cleaning_the_data_and_uploading_it_to_drive_.ipynb

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    "colab": {
      "name": "cleaning the data and uploading it to drive.",
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        "<a href=\"https://colab.research.google.com/github/e-aditi/self-assigned-mini-project-1/blob/master/cleaning_the_data_and_uploading_it_to_drive_.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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        "id": "KNWZUOpXFRia",
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          "height": 70
        },
        "outputId": "013ab6f0-9226-408f-e74e-d5160e1b9854"
      },
      "source": [
        "path = '/content/covid_data.csv'\n",
        "import pandas as pd\n",
        "improve_data=pd.read_csv(path)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py:2718: DtypeWarning: Columns (1) have mixed types.Specify dtype option on import or set low_memory=False.\n",
            "  interactivity=interactivity, compiler=compiler, result=result)\n"
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          "name": "stderr"
        }
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          "height": 402
        },
        "outputId": "7f89076d-0590-4fc2-8827-7f53c391f4aa"
      },
      "source": [
        "improve_data"
      ],
      "execution_count": null,
      "outputs": [
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              "         s.no     sex  C_pos  C_sym  ...  diabetes   hw  risk  Unnamed: 10\n",
              "0         NaN    male    0.0    0.0  ...       0.0  0.0  0.09          NaN\n",
              "1         NaN    male    0.0    0.0  ...       1.0  0.0  0.09          NaN\n",
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              "4         NaN  female    0.0    0.0  ...       0.0  0.0  0.09          NaN\n",
              "...       ...     ...    ...    ...  ...       ...  ...   ...          ...\n",
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              "1048573   NaN     NaN    NaN    NaN  ...       NaN  NaN  0.00          NaN\n",
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              "\n",
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rLxUFbxNLpjI"
      },
      "source": [
        "improve_data.drop([\"s.no\",\"Unnamed: 10\"],axis=1,inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qlRDqXAyMHH8"
      },
      "source": [
        "improve_data.head()"
      ],
      "execution_count": null,
      "outputs": []
    },
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      "cell_type": "code",
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        "outputId": "494e5741-7893-4eea-a3b4-7c192736983c"
      },
      "source": [
        "sex = pd.get_dummies(improve_data['sex'],drop_first=True)\n",
        "sex"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "         male  other  undefined\n",
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              "...       ...    ...        ...\n",
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              "\n",
              "[1048575 rows x 3 columns]"
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      "source": [
        "sex.drop([\"other\",\"undefined\"],axis=1,inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
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        "sex.head()"
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              "   male\n",
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              "4     0"
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        "improve_data = pd.concat([improve_data,sex],axis=1)\n",
        "improve_data.drop([\"sex\"],axis=1,inplace=True)\n",
        "improve_data.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
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              "</div>"
            ],
            "text/plain": [
              "   C_pos  C_sym  C_con  asthma  lung_d  diabetes   hw  risk  male\n",
              "0    0.0    0.0    0.0     0.0     0.0       0.0  0.0  0.09     1\n",
              "1    0.0    0.0    0.0     0.0     1.0       1.0  0.0  0.09     1\n",
              "2    0.0    0.0    0.0     0.0     0.0       0.0  0.0  0.09     0\n",
              "3    0.0    0.0    0.0     0.0     0.0       1.0  0.0  0.09     1\n",
              "4    0.0    0.0    0.0     0.0     0.0       0.0  0.0  0.09     0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Xx8KWWfLNDSg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "outputId": "2f4417fc-d438-4f16-cd57-d7bff6df6349"
      },
      "source": [
        "improve_data[improve_data <= 0.9] = 0\n",
        "improve_data.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "      <th></th>\n",
              "      <th>C_pos</th>\n",
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              "      <th>C_con</th>\n",
              "      <th>asthma</th>\n",
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              "      <th>diabetes</th>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
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            "text/plain": [
              "   C_pos  C_sym  C_con  asthma  lung_d  diabetes   hw  risk  male\n",
              "0    0.0    0.0    0.0     0.0     0.0       0.0  0.0   0.0     1\n",
              "1    0.0    0.0    0.0     0.0     1.0       1.0  0.0   0.0     1\n",
              "2    0.0    0.0    0.0     0.0     0.0       0.0  0.0   0.0     0\n",
              "3    0.0    0.0    0.0     0.0     0.0       1.0  0.0   0.0     1\n",
              "4    0.0    0.0    0.0     0.0     0.0       0.0  0.0   0.0     0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cQyG8PmLNWYp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "outputId": "2905ae39-edbe-4210-ff5f-7e29e1b3a3a5"
      },
      "source": [
        "improve_data[improve_data>0.9]=1\n",
        "improve_data.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>C_pos</th>\n",
              "      <th>C_sym</th>\n",
              "      <th>C_con</th>\n",
              "      <th>asthma</th>\n",
              "      <th>lung_d</th>\n",
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            "text/plain": [
              "   C_pos  C_sym  C_con  asthma  lung_d  diabetes   hw  risk  male\n",
              "0    0.0    0.0    0.0     0.0     0.0       0.0  0.0   0.0     1\n",
              "1    0.0    0.0    0.0     0.0     1.0       1.0  0.0   0.0     1\n",
              "2    0.0    0.0    0.0     0.0     0.0       0.0  0.0   0.0     0\n",
              "3    0.0    0.0    0.0     0.0     0.0       1.0  0.0   0.0     1\n",
              "4    0.0    0.0    0.0     0.0     0.0       0.0  0.0   0.0     0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0xnKvTT_NjkR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 185
        },
        "outputId": "be32553d-4c73-4cd6-e0e2-fd158c0834db"
      },
      "source": [
        "improve_data.isnull().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "C_pos       342242\n",
              "C_sym       342242\n",
              "C_con       342242\n",
              "asthma      342242\n",
              "lung_d      342242\n",
              "diabetes    342242\n",
              "hw          342242\n",
              "risk             0\n",
              "male             0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "seeJ677GNt1M",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 185
        },
        "outputId": "c926e14e-fc85-4143-e5cf-1722844b8c14"
      },
      "source": [
        "zer=0\n",
        "improve_data['C_pos'].fillna(zer,inplace=True)\n",
        "improve_data.isnull().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "C_pos       0\n",
              "C_sym       0\n",
              "C_con       0\n",
              "asthma      0\n",
              "lung_d      0\n",
              "diabetes    0\n",
              "hw          0\n",
              "risk        0\n",
              "male        0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ni5pAwvoNzyE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "outputId": "dcee4edf-3e60-41d8-8cb1-362a0fcf3843"
      },
      "source": [
        "improve_data.tail()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    <tr>\n",
              "      <th>1048574</th>\n",
              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
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              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         C_pos  C_sym  C_con  asthma  lung_d  diabetes   hw  risk  male\n",
              "1048570    0.0    0.0    0.0     0.0     0.0       0.0  0.0   0.0     0\n",
              "1048571    0.0    0.0    0.0     0.0     0.0       0.0  0.0   0.0     0\n",
              "1048572    0.0    0.0    0.0     0.0     0.0       0.0  0.0   0.0     0\n",
              "1048573    0.0    0.0    0.0     0.0     0.0       0.0  0.0   0.0     0\n",
              "1048574    0.0    0.0    0.0     0.0     0.0       0.0  0.0   0.0     0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Thcfv64DOLJD",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 121
        },
        "outputId": "d7497412-814c-4690-8cf1-ea4b148d8e10"
      },
      "source": [
        "# Import Drive API and authenticate.\n",
        "from google.colab import drive\n",
        "\n",
        "# Mount your Drive to the Colab VM.\n",
        "drive.mount('/gdrive')\n",
        "\n",
        "# Write the DataFrame to CSV file.\n",
        "with open('/gdrive/My Drive/foo.csv', 'w') as f:\n",
        "  improve_data.to_csv(f)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /gdrive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UJFSVMdyPNOM"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}