              "        }    #T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row2_col0 {\n",
              "            background-color:  #fd9d53;\n",
              "            color:  #000000;\n",
              "        }    #T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row3_col0 {\n",
              "            background-color:  #fdab66;\n",
              "            color:  #000000;\n",
              "        }    #T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row4_col0 {\n",
              "            background-color:  #fdc38d;\n",
              "            color:  #000000;\n",
              "        }    #T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row5_col0 {\n",
              "            background-color:  #fdc794;\n",
              "            color:  #000000;\n",
              "        }    #T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row6_col0 {\n",
              "            background-color:  #fee8d2;\n",
              "            color:  #000000;\n",
              "        }    #T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row7_col0 {\n",
              "            background-color:  #fee9d3;\n",
              "            color:  #000000;\n",
              "        }    #T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row8_col0 {\n",
              "            background-color:  #fee9d3;\n",
              "            color:  #000000;\n",
              "        }    #T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row9_col0 {\n",
              "            background-color:  #fff5eb;\n",
              "            color:  #000000;\n",
              "        }</style><table id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >max_dead</th>    </tr>    <tr>        <th class=\"index_name level0\" >Country/Region</th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
              "                <tr>\n",
              "                        <th id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >US</th>\n",
              "                        <td id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row0_col0\" class=\"data row0 col0\" >2612.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >France</th>\n",
              "                        <td id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row1_col0\" class=\"data row1 col0\" >1440.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >China</th>\n",
              "                        <td id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row2_col0\" class=\"data row2 col0\" >1290.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >United Kingdom</th>\n",
              "                        <td id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row3_col0\" class=\"data row3 col0\" >1172.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >Spain</th>\n",
              "                        <td id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row4_col0\" class=\"data row4 col0\" >961.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >Italy</th>\n",
              "                        <td id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row5_col0\" class=\"data row5 col0\" >919.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >Germany</th>\n",
              "                        <td id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row6_col0\" class=\"data row6 col0\" >510.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >Belgium</th>\n",
              "                        <td id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row7_col0\" class=\"data row7 col0\" >496.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >Brazil</th>\n",
              "                        <td id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row8_col0\" class=\"data row8 col0\" >493.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >Canada</th>\n",
              "                        <td id=\"T_ab690ffa_00ad_11eb_a9da_0242ac1c0002row9_col0\" class=\"data row9 col0\" >251.000000</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fedb10b9940>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M9-rrMOyJmMa",
        "outputId": "795e4bc6-f6dc-4750-ff71-e00c25608d8e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 168
        }
      },
      "source": [
        "death_agg['max_dead'].to_frame().sort_values(by=['max_dead'],ascending=False)[-30:-25].style.background_gradient(cmap='Greens')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<style  type=\"text/css\" >\n",
              "    #T_e0472892_00ad_11eb_a9da_0242ac1c0002row0_col0 {\n",
              "            background-color:  #00441b;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_e0472892_00ad_11eb_a9da_0242ac1c0002row1_col0 {\n",
              "            background-color:  #00441b;\n",
              "            color:  #f1f1f1;\n",
              "        }    #T_e0472892_00ad_11eb_a9da_0242ac1c0002row2_col0 {\n",
              "            background-color:  #f7fcf5;\n",
              "            color:  #000000;\n",
              "        }    #T_e0472892_00ad_11eb_a9da_0242ac1c0002row3_col0 {\n",
              "            background-color:  #f7fcf5;\n",
              "            color:  #000000;\n",
              "        }    #T_e0472892_00ad_11eb_a9da_0242ac1c0002row4_col0 {\n",
              "            background-color:  #f7fcf5;\n",
              "            color:  #000000;\n",
              "        }</style><table id=\"T_e0472892_00ad_11eb_a9da_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >max_dead</th>    </tr>    <tr>        <th class=\"index_name level0\" >Country/Region</th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
              "                <tr>\n",
              "                        <th id=\"T_e0472892_00ad_11eb_a9da_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >Mauritania</th>\n",
              "                        <td id=\"T_e0472892_00ad_11eb_a9da_0242ac1c0002row0_col0\" class=\"data row0 col0\" >1.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e0472892_00ad_11eb_a9da_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >Djibouti</th>\n",
              "                        <td id=\"T_e0472892_00ad_11eb_a9da_0242ac1c0002row1_col0\" class=\"data row1 col0\" >1.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e0472892_00ad_11eb_a9da_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >Uganda</th>\n",
              "                        <td id=\"T_e0472892_00ad_11eb_a9da_0242ac1c0002row2_col0\" class=\"data row2 col0\" >0.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e0472892_00ad_11eb_a9da_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >Grenada</th>\n",
              "                        <td id=\"T_e0472892_00ad_11eb_a9da_0242ac1c0002row3_col0\" class=\"data row3 col0\" >0.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e0472892_00ad_11eb_a9da_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >Eritrea</th>\n",
              "                        <td id=\"T_e0472892_00ad_11eb_a9da_0242ac1c0002row4_col0\" class=\"data row4 col0\" >0.000000</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fedb10b9518>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SvDmL0A4KFI6"
      },
      "source": [
        "we observed that US,CHINA and FRANCE had maximum number of death cases and infection rate."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cDMfFQFXJ0c6"
      },
      "source": [
        "lat=[i for i in confirm_data['Lat']] #for confirmed cases\n",
        "lon=[i for i in confirm_data['Long']] #for confirmed cases longitude"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aXzntUpuOGB4"
      },
      "source": [
        "import geopandas as gpd\n",
        "from shapely.geometry import Point,Polygon"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JqG5E7ztOjCM"
      },
      "source": [
        "geo=[Point(xy) for xy in  zip(lon,lat)]\n",
        "g=gpd.GeoDataFrame(geometry=geo)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YALzqkybO55h"
      },
      "source": [
        " world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l-y5z31mPSh4",
        "outputId": "d033fa73-a9d4-4de4-f33a-1760765309ab",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        }
      },
      "source": [
        "fig,ax=plt.subplots(figsize=(15,10))\n",
        "world.plot(ax=ax,color='green')\n",
        "g.plot(ax=ax,color='pink')\n",
        "plt.title('confirm cases in the world',color='white')\n",
        "plt.axis('off')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AT5Yf8dQVFbW"
      },
      "source": [
        "corona_data=pd.DataFrame(confirm_agg[\"maximum_rate\"])\n",
        "death_data=pd.DataFrame(death_agg[\"max_dead\"])"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NyqoOFhTYBaF",
        "outputId": "c6abfca2-f553-4624-ae2e-d3ab180d3462",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "happiness_report"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(156, 9)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Eei5ddXiYKAt"
      },
      "source": [
        "useless=['Overall rank','Score','Generosity','Perceptions of corruption']\n",
        "happiness_report.drop(useless,axis=1,inplace=True)"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B23XbUfQYZKC"
      },
      "source": [
        "#change the index to join other data\n",
        "happiness_report.set_index(\"Country or region\",inplace=True)"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UStI7LWFY1Jt",
        "outputId": "8c7006af-31c6-4b91-aab6-9cf279d78b02",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        }
      },
      "source": [
        "data=corona_data.join(happiness_report,how='inner')\n",
        "data=death_data.join(data,how='inner')\n",
        "data.head()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>max_dead</th>\n",
              "      <th>maximum_rate</th>\n",
              "      <th>GDP per capita</th>\n",
              "      <th>Social support</th>\n",
              "      <th>Healthy life expectancy</th>\n",
              "      <th>Freedom to make life choices</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>7.0</td>\n",
              "      <td>232.0</td>\n",
              "      <td>0.350</td>\n",
              "      <td>0.517</td>\n",
              "      <td>0.361</td>\n",
              "      <td>0.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Albania</th>\n",
              "      <td>4.0</td>\n",
              "      <td>34.0</td>\n",
              "      <td>0.947</td>\n",
              "      <td>0.848</td>\n",
              "      <td>0.874</td>\n",
              "      <td>0.383</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Algeria</th>\n",
              "      <td>30.0</td>\n",
              "      <td>199.0</td>\n",
              "      <td>1.002</td>\n",
              "      <td>1.160</td>\n",
              "      <td>0.785</td>\n",
              "      <td>0.086</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Argentina</th>\n",
              "      <td>13.0</td>\n",
              "      <td>291.0</td>\n",
              "      <td>1.092</td>\n",
              "      <td>1.432</td>\n",
              "      <td>0.881</td>\n",
              "      <td>0.471</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Armenia</th>\n",
              "      <td>3.0</td>\n",
              "      <td>134.0</td>\n",
              "      <td>0.850</td>\n",
              "      <td>1.055</td>\n",
              "      <td>0.815</td>\n",
              "      <td>0.283</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             max_dead  ...  Freedom to make life choices\n",
              "Afghanistan       7.0  ...                         0.000\n",
              "Albania           4.0  ...                         0.383\n",
              "Algeria          30.0  ...                         0.086\n",
              "Argentina        13.0  ...                         0.471\n",
              "Armenia           3.0  ...                         0.283\n",
              "\n",
              "[5 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7HiysbskY_0p",
        "outputId": "4673bde8-dc94-449f-f0cf-d5740352da60",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 405
        }
      },
      "source": [
        "#let us find the correlation between the variables\n",
        "sns.heatmap(data.corr(),cmap='spring',annot=True, vmin=-1, vmax=1, center= 0)\n",
        "plt.xticks(color='White')\n",
        "plt.yticks(color='white')\n",
        "plt.show()"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yNNuxOZtotTP"
      },
      "source": [
        "A correlation matrix can help us quickly understand the correlations between each pair of variables. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6jZAbx-X9wQW",
        "outputId": "da705dd5-d656-4426-ff94-17743fe04929",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 335
        }
      },
      "source": [
        "x=data['Healthy life expectancy']\n",
        "y=data['max_dead']\n",
        "sns.regplot(x,y)\n",
        "plt.show()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KaMFXOEvDNsg"
      },
      "source": [
        "That was it for now . we have health life expectancy which is health  measure that combines age-specific mortality with morbidity or health status to estimate expected years of life in good health for persons at a given age . If we look at the plot , we observe that there are few nations or countries which have high LE but the death rate is high as well. One possible reason could be the lack of covid data we have which is of only 3 months. In the beginning, due to lack of covid awareness the death rate and the confirmed cases might be increasing.\n",
        "\n",
        "Data is very powerful. Combining different data can help us tell the story that matters and insights.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_-4rxyvqFAgw"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}