introduccion_colab_live_07b0ed82-599e-45a5-a89a-cbcdb23943bb.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VX4AXt1z06p7"
      },
      "source": [
        "# Introducción a Google Colaboratory\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3w9hDmeT1RFc"
      },
      "source": [
        "## Ejecución y edición de celdas"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kVycw82U1SNU"
      },
      "source": [
        "### Celdas de código"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pmj63Cv01Smg",
        "outputId": "f91ad15a-0716-4776-e06d-fcf1506dcf09"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "3"
            ]
          },
          "execution_count": 1,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "1 + 2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BizkQMEJ1bFT"
      },
      "source": [
        "### Celdas de texto"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "o1RZy_-O2qwR"
      },
      "source": [
        "#### Texto enriquericido\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-OXWFW_u2rNL"
      },
      "source": [
        "#### Imágenes o gifs"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k-Ui7NLh1bLf"
      },
      "source": [
        "![link text](https://media.giphy.com/media/6aGXQxkohixag/giphy.gif)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RrNr7t6F1bP8"
      },
      "source": [
        "## Variables"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3jaRCHkS1bTf"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "HiN7Chx11bWf"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RMzLQ0KF1bZY"
      },
      "source": [
        "## Línea de comandos"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "diJyGyWw3392"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IcPvNSH64OGR"
      },
      "source": [
        "## Instalación de librerías"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_q-ajRSrFK1Q"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "EvgpUkAGG1hH"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "XXW_W6F4JjzN"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bfbnB1rw437K"
      },
      "source": [
        "### Ciencia de datos"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Zh3EV2drAyRE"
      },
      "source": [
        "### Subir archivos"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "o2zBdfYDAwoT"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tWT-hVeekJ7Y"
      },
      "source": [
        "### Librerías para Ciencia de Datos\n",
        "\n",
        "- 📊 **matplotlib**: Generación de gráficos a partir de listas o arrays.\n",
        "- 🧑‍💻 **numpy**: Cómputo científico para la manipulación de vectores.\n",
        "- 🧑‍💻 **pandas**: Manipulación y análisis de datos de tablas y series temporales.\n",
        "- 🧑‍💻 **scipy**: Herramientas y algoritmos matemáticos.\n",
        "- 📊 **seaborn**: Visualización de datos estadísticos."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ARjmm8iZkKGG"
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import scipy as sc\n",
        "import seaborn as sns"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EMnwCNzMkKTd"
      },
      "source": [
        "### Gráficas"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "YRzwKWVPrsv2"
      },
      "outputs": [],
      "source": [
        "# load an example dataset\n",
        "from vega_datasets import data\n",
        "cars = data.cars()\n",
        "\n",
        "# plot the dataset, referencing dataframe column names\n",
        "import altair as alt\n",
        "alt.Chart(cars).mark_bar().encode(\n",
        "  x=alt.X('Miles_per_Gallon', bin=True),\n",
        "  y='count()',\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MvJKNGhb8pP8"
      },
      "source": [
        "## Atajos de teclado"
      ]
    }
  ],
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    "colab": {
      "collapsed_sections": [],
      "name": "introduccion_colab_live.ipynb",
      "provenance": []
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    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
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  "nbformat": 4,
  "nbformat_minor": 0
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