AQI_india.ipynb

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      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline"
      ]
    },
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      "source": [
        "df=pd.read_csv('air-quality-india.csv')\n",
        "df.head()"
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              "             Timestamp  Year  Month  Day  Hour   PM2.5\n",
              "0  2017-11-07 12:00:00  2017     11    7    12   64.51\n",
              "1  2017-11-07 13:00:00  2017     11    7    13   69.95\n",
              "2  2017-11-07 14:00:00  2017     11    7    14   92.79\n",
              "3  2017-11-07 15:00:00  2017     11    7    15  109.66\n",
              "4  2017-11-07 16:00:00  2017     11    7    16  116.50"
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              "(36192, 6)"
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            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 36192 entries, 0 to 36191\n",
            "Data columns (total 6 columns):\n",
            " #   Column     Non-Null Count  Dtype  \n",
            "---  ------     --------------  -----  \n",
            " 0   Timestamp  36192 non-null  object \n",
            " 1   Year       36192 non-null  int64  \n",
            " 2   Month      36192 non-null  int64  \n",
            " 3   Day        36192 non-null  int64  \n",
            " 4   Hour       36192 non-null  int64  \n",
            " 5   PM2.5      36192 non-null  float64\n",
            "dtypes: float64(1), int64(4), object(1)\n",
            "memory usage: 1.7+ MB\n"
          ]
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        "df.describe()"
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      "execution_count": 6,
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            "text/plain": [
              "               Year         Month           Day          Hour         PM2.5\n",
              "count  36192.000000  36192.000000  36192.000000  36192.000000  36192.000000\n",
              "mean    2019.682278      6.331841     15.716401     11.477840     49.308429\n",
              "std        1.345011      3.593321      8.859769      6.925088     24.863511\n",
              "min     2017.000000      1.000000      1.000000      0.000000      7.020000\n",
              "25%     2019.000000      3.000000      8.000000      5.000000     28.080000\n",
              "50%     2020.000000      6.000000     16.000000     11.000000     45.730000\n",
              "75%     2021.000000     10.000000     23.000000     17.000000     64.520000\n",
              "max     2022.000000     12.000000     31.000000     23.000000    245.630000"
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              "      <th>50%</th>\n",
              "      <td>2020.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>45.730000</td>\n",
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              "      <th>75%</th>\n",
              "      <td>2021.000000</td>\n",
              "      <td>10.000000</td>\n",
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              "      <td>17.000000</td>\n",
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              "      <td>12.000000</td>\n",
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          "data": {
            "text/plain": [
              "Timestamp    0\n",
              "Year         0\n",
              "Month        0\n",
              "Day          0\n",
              "Hour         0\n",
              "PM2.5        0\n",
              "dtype: int64"
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              "0"
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        "df.pivot_table(values='PM2.5', index='Hour', columns='Year').head()"
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      "execution_count": 9,
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          "data": {
            "text/plain": [
              "Year        2017       2018       2019       2020       2021       2022\n",
              "Hour                                                                   \n",
              "0      88.248367  50.741093  50.607333  43.163818  44.515159  49.133910\n",
              "1      87.370833  51.013785  49.126854  42.400057  43.739169  48.435530\n",
              "2      90.833469  53.184920  49.385732  42.129286  43.961146  49.136316\n",
              "3     100.352292  57.246440  51.040342  43.680543  45.715747  51.971579\n",
              "4     108.137755  59.940452  53.655831  45.246866  47.587649  54.564697"
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              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>2020</th>\n",
              "      <th>2021</th>\n",
              "      <th>2022</th>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig,axes=plt.subplots(figsize=(20,8))\n",
        "da=df.pivot_table(values='PM2.5', index='Hour', columns='Year')\n",
        "sns.heatmap(da,ax=axes)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 515
        },
        "id": "JdiK1QiPgNL0",
        "outputId": "b3de03c5-c7cd-4aac-ef04-ad79e36f9850"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f8a1916db10>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x576 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig,axes=plt.subplots(figsize=(15,5))\n",
        "df.groupby('Year')['PM2.5'].mean().plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 352
        },
        "id": "e7utSFNaTdjx",
        "outputId": "443b0cc4-00d4-472f-fb80-fcd1b6bf7dc1"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f8a167d7f90>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "In INDIA from month of octobar,marks the beginning of winter season where the temperture ranges from 2 degrees to 30 degree centegrate throughout the lenght and breadth of country.\n",
        "where the majority of the region is free from any moisture and the season is absolutly dry.\n",
        "\n",
        "With burning of paddy fields to prepare the farms for Rabi crop and Diwali festival, India sees large amount of pollution hence increase in PM 2.5\n",
        "Therefore,the Months,10,11,12,1 ( Octobar TO January ) Sees high amount of PM 2.5 Matter.\n",
        "\n",
        "India also witness strong , South-West Moonsoon Winds ( Rainfall ) , in the Months 6,7,8,9( June TO September ), where most of the region is wet and sees less amount of PM2.5 matters.\n",
        "\n",
        "Remaining Months 2,3,4,5 ( Feburary To May ) India , witness Hrash Summer, with clear skies, and medium amount of Forests Fires, hence the PM2.5 levels are moderate."
      ],
      "metadata": {
        "id": "6wAisMG7WMKO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "fig,axes=plt.subplots(figsize=(15,5))\n",
        "sns.violinplot(x=\"Month\", y=\"PM2.5\", data=df, palette='rainbow')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 352
        },
        "id": "WXz7cV_SUyGT",
        "outputId": "44fcba71-8014-4832-8e1e-2addd528ece1"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f8a162c29d0>"
            ]
          },
          "metadata": {},
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig,axes=plt.subplots(figsize=(15,5))\n",
        "sns.kdeplot(df['PM2.5'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 352
        },
        "id": "K-kR7yICV2W8",
        "outputId": "e442d75c-faf4-4f4e-ac99-e58844535b3c"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f8a16166250>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}