Introduction_to_Pandas_DataFrames.ipynb

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        "<a href=\"https://colab.research.google.com/github/HarivigneshA/Data-Science/blob/main/Introduction_to_Pandas_DataFrames.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
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    {
      "cell_type": "code",
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        "id": "wsBDAFATdngm"
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      "source": [
        "import pandas as pd"
      ],
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      "outputs": []
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        "id": "7c37tvkAhiqc"
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        "weather_data = {\n",
        "    'day': ['1/1/2017','1/2/2017','1/3/2017','1/4/2017','1/5/2017','1/6/2017'], \n",
        "    'temperature': [32,35,28,24,32,31], # numerical data\n",
        "    'windspeed': [6,7,2,7,4,2],  # numerical data\n",
        "    'event': ['Rain', 'Sunny', 'Snow','Snow','Rain', 'Sunny']    # categorical data\n",
        "}"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
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      "source": [
        "df = pd.DataFrame(weather_data)\n",
        "df"
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              "      <th>event</th>\n",
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              "      <td>1/1/2017</td>\n",
              "      <td>32</td>\n",
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              "      <td>Rain</td>\n",
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              "      <td>Sunny</td>\n",
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              "      <td>1/3/2017</td>\n",
              "      <td>28</td>\n",
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              "      <td>Snow</td>\n",
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              "      <th>3</th>\n",
              "      <td>1/4/2017</td>\n",
              "      <td>24</td>\n",
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              "      <td>Snow</td>\n",
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              "      <td>32</td>\n",
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              "      <td>Rain</td>\n",
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              "      <td>Sunny</td>\n",
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            "text/plain": [
              "        day  temperature  windspeed  event\n",
              "0  1/1/2017           32          6   Rain\n",
              "1  1/2/2017           35          7  Sunny\n",
              "2  1/3/2017           28          2   Snow\n",
              "3  1/4/2017           24          7   Snow\n",
              "4  1/5/2017           32          4   Rain\n",
              "5  1/6/2017           31          2  Sunny"
            ]
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      },
      "source": [
        "df.head(2)"
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              "      <th>windspeed</th>\n",
              "      <th>event</th>\n",
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              "        day  temperature  windspeed  event\n",
              "0  1/1/2017           32          6   Rain\n",
              "1  1/2/2017           35          7  Sunny"
            ]
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      "source": [
        "df.tail(3)"
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              "        day  temperature  windspeed  event\n",
              "3  1/4/2017           24          7   Snow\n",
              "4  1/5/2017           32          4   Rain\n",
              "5  1/6/2017           31          2  Sunny"
            ]
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      "source": [
        "df.sample(1)"
      ],
      "execution_count": null,
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        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>day</th>\n",
              "      <th>temperature</th>\n",
              "      <th>windspeed</th>\n",
              "      <th>event</th>\n",
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              "      <td>1/5/2017</td>\n",
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              "      <td>Rain</td>\n",
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              "        day  temperature  windspeed event\n",
              "4  1/5/2017           32          4  Rain"
            ]
          },
          "metadata": {
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          "execution_count": 6
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      "source": [
        "df.columns"
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          "data": {
            "text/plain": [
              "Index(['day', 'temperature', 'windspeed', 'event'], dtype='object')"
            ]
          },
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            "tags": []
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          "execution_count": 7
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    },
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      "source": [
        " df.set_index('day',inplace=True)"
      ],
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        "df.reset_index(inplace=True)"
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      "source": [
        "df[['temperature','event']]"
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              "      <th>temperature</th>\n",
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              "      <th>0</th>\n",
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              "      <td>35</td>\n",
              "      <td>Sunny</td>\n",
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              "      <td>28</td>\n",
              "      <td>Snow</td>\n",
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              "      <td>Snow</td>\n",
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              "      <td>32</td>\n",
              "      <td>Rain</td>\n",
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            "text/plain": [
              "   temperature  event\n",
              "0           32   Rain\n",
              "1           35  Sunny\n",
              "2           28   Snow\n",
              "3           24   Snow\n",
              "4           32   Rain\n",
              "5           31  Sunny"
            ]
          },
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          "execution_count": 10
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      "source": [
        " df.set_index('day',inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
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      },
      "source": [
        "df.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Index: 6 entries, 1/1/2017 to 1/6/2017\n",
            "Data columns (total 3 columns):\n",
            " #   Column       Non-Null Count  Dtype \n",
            "---  ------       --------------  ----- \n",
            " 0   temperature  6 non-null      int64 \n",
            " 1   windspeed    6 non-null      int64 \n",
            " 2   event        6 non-null      object\n",
            "dtypes: int64(2), object(1)\n",
            "memory usage: 192.0+ bytes\n"
          ],
          "name": "stdout"
        }
      ]
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        "outputId": "763c70e2-a267-4938-b083-7c8c30ca0f8d"
      },
      "source": [
        "df['event'].min()"
      ],
      "execution_count": null,
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        {
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
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            "text/plain": [
              "'Rain'"
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          "execution_count": 13
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}