C8_Groupby.ipynb

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      "authorship_tag": "ABX9TyNGirmj9rUvzTPlRBTEwFI4",
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    "kernelspec": {
      "name": "python3",
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Markohf/CD_Flash_DS/blob/main/C8_Groupby.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Groupby\n",
        "\n",
        "Una forma sencilla y rápida de entender a groupby es como una forma de hacer tablas dinámicas usando pandas."
      ],
      "metadata": {
        "id": "yGbs_etImwhF"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "NsJr39KimrVZ"
      },
      "outputs": [],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd"
      ],
      "metadata": {
        "id": "MILf5QpmnODZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "filename = '/content/drive/MyDrive/Flashcamp - Data Science/BBDD/passenger_modified.csv'\n",
        "df = pd.read_csv(filename)\n",
        "df.head()"
      ],
      "metadata": {
        "id": "0paCqOsHnRxn"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "id": "ZEmDJtobnnA0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe().round(2)"
      ],
      "metadata": {
        "id": "VoNm2mdenqbx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['Age'].max()"
      ],
      "metadata": {
        "id": "CJXDNEvyn0Kp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby('Type of Travel')[['Age']].mean()"
      ],
      "metadata": {
        "id": "3WXJVQeen5Tr"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby(['Class', 'Gender'])[['Age']].mean()"
      ],
      "metadata": {
        "id": "kXu-EYodoE4w"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}