{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Introducción a Matplotlib \n", "\n", "[Matplotlib](https://matplotlib.org/) es una librería de Python para hacer gráficos en dos dimensiones de alta calidad y altamente configurables. Tiene excelente integración con otras librerías como pandas y numpy\n", "\n", "Adicionalmente matplotlib se integra con Jupyter mediante la magia `%matplotlib backend`. Entre las opciones de backend se encuentran\n", " \n", "- `inline` : Gráficos rasterizados en el notebook/lab\n", "- `notebook` : Gráficos interactivos en el notebook\n", "- `ipympl`: Gráficos interactivos en jupyter lab y vscode\n", "- `qt`, `gtk`, `osx` : Gráficos en una ventana emergente \n", "\n", "Puedes consultar más información sobre esta magia en un terminal de IPython usando:\n", "\n", "```python\n", "%matplotlib?\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Instalación**\n", " \n", "Con nuestro ambiente conda activado\n", "\n", " conda install matplotlib\n", " \n", "O si usamos jupyterlab/VSCode\n", "\n", " conda install matplotlib ipympl" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Importar**" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2020-05-24T03:32:01.997317Z", "start_time": "2020-05-24T03:32:01.991334Z" } }, "outputs": [ { "data": { "text/plain": [ "'3.5.1'" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Invocamos la magia con una de las opciones de backend\n", "%matplotlib inline\n", "# Importamos la librería\n", "import matplotlib as mpl\n", "display(mpl.__version__)\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "El modulo `pyplot` provee \n", "\n", "- Funciones para crear distintos tipos de gráficos\n", "- Una maquina de estados que añade los diversos elementos que queremos incluir en él\n", "\n", "A continuación vamos a revisar ambos" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Nuestra primera figura en matplotlib\n", "\n", "Consideremos los siguientes datos que representan el número de casos covid19 positivos totales desde el 22 de Enero de 2020 hasta el 13 de Mayo de 2020" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | 1/22/20 | \n", "1/23/20 | \n", "1/24/20 | \n", "1/25/20 | \n", "1/26/20 | \n", "1/27/20 | \n", "1/28/20 | \n", "1/29/20 | \n", "1/30/20 | \n", "1/31/20 | \n", "... | \n", "5/4/20 | \n", "5/5/20 | \n", "5/6/20 | \n", "5/7/20 | \n", "5/8/20 | \n", "5/9/20 | \n", "5/10/20 | \n", "5/11/20 | \n", "5/12/20 | \n", "5/13/20 | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Country/Region | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
Argentina | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "... | \n", "4887 | \n", "5020 | \n", "5208 | \n", "5371 | \n", "5611 | \n", "5776 | \n", "6034 | \n", "6278 | \n", "6563 | \n", "6879 | \n", "
Bolivia | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "... | \n", "1681 | \n", "1802 | \n", "1886 | \n", "2081 | \n", "2266 | \n", "2437 | \n", "2556 | \n", "2831 | \n", "2964 | \n", "3148 | \n", "
Brazil | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "... | \n", "108620 | \n", "115455 | \n", "126611 | \n", "135773 | \n", "146894 | \n", "156061 | \n", "162699 | \n", "169594 | \n", "178214 | \n", "190137 | \n", "
Chile | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "0 | \n", "... | \n", "20643 | \n", "22016 | \n", "23048 | \n", "24581 | \n", "25972 | \n", "27219 | \n", "28866 | \n", "30063 | \n", "31721 | \n", "34381 | \n", "
4 rows × 113 columns
\n", "