{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "07e8812a",
   "metadata": {},
   "source": [
    "# Librería matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "407cc917",
   "metadata": {},
   "source": [
    "(basado en https://matplotlib.org/stable/tutorials/introductory/quick_start.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "430b3724",
   "metadata": {},
   "source": [
    "Matplotlib es un paquete python para la generación de gráficos.\n",
    "Permite obtener resultados de calidad de forma rápida en gran variedad de formatos.\n",
    "\n",
    "La idea de este breve repaso a matplotlib es tratar de comprender su funcionamiento básico.\n",
    "Entender los cambios que podemos realizar sobre los diferentes elementos para poder entender y modificar ejemplos más complejos.\n",
    "\n",
    "Antes de empezar es buena idea echar un vistazo a la galería http://matplotlib.org/gallery.html para ver las posibilidades que nos ofrece."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a03c65fe",
   "metadata": {},
   "source": [
    "## Primera gráfica"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0af2afb0",
   "metadata": {},
   "source": [
    "Matplotlib posee un montón de módulos que pueden resultar confusos al principio.\n",
    "La forma más recomendable de empezar es centrarse en el módulo ``pyplot``.\n",
    "\n",
    "El módulo ``pyplot`` es el encargado de juntar toda la potencia de matplotlib. Se trata del punto de partida para:\n",
    "\n",
    "* Preparar las figuras\n",
    "* Pintar las gráficas\n",
    "* Hacer modificaciones sobre las gráficas\n",
    "\n",
    "Con este módulo, cada función que invoquemos realizará un cambio sobre la figura: pintar una línea, añadir una etiqueta, cambiar los límites de un eje,...\n",
    "\n",
    "Las funciones que pintan los gráficos en general utilizarán un array de numpy o un objeto similar como entrada. Las series y dataframes de pandas suelen funcionar (aunque no para todas las funciones). En todo caso se pueden convertir a un array de numpy antes de plotearlos.\n",
    "\n",
    "Importamos los módulos que utilizaremos:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a8ce358d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f6c1850",
   "metadata": {},
   "source": [
    "Un ejemplo muy sencillo que podemos realizar con matplotlib es el siguiente:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4bc37f86",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([1, 2, 3, 4], [1, 4, 2, 3])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e412b2d",
   "metadata": {},
   "source": [
    "Simplemente hemos especificado las coordenadas x e y de los puntos que queremos conectar con líneas utilizando dos listas y todo lo demás ha funcionado solo.\n",
    "\n",
    "Matplotlib ha realizado una serie de acciones por defecto como crear la figura (lienzo),\n",
    "crear una gráfica en el lienzo, asignar valores al eje X, etc."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7b855c8",
   "metadata": {},
   "source": [
    "Podemos especificar estas coordenadas como una función:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "69583d25",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0,15,30)\n",
    "y = np.sin(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b9113a02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f7f462ade10>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x,y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97568fc4",
   "metadata": {},
   "source": [
    "## Partes de una figura"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8be3a8c2",
   "metadata": {},
   "source": [
    "En una figura podemos encontrar una gran variedad de objetos diferentes que la componen:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "194825b8",
   "metadata": {},
   "source": [
    "![](_images/anatomia_figura.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99b81655",
   "metadata": {},
   "source": [
    "El pintado se realiza a través del objeto  `Figure` (http://matplotlib.org/api/figure_api.html#matplotlib.figure.Figure).\n",
    "Se puede ver como el lienzo donde vamos a pintar nuestra/s gráfica/s. Es aquí donde especificaremos cosas como el tamaño, la resolución en dpi o su aspect ratio.\n",
    "\n",
    "Cada ``Figure`` puede contener uno o varios ``Axes``: "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef31145b",
   "metadata": {},
   "source": [
    "![](_images/matplotlib_2.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ff5633f",
   "metadata": {},
   "source": [
    "Un ``Axes`` es lo que identificamos como una gráfica. Puede ser una línea, un histograma, etc. A través de este objeto podemos acceder y modificar la apariencia, los ejes, etiquetas, título, leyenda, etc, por medio de distintos métodos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4ac41945",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXwAAAD8CAYAAAB0IB+mAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAANT0lEQVR4nO3cYYjkd33H8ffHO1NpjKb0VpC706T00njYQtIlTRFqirZc8uDugUXuIFgleGAbKVWEFEuU+MiGWhCu1ZOKVdAYfSALntwDjQTEC7chNXgXItvTeheFrDHNk6Ax7bcPZtKdrneZf3Zndy/7fb/gYP7/+e3Mlx97752d2ZlUFZKk7e8VWz2AJGlzGHxJasLgS1ITBl+SmjD4ktSEwZekJqYGP8lnkzyZ5PuXuD5JPplkKcmjSW6c/ZiSpPUa8gj/c8CBF7n+VmDf+N9R4F/WP5YkadamBr+qHgR+/iJLDgGfr5FTwNVJXj+rASVJs7FzBrexGzg/cXxhfO6nqxcmOcrotwCuvPLKP7z++utncPeS1MfDDz/8s6qaW8vXziL4g1XVceA4wPz8fC0uLm7m3UvSy16S/1zr187ir3SeAPZOHO8Zn5MkXUZmEfwF4F3jv9a5GXimqn7t6RxJ0taa+pROki8BtwC7klwAPgK8EqCqPgWcAG4DloBngfds1LCSpLWbGvyqOjLl+gL+emYTSZI2hO+0laQmDL4kNWHwJakJgy9JTRh8SWrC4EtSEwZfkpow+JLUhMGXpCYMviQ1YfAlqQmDL0lNGHxJasLgS1ITBl+SmjD4ktSEwZekJgy+JDVh8CWpCYMvSU0YfElqwuBLUhMGX5KaMPiS1ITBl6QmDL4kNWHwJakJgy9JTRh8SWrC4EtSEwZfkpow+JLUhMGXpCYMviQ1YfAlqYlBwU9yIMnjSZaS3HWR69+Q5IEkjyR5NMltsx9VkrQeU4OfZAdwDLgV2A8cSbJ/1bK/B+6vqhuAw8A/z3pQSdL6DHmEfxOwVFXnquo54D7g0Ko1BbxmfPm1wE9mN6IkaRaGBH83cH7i+ML43KSPArcnuQCcAN5/sRtKcjTJYpLF5eXlNYwrSVqrWb1oewT4XFXtAW4DvpDk1267qo5X1XxVzc/Nzc3oriVJQwwJ/hPA3onjPeNzk+4A7geoqu8CrwJ2zWJASdJsDAn+aWBfkmuTXMHoRdmFVWt+DLwNIMmbGAXf52wk6TIyNfhV9TxwJ3ASeIzRX+OcSXJPkoPjZR8E3pvke8CXgHdXVW3U0JKkl27nkEVVdYLRi7GT5+6euHwWeMtsR5MkzZLvtJWkJgy+JDVh8CWpCYMvSU0YfElqwuBLUhMGX5KaMPiS1ITBl6QmDL4kNWHwJakJgy9JTRh8SWrC4EtSEwZfkpow+JLUhMGXpCYMviQ1YfAlqQmDL0lNGHxJasLgS1ITBl+SmjD4ktSEwZekJgy+JDVh8CWpCYMvSU0YfElqwuBLUhMGX5KaMPiS1ITBl6QmDL4kNTEo+EkOJHk8yVKSuy6x5p1JziY5k+SLsx1TkrReO6ctSLIDOAb8GXABOJ1koarOTqzZB/wd8JaqejrJ6zZqYEnS2gx5hH8TsFRV56rqOeA+4NCqNe8FjlXV0wBV9eRsx5QkrdeQ4O8Gzk8cXxifm3QdcF2S7yQ5leTAxW4oydEki0kWl5eX1zaxJGlNZvWi7U5gH3ALcAT4TJKrVy+qquNVNV9V83NzczO6a0nSEEOC/wSwd+J4z/jcpAvAQlX9qqp+CPyA0Q8ASdJlYkjwTwP7klyb5ArgMLCwas3XGD26J8kuRk/xnJvdmJKk9Zoa/Kp6HrgTOAk8BtxfVWeS3JPk4HjZSeCpJGeBB4APVdVTGzW0JOmlS1VtyR3Pz8/X4uLilty3JL1cJXm4qubX8rW+01aSmjD4ktSEwZekJgy+JDVh8CWpCYMvSU0YfElqwuBLUhMGX5KaMPiS1ITBl6QmDL4kNWHwJakJgy9JTRh8SWrC4EtSEwZfkpow+JLUhMGXpCYMviQ1YfAlqQmDL0lNGHxJasLgS1ITBl+SmjD4ktSEwZekJgy+JDVh8CWpCYMvSU0YfElqwuBLUhMGX5KaMPiS1ITBl6QmBgU/yYEkjydZSnLXi6x7R5JKMj+7ESVJszA1+El2AMeAW4H9wJEk+y+y7irgb4CHZj2kJGn9hjzCvwlYqqpzVfUccB9w6CLrPgZ8HPjFDOeTJM3IkODvBs5PHF8Yn/s/SW4E9lbV11/shpIcTbKYZHF5efklDytJWrt1v2ib5BXAJ4APTltbVcerar6q5ufm5tZ715Kkl2BI8J8A9k4c7xmfe8FVwJuBbyf5EXAzsOALt5J0eRkS/NPAviTXJrkCOAwsvHBlVT1TVbuq6pqqugY4BRysqsUNmViStCZTg19VzwN3AieBx4D7q+pMknuSHNzoASVJs7FzyKKqOgGcWHXu7kusvWX9Y0mSZs132kpSEwZfkpow+JLUhMGXpCYMviQ1YfAlqQmDL0lNGHxJasLgS1ITBl+SmjD4ktSEwZekJgy+JDVh8CWpCYMvSU0YfElqwuBLUhMGX5KaMPiS1ITBl6QmDL4kNWHwJakJgy9JTRh8SWrC4EtSEwZfkpow+JLUhMGXpCYMviQ1YfAlqQmDL0lNGHxJasLgS1ITBl+SmhgU/CQHkjyeZCnJXRe5/gNJziZ5NMk3k7xx9qNKktZjavCT7ACOAbcC+4EjSfavWvYIMF9VfwB8FfiHWQ8qSVqfIY/wbwKWqupcVT0H3AccmlxQVQ9U1bPjw1PAntmOKUlaryHB3w2cnzi+MD53KXcA37jYFUmOJllMsri8vDx8SknSus30RdsktwPzwL0Xu76qjlfVfFXNz83NzfKuJUlT7Byw5glg78TxnvG5/yfJ24EPA2+tql/OZjxJ0qwMeYR/GtiX5NokVwCHgYXJBUluAD4NHKyqJ2c/piRpvaYGv6qeB+4ETgKPAfdX1Zkk9yQ5OF52L/Bq4CtJ/j3JwiVuTpK0RYY8pUNVnQBOrDp398Tlt894LknSjPlOW0lqwuBLUhMGX5KaMPiS1ITBl6QmDL4kNWHwJakJgy9JTRh8SWrC4EtSEwZfkpow+JLUhMGXpCYMviQ1YfAlqQmDL0lNGHxJasLgS1ITBl+SmjD4ktSEwZekJgy+JDVh8CWpCYMvSU0YfElqwuBLUhMGX5KaMPiS1ITBl6QmDL4kNWHwJakJgy9JTRh8SWrC4EtSEwZfkpoYFPwkB5I8nmQpyV0Xuf43knx5fP1DSa6Z+aSSpHWZGvwkO4BjwK3AfuBIkv2rlt0BPF1Vvwv8E/DxWQ8qSVqfIY/wbwKWqupcVT0H3AccWrXmEPBv48tfBd6WJLMbU5K0XjsHrNkNnJ84vgD80aXWVNXzSZ4Bfhv42eSiJEeBo+PDXyb5/lqG3oZ2sWqvGnMvVrgXK9yLFb+31i8cEvyZqarjwHGAJItVNb+Z93+5ci9WuBcr3IsV7sWKJItr/dohT+k8AeydON4zPnfRNUl2Aq8FnlrrUJKk2RsS/NPAviTXJrkCOAwsrFqzAPzl+PJfAN+qqprdmJKk9Zr6lM74Ofk7gZPADuCzVXUmyT3AYlUtAP8KfCHJEvBzRj8Upjm+jrm3G/dihXuxwr1Y4V6sWPNexAfiktSD77SVpCYMviQ1seHB92MZVgzYiw8kOZvk0STfTPLGrZhzM0zbi4l170hSSbbtn+QN2Ysk7xx/b5xJ8sXNnnGzDPg/8oYkDyR5ZPz/5LatmHOjJflskicv9V6ljHxyvE+PJrlx0A1X1Yb9Y/Qi738AvwNcAXwP2L9qzV8BnxpfPgx8eSNn2qp/A/fiT4HfHF9+X+e9GK+7CngQOAXMb/XcW/h9sQ94BPit8fHrtnruLdyL48D7xpf3Az/a6rk3aC/+BLgR+P4lrr8N+AYQ4GbgoSG3u9GP8P1YhhVT96KqHqiqZ8eHpxi952E7GvJ9AfAxRp/L9IvNHG6TDdmL9wLHquppgKp6cpNn3CxD9qKA14wvvxb4ySbOt2mq6kFGf/F4KYeAz9fIKeDqJK+fdrsbHfyLfSzD7kutqarngRc+lmG7GbIXk+5g9BN8O5q6F+NfUfdW1dc3c7AtMOT74jrguiTfSXIqyYFNm25zDdmLjwK3J7kAnADevzmjXXZeak+ATf5oBQ2T5HZgHnjrVs+yFZK8AvgE8O4tHuVysZPR0zq3MPqt78Ekv19V/7WVQ22RI8Dnquofk/wxo/f/vLmq/merB3s52OhH+H4sw4ohe0GStwMfBg5W1S83abbNNm0vrgLeDHw7yY8YPUe5sE1fuB3yfXEBWKiqX1XVD4EfMPoBsN0M2Ys7gPsBquq7wKsYfbBaN4N6stpGB9+PZVgxdS+S3AB8mlHst+vztDBlL6rqmaraVVXXVNU1jF7POFhVa/7QqMvYkP8jX2P06J4kuxg9xXNuE2fcLEP24sfA2wCSvIlR8Jc3dcrLwwLwrvFf69wMPFNVP532RRv6lE5t3McyvOwM3It7gVcDXxm/bv3jqjq4ZUNvkIF70cLAvTgJ/HmSs8B/Ax+qqm33W/DAvfgg8Jkkf8voBdx3b8cHiEm+xOiH/K7x6xUfAV4JUFWfYvT6xW3AEvAs8J5Bt7sN90qSdBG+01aSmjD4ktSEwZekJgy+JDVh8CWpCYMvSU0YfElq4n8BzPZculjwdYoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()    # creamos un objeto Figure\n",
    "ax = plt.subplot()    # cremos un objeto Axes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e63b2fb9",
   "metadata": {},
   "source": [
    "O, en una sola línea:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1d1bc134",
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(6, 4))  # aquí damos el tamaño de la figura"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56a7c07b",
   "metadata": {},
   "source": [
    "## Explícito o implícito"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d40b7da",
   "metadata": {},
   "source": [
    "Hay dos formas diferentes de pintar una misma gráfica:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "1099107f",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0, 2, 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "f52e95e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f7f45b4ecb0>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Método implícito\n",
    "\n",
    "plt.figure(figsize=(5, 3), layout='constrained')\n",
    "\n",
    "plt.plot(x, x, label='lineal')  # Plot some data on the (implicit) axes.\n",
    "plt.plot(x, x**2, label='cuadrático')  # etc.\n",
    "plt.plot(x, x**3, label='cúbico')\n",
    "\n",
    "plt.xlabel('etiqueta eje X')\n",
    "plt.ylabel('etiqueta eje Y')\n",
    "plt.title(\"Gráfica simple\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "56f746d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f7f459d9ed0>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Método explícito\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(5, 3), layout='constrained')\n",
    "\n",
    "ax.plot(x, x, label='lineal')  # Plot some data on the axes.\n",
    "ax.plot(x, x**2, label='cuadrático')  # Plot more data on the axes...\n",
    "ax.plot(x, x**3, label='cúbico')  # ... and some more.\n",
    "\n",
    "ax.set_xlabel('etiqueta eje X')  # Add an x-label to the axes.\n",
    "ax.set_ylabel('etiqueta eje Y')  # Add a y-label to the axes.\n",
    "ax.set_title(\"Gráfica simple\")  # Add a title to the axes.\n",
    "ax.legend()  # Add a legend."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe02217c",
   "metadata": {},
   "source": [
    "El primer ejemplo, el método implícito, parece más claro y sencillo. Lo que está ocurriendo es que todos los métodos del objeto ``Axes`` están disponibles directamente desde ``pyplot``.\n",
    "Así pues cuando ejecutamos ``plt.plot()``, ``pyplot`` llama internamente a ``ax.plot()``. Esto da un nivel extra de sencillez pero reduce en parte la versatilidad.  \n",
    "En cambio en el segundo ejemplo se usa el método explícito, llamando directamente a un  objeto ``Axes``.\n",
    "\n",
    "Conclusión: para ejemplos sencillos y rápidos podemos recurrir a la versión \"abreviada\" o implícita, más fácil de usar. Pero cuando queramos realizar gráficas más elaboradas es recomendable utilizar la versión explícita, que nos da más control sobre los diferentes elementos individuales.\n",
    "\n",
    "Cuando copiemos código de los ejemplos nos encontraremos en este segundo caso. Con objeto de poder entender y reutilizar dicho código, en el resto de este tutorial usaremos la forma explícita."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67cf4b27",
   "metadata": {},
   "source": [
    "## Estilos"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20fc92bb",
   "metadata": {},
   "source": [
    "Usaremos ``plot`` para dibujar una línea. Podemos modificar el estilo cambiando el estilo de línea, su grosor o su color, por ejemplo. Esto se puede hacer con argumentos de la función plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "bf3ed0c2",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fd3700f2020>]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0, 10, 100)\n",
    "fig, ax = plt.subplots(figsize=(5, 3))\n",
    "ax.plot(x, np.sin(x), linestyle='--', linewidth=4, color='red')\n",
    "# Esto es idéntico, usando RGB:\n",
    "#ax.plot(x, np.sin(x), linestyle='--', linewidth=4, color=(1.0, 0.0, 0.0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "542946ca",
   "metadata": {},
   "source": [
    "Hay mucha más información sobre colores en https://matplotlib.org/stable/gallery/color/index.html y https://matplotlib.org/stable/tutorials/colors/colors.html"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd67338c",
   "metadata": {},
   "source": [
    "Además de líneas, hay otros muchos gráficos que se pueden utilizar en matplotlib.\n",
    "Por ejemplo, aquí representamos algunos datos de estaciones extraídos de la web de ONAMET (Oficina Nacional Meteorológica de la República Dominicana) por medio de marcadores (markers) en forma de rombos, gracias al método ``ax.scatter``:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4dfb42e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NÚM.</th>\n",
       "      <th>ESTACIÓN</th>\n",
       "      <th>PROVINCIA</th>\n",
       "      <th>LOCALIDAD</th>\n",
       "      <th>TIPO</th>\n",
       "      <th>T. MÁX. (°C)</th>\n",
       "      <th>T. MÍN. (°C)</th>\n",
       "      <th>LLUVIA (mm)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>ARPT. DEL CIBAO</td>\n",
       "      <td>SANTIAGO</td>\n",
       "      <td>ONAMET</td>\n",
       "      <td>EMCO</td>\n",
       "      <td>35.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6.0</td>\n",
       "      <td>ARPT. EL CATEY</td>\n",
       "      <td>SAMANÁ</td>\n",
       "      <td>ONAMET</td>\n",
       "      <td>EMCO</td>\n",
       "      <td>33.0</td>\n",
       "      <td>24.6</td>\n",
       "      <td>19.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7.0</td>\n",
       "      <td>ENRIQUILLO</td>\n",
       "      <td>BARAHONA</td>\n",
       "      <td>MINISTERIO DE AGRICULTURA</td>\n",
       "      <td>EMCV</td>\n",
       "      <td>31.5</td>\n",
       "      <td>25.0</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8.0</td>\n",
       "      <td>CABRERA</td>\n",
       "      <td>MARÍA TRINIDAD SÁNCHEZ</td>\n",
       "      <td>ESCUELA ARÍSTIDES FIALLO CABRAL</td>\n",
       "      <td>EMCO</td>\n",
       "      <td>32.5</td>\n",
       "      <td>25.0</td>\n",
       "      <td>14.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9.0</td>\n",
       "      <td>VILLA RIVA</td>\n",
       "      <td>DUARTE</td>\n",
       "      <td>HOSP. MPAL. ALICIA DE LEGENDRE</td>\n",
       "      <td>EMCO</td>\n",
       "      <td>32.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10.0</td>\n",
       "      <td>LA VEGA</td>\n",
       "      <td>LA VEGA</td>\n",
       "      <td>IATESA</td>\n",
       "      <td>EMCO</td>\n",
       "      <td>30.5</td>\n",
       "      <td>24.0</td>\n",
       "      <td>10.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   NÚM.         ESTACIÓN               PROVINCIA  \\\n",
       "4   5.0  ARPT. DEL CIBAO                SANTIAGO   \n",
       "5   6.0   ARPT. EL CATEY                  SAMANÁ   \n",
       "6   7.0       ENRIQUILLO                BARAHONA   \n",
       "7   8.0          CABRERA  MARÍA TRINIDAD SÁNCHEZ   \n",
       "8   9.0       VILLA RIVA                  DUARTE   \n",
       "9  10.0          LA VEGA                 LA VEGA   \n",
       "\n",
       "                         LOCALIDAD  TIPO T. MÁX. (°C) T. MÍN. (°C)  \\\n",
       "4                           ONAMET  EMCO         35.0         23.0   \n",
       "5                           ONAMET  EMCO         33.0         24.6   \n",
       "6        MINISTERIO DE AGRICULTURA  EMCV         31.5         25.0   \n",
       "7  ESCUELA ARÍSTIDES FIALLO CABRAL  EMCO         32.5         25.0   \n",
       "8   HOSP. MPAL. ALICIA DE LEGENDRE  EMCO         32.0         23.0   \n",
       "9                           IATESA  EMCO         30.5         24.0   \n",
       "\n",
       "   LLUVIA (mm)  \n",
       "4         20.0  \n",
       "5         19.3  \n",
       "6         17.3  \n",
       "7         14.3  \n",
       "8         11.9  \n",
       "9         10.7  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"../07_pandas/onamet_20230824.csv\", sep=\",\", skiprows=4, encoding = \"utf-8\")\n",
    "df =df[4:10] # Nos quedamos con seis filas para simplificar\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "03809d00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.scatter(df[\"ESTACIÓN\"], df[\"LLUVIA (mm)\"], marker=\"D\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c179a192",
   "metadata": {},
   "source": [
    "O quizás mejor, usando un diagrama de barras (``ax.bar``):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e56aa770",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.bar(df[\"ESTACIÓN\"], df[\"LLUVIA (mm)\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b785199",
   "metadata": {},
   "source": [
    "Se puede modificar también el estilo de dibujo. Por ejemplo para usar el estilo seaborn:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ddec84f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f70508d99f0>]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use(['seaborn'])\n",
    "x = np.linspace(0, 10, 100)\n",
    "fig, ax = plt.subplots(figsize=(5, 3))\n",
    "ax.plot(x, np.sin(x), linestyle='--', linewidth=4, color='red')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b0ec941",
   "metadata": {},
   "source": [
    "seaborn tiene además su propia librería: https://seaborn.pydata.org/"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cb15c64",
   "metadata": {},
   "source": [
    "## Límites"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04327e93",
   "metadata": {},
   "source": [
    "Matplotlib se encarga de por sí solo de establecer los límites de las gráficas. Sin embargo en muchas ocasiones podemos querer controlar este aspecto. Lo haremos mediante los métodos ``ax.set_ylim`` y ``ax.set_ylim``:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f168ca67",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-2.0, 2.0)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0, 10, 100)\n",
    "fig, ax = plt.subplots(figsize=(5, 3))\n",
    "ax.plot(x, np.sin(x))\n",
    "ax.set_xlim(0, 6)\n",
    "ax.set_ylim(-2, 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c8578fb",
   "metadata": {},
   "source": [
    "Podemos establecer únicamente el límite inferior o superior y dejar que matplotlib se encargue del resto:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e2392222",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.0993384025373631, 2.0)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 3))\n",
    "ax.plot(x, np.sin(x))\n",
    "ax.set_xlim(right=6)\n",
    "ax.set_ylim(top=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20ba0934",
   "metadata": {},
   "source": [
    "## Marcas (ticks) y etiquetas"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73ee9acd",
   "metadata": {},
   "source": [
    "Matplotlib nos da también métodos para dar título de la gráfica (``ax.set_title``), a las etiquetas de los ejes (``ax.set_xlabel`` y ``ax.set_ylabel``), y a la frecuencia de las marcas y sus etiquetas (``ax.xticks`` y ``ax.yticks``). \n",
    "Alternativamente se puede usar el objeto axis, con la función ``ax.axis.set_ticks``.\n",
    "\n",
    "Si los incluímos en el diagrama de barras del apartado anterior:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b55ee484",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.bar(df[\"ESTACIÓN\"], df[\"LLUVIA (mm)\"])\n",
    "ax.set_ylabel('Lluvia (mm)')\n",
    "ax.set_xlabel('Estación')\n",
    "ax.set_xticks(range(0, len(df[\"ESTACIÓN\"])), df[\"ESTACIÓN\"], rotation=45, ha=\"right\") \n",
    "# o también:\n",
    "# ax.xaxis.set_ticks(range(0, len(df[\"ESTACIÓN\"])), df[\"ESTACIÓN\"], rotation=45, ha=\"right\") \n",
    "ax.set_title(\"Lluvia para el día 24 de agosto de 2023\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "346a45fa",
   "metadata": {},
   "source": [
    "En el caso de las etiquetas de las marcas (los \"ticks\") observar que el primer argumento indica la posición de cada marca, y el segundo el texto de cada etiqueta:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a9845f4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 2, 3, 4, 5]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(range(0, len(df[\"ESTACIÓN\"])))  #  Las barras están en las posiciones 0 a 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d335f008",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4    ARPT. DEL CIBAO\n",
       "5     ARPT. EL CATEY\n",
       "6         ENRIQUILLO\n",
       "7            CABRERA\n",
       "8         VILLA RIVA\n",
       "9            LA VEGA\n",
       "Name: ESTACIÓN, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"ESTACIÓN\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "006024ab",
   "metadata": {},
   "source": [
    "Además hemos girado las etiquetas para evitar que se pisen unas a otras (argumento opcional rotation), y las hemos desplazado a la derecha (argumento opcional ha) para que estén bien situadas bajo su marca."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "268ce7bc",
   "metadata": {},
   "source": [
    "Hay una gran variedad de formatos de ticks posibles (por ejemplo se pueden dibujar ticks mayores y menores).  \n",
    "En la documentación se puede encontrar una explicación más detallada (por ejemplo, para usar fechas como etiquetas se puede consultar https://matplotlib.org/stable/gallery/text_labels_and_annotations/date.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acacc581",
   "metadata": {},
   "source": [
    "### Expresiones matemáticas"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "893feb48",
   "metadata": {},
   "source": [
    "Matplotlib puede utilizar el lenguaje de markup TeX para escribir expresiones matemáticas (en el título, una etiqueta, la leyenda, etc).\n",
    "Para ello basta con poner la expresión en código TeX dentro de signos de dólar($)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1d6aec7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Por ejemplo, la expresión de TeX $e^{i\\pi}+1=0$ queda así:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ccc4bbc",
   "metadata": {},
   "source": [
    "$\\Large e^{i\\pi}+1=0$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f989556",
   "metadata": {},
   "source": [
    "Veamos un caso práctico en el que tomamos datos de una semana de la estación de Atlacomulco de la web del Servicio Meteorológico Nacional de México:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b726a20d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"Estacion_ATLACOMULCO_1_semana.csv\", parse_dates=[0], skiprows=9,\n",
    "                     sep=\",\", encoding = \"ISO-8859-1\", index_col=[0])\n",
    "df = df.sort_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "147e10a2",
   "metadata": {},
   "source": [
    "Si queremos representar la radiación, que tiene como unidad watios por metro cuadrado, podemos incluir el símbolo del cuadrado fácilmente con TeX:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a7444aee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.dates as mdates\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(12,4))\n",
    "ax.plot(df.index, df['Radiación Solar (W/m2)'])\n",
    "ax.set_ylabel('Radiación ($W/m^2$)') # Con los $, escribe el cuadrado correctamente\n",
    "ax.set_xlabel('t')\n",
    "myFmt = mdates.DateFormatter('%m-%d %H:%M')  # Un ejemplo de formateo de fechas para los xticks\n",
    "ax.xaxis.set_major_formatter(myFmt)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d3f3ace",
   "metadata": {},
   "source": [
    "## Leyenda"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b000f417",
   "metadata": {},
   "source": [
    "El método ``ax.legend`` nos da la opción de incluir una leyenda. Hay distintos argumentos para modificar el contenido de la leyenda y su posición en el gráfico (poniéndola incluso fuera de él).  \n",
    "Usando el ejemplo anterior:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1200d0e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12,4))\n",
    "ax.plot(df.index, df['Rapidez de viento (km/h)'], label='Rapidez de viento')\n",
    "ax.plot(df.index, df['Temperatura del Aire (°C)'], label='Temperatura')\n",
    "ax.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af73631f",
   "metadata": {},
   "source": [
    "## Anotaciones"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2600e29f",
   "metadata": {},
   "source": [
    "Para añadir una anotación sobre la propia gráfica se puede utilizar ``ax.annotate``:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "33010d7f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_81964/1569395812.py:8: RuntimeWarning: invalid value encountered in sqrt\n",
      "  eq1 = ((x/7)**2*sqrt(abs(abs(x)-3)/(abs(x)-3))+(y/3)**2*sqrt(abs(y+3/7*sqrt(33))/(y+3/7*sqrt(33)))-1)\n",
      "/tmp/ipykernel_81964/1569395812.py:9: RuntimeWarning: invalid value encountered in sqrt\n",
      "  eq2 = (abs(x/2)-((3*sqrt(33)-7)/112)*x**2-3+sqrt(1-(abs(abs(x)-2)-1)**2)-y)\n",
      "/tmp/ipykernel_81964/1569395812.py:10: RuntimeWarning: invalid value encountered in sqrt\n",
      "  eq3 = (9*sqrt(abs((abs(x)-1)*(abs(x)-.75))/((1-abs(x))*(abs(x)-.75)))-8*abs(x)-y)\n",
      "/tmp/ipykernel_81964/1569395812.py:11: RuntimeWarning: invalid value encountered in sqrt\n",
      "  eq4 = (3*abs(x)+.75*sqrt(abs((abs(x)-.75)*(abs(x)-.5))/((.75-abs(x))*(abs(x)-.5)))-y)\n",
      "/tmp/ipykernel_81964/1569395812.py:12: RuntimeWarning: invalid value encountered in sqrt\n",
      "  eq5 = (2.25*sqrt(abs((x-.5)*(x+.5))/((.5-x)*(.5+x)))-y)\n",
      "/tmp/ipykernel_81964/1569395812.py:13: RuntimeWarning: invalid value encountered in sqrt\n",
      "  eq6 = (6*sqrt(10)/7+(1.5-.5*abs(x))*sqrt(abs(abs(x)-1)/(abs(x)-1))-(6*sqrt(10)/14)*sqrt(4-(abs(x)-1)**2)-y)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from numpy import sqrt, meshgrid, arange\n",
    "\n",
    "xs = arange(-7.25, 7.25, 0.01)\n",
    "ys = arange(-5, 5, 0.01)\n",
    "x, y = meshgrid(xs, ys)\n",
    "\n",
    "eq1 = ((x/7)**2*sqrt(abs(abs(x)-3)/(abs(x)-3))+(y/3)**2*sqrt(abs(y+3/7*sqrt(33))/(y+3/7*sqrt(33)))-1)\n",
    "eq2 = (abs(x/2)-((3*sqrt(33)-7)/112)*x**2-3+sqrt(1-(abs(abs(x)-2)-1)**2)-y)\n",
    "eq3 = (9*sqrt(abs((abs(x)-1)*(abs(x)-.75))/((1-abs(x))*(abs(x)-.75)))-8*abs(x)-y)\n",
    "eq4 = (3*abs(x)+.75*sqrt(abs((abs(x)-.75)*(abs(x)-.5))/((.75-abs(x))*(abs(x)-.5)))-y)\n",
    "eq5 = (2.25*sqrt(abs((x-.5)*(x+.5))/((.5-x)*(.5+x)))-y)\n",
    "eq6 = (6*sqrt(10)/7+(1.5-.5*abs(x))*sqrt(abs(abs(x)-1)/(abs(x)-1))-(6*sqrt(10)/14)*sqrt(4-(abs(x)-1)**2)-y)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(5, 4))\n",
    "\n",
    "for f in [eq1,eq2,eq3,eq4,eq5,eq6]:\n",
    "    ax.contour(x, y, f, [0])\n",
    "\n",
    "ax.annotate('llámenle si tienen\\n dificultades', xy=(1.1, 2.5), xytext=(2, 3.8),\n",
    "            arrowprops=dict(facecolor='black'), fontsize=10)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b565f508",
   "metadata": {},
   "source": [
    "## Compartiendo ejes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "057bb93a",
   "metadata": {},
   "source": [
    "Volviendo al ejemplo de la estación de Atlacomulco, no parece adecuado representar la temperatura y la rapidez del viento en el mismo eje, dado que tienen escalas distintas.\n",
    "\n",
    "Podemos construir una gráfica con dos ``Axes`` diferentes, uno para cada parámetro, pero que compartan el eje X. Para ello usaremos ``ax.twinx``:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "51932885",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots(figsize=(12,4))\n",
    "ax1.plot(df.index, df['Rapidez de viento (km/h)'], color=(0,0,1))\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(df.index, df['Temperatura del Aire (°C)'], color=(1,0,0))\n",
    "ax1.set_ylabel(\"Viento (km/h)\")\n",
    "ax2.set_ylabel(\"Temperatura (°C)\")\n",
    "ax1.set_xlabel(\"t\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e20f8fc",
   "metadata": {},
   "source": [
    "**Ejercicio:** Utilizar el fichero de Buenos Aires (buenos_aires_20230813.txt) para representar en una misma gráfica la temperatura y la humedad relativa, compartiendo el eje X (eje de tiempo). Incluir una leyenda con los dos parámetros."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4c185c17",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"../07_pandas/buenos_aires_20230813.txt\", parse_dates=[['Fecha', 'Hora']],\n",
    "                     sep=\",\", encoding = \"ISO-8859-1\", usecols=[0,1,3,5], index_col=[0])\n",
    "df = df.sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a7568ef3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots()\n",
    "lns1 = ax1.plot(df.index, df[\"T (°C)\"], color=\"red\", label=\"Temperatura\")\n",
    "ax2 = ax1.twinx() # utilizamos el mismo eje x para las 2 gráficas\n",
    "lns2 = ax2.plot(df.index, df[\"HR (%)\"], color=\"blue\", label=\"Humedad relativa\")\n",
    "ax1.set_xlabel('t (hora)')\n",
    "ax1.set_ylabel(\"T (°C)\")\n",
    "ax2.set_ylabel(\"HR (%)\")\n",
    "\n",
    "ax1.set_xticks(ticks=df.index, labels=df.index.hour, fontsize=8)\n",
    "\n",
    "labels = [l.get_label() for l in lns1+lns2]\n",
    "ax1.legend(lns1+lns2, labels, loc='center right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0307cca",
   "metadata": {},
   "source": [
    "## Subplots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e4ba1a0",
   "metadata": {},
   "source": [
    "Cada ``Figure`` puede contener varios ``Axes``, se conocen como subaxes o subplots.\n",
    "\n",
    "Cuando añadimos una gráfica a la figura podemos especificar cuantas filas y columnas queremos, y que posición ocupa la gráfica actual, con los argumentos de subplot(ncol, nrow, n)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e90156df",
   "metadata": {},
   "source": [
    "Hay varias maneras de añadir y modificar gráficas en una figura. Veamos las más comunes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d0f21b58",
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, axes = plt.subplots(1, 3)   # devuelve una Figure y una 3-tupla de Axes\n",
    "    ...\n",
    "\n",
    "ax = plt.subplot(2, 2, 1)        # divide la figura en 4 partes y devuelve el primer axes\n",
    "\n",
    "ax = fig.add_subplot(2, 2, 1)    # equivalente al anterior\n",
    "\n",
    "ax = fig.add_axes([.6, .6, .2, .2]) # añade un Axe con la geometria [left, bottom, width, height]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "271493d7",
   "metadata": {},
   "source": [
    "Veamos un ejemplo de dibujo de subplots con el fichero de Atlacomulco:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "b8ae0af4",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"Estacion_ATLACOMULCO_1_semana.csv\", parse_dates=[0], skiprows=9,\n",
    "                     sep=\",\", encoding = \"ISO-8859-1\", index_col=[0])\n",
    "df = df.sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "c03d6034",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2, figsize=(10,8))   # devuelve una Figure y un array de Axes\n",
    "parameter = [[\"Rapidez de viento (km/h)\",\"Temperatura del Aire (°C)\"],\n",
    "             [\"Humedad relativa (%)\", \"Radiación Solar (W/m2)\"]]\n",
    "parcolors = [[\"green\", \"orange\"], [\"blue\", \"red\"]]\n",
    "\n",
    "for i in [0,1]:\n",
    "    for j in [0,1]:\n",
    "        axes[i,j].plot(df[parameter[i][j]], color=parcolors[i][j])\n",
    "        axes[i,j].set_title(parameter[i][j])\n",
    "        axes[i,j].set_xticks([])  # quito las etiquetas del eje X para que no molesten"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b3bf763",
   "metadata": {},
   "source": [
    "Otras instrucciones útiles: ``plt.subplots_adjust`` nos permite jugar con el espaciado entre gráficas. \n",
    "Si tenemos problemas con el ajuste de espacios podemos usar ``plt.tight_layout``, que realiza un auto ajuste."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73814b09",
   "metadata": {},
   "source": [
    "## Guardar en fichero"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0981d1e",
   "metadata": {},
   "source": [
    "Podemos guardar la figura por medio de ``fig.savefig``, indicando el nombre y la extensión:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3ee41fba",
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.savefig('atlacomulco.png')\n",
    "fig.savefig('atlacomulco.pdf')\n",
    "fig.savefig('atlacomulco.ps')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b78d0dd",
   "metadata": {},
   "source": [
    "## Mapas de color"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60b30f9d",
   "metadata": {},
   "source": [
    "Es posible que a veces queramos una gráfica con una tercera dimensión representada por colores diferentes en un mapa de colores. Matplotlib dispone de varias funciones (``ax.pcolormesh``, ``ax.contourf``, ``ax.imshow``) para conseguir esto."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1fff3fa",
   "metadata": {},
   "source": [
    "Por ejemplo, supongamos que queremos representar la radiación solar dependiendo del día del mes (en el eje Y) y de la hora del día (en el eje X), de forma que cada color represente una diferente insolación, desde una radiación nula en color azul oscuro a una radiación máxima en color amarillo.\n",
    "Este código nos da la respuesta:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bb8205b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "parameter = 'Radiación Solar (W/m2)'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7ce68eb6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"Estacion_ATLACOMULCO_1_semana.csv\", parse_dates=[0], skiprows=9,\n",
    "                     sep=\",\", encoding = \"ISO-8859-1\", index_col=[0])\n",
    "df = df.sort_index()\n",
    "\n",
    "df = df[[parameter]]     # Nos quedamos con el parametro elegido\n",
    "df['dia'] = df.index.date\n",
    "df['hora'] = df.index.hour\n",
    "df_hour = df[df.index.minute==0]  # Eliminamos las observaciones que no son a la hora en punto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "642d21c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>hora</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
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       "      <th>19</th>\n",
       "      <th>20</th>\n",
       "      <th>21</th>\n",
       "      <th>22</th>\n",
       "      <th>23</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dia</th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-08-24</th>\n",
       "      <td>NaN</td>\n",
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       "      <td>612.0</td>\n",
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       "      <td>56.0</td>\n",
       "      <td>6.0</td>\n",
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       "      <th>2023-08-25</th>\n",
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       "      <td>1132.0</td>\n",
       "      <td>321.0</td>\n",
       "      <td>218.0</td>\n",
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       "      <td>75.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2023-08-26</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>310.0</td>\n",
       "      <td>355.0</td>\n",
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       "      <td>1102.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>165.0</td>\n",
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       "      <td>45.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1112.0</td>\n",
       "      <td>777.0</td>\n",
       "      <td>181.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>256.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-28</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>522.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "hora         0    1    2    3    4    5    6     7      8      9   ...  \\\n",
       "dia                                                                ...   \n",
       "2023-08-24  NaN  NaN  NaN  NaN  NaN  NaN  NaN   NaN    NaN    NaN  ...   \n",
       "2023-08-25  0.0  0.0  0.0  0.0  0.0  0.0  0.0  57.0  331.0  596.0  ...   \n",
       "2023-08-26  0.0  0.0  0.0  0.0  0.0  0.0  0.0  72.0  310.0  355.0  ...   \n",
       "2023-08-27  0.0  0.0  0.0  0.0  0.0  0.0  0.0  56.0  159.0  173.0  ...   \n",
       "2023-08-28  0.0  0.0  0.0  0.0  0.0  0.0  0.0  49.0  167.0  522.0  ...   \n",
       "\n",
       "hora            14     15     16     17     18   19   20   21   22   23  \n",
       "dia                                                                      \n",
       "2023-08-24   612.0    NaN  793.0  210.0   56.0  6.0  0.0  0.0  0.0  0.0  \n",
       "2023-08-25  1132.0  321.0  218.0  129.0   75.0  3.0  0.0  0.0  0.0  0.0  \n",
       "2023-08-26  1102.0   99.0  165.0  142.0   45.0  0.0  0.0  0.0  0.0  0.0  \n",
       "2023-08-27  1112.0  777.0  181.0   74.0  256.0  5.0  0.0  0.0  0.0  0.0  \n",
       "2023-08-28     NaN    NaN    NaN    NaN    NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rad = pd.pivot_table(df_hour, values='Radiación Solar (W/m2)', \n",
    "                        index='dia', columns='hora')\n",
    "df_rad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b6ba5698",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f20dfd45150>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib as mpl\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(12,3))\n",
    "pc = ax.imshow(df_rad, cmap='plasma', aspect='auto',\n",
    "               norm=mpl.colors.Normalize(vmin=0, vmax=1000))\n",
    "ax.set_yticks(range(0, len(df_rad.index)),df_rad.index)\n",
    "ax.set_xlabel(\"hora\")\n",
    "ax.set_ylabel(\"día\")\n",
    "ax.set_title(\"Radiación Solar en Atlacomulco ($W/m^2$)\")\n",
    "fig.colorbar(pc)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "64618399",
   "metadata": {},
   "source": [
    "**Warning:** notar que en este caso hemos cometido un error, al tomar la observación de la hora en punto como representativa de toda la hora."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e75bfc0b",
   "metadata": {},
   "source": [
    "Dado que tenemos observaciones cada 10 minutos, podemos afinar incluso más:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "40467327",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.dates as mdates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "412442c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['minuto'] = df.index.minute\n",
    "df_rad_min = pd.pivot_table(df, values='Radiación Solar (W/m2)', \n",
    "               index='dia', columns=['hora', 'minuto'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "96b11b8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "xtickvalues = df_rad_min.columns.get_level_values(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "1d1cbbdd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f20dc5e4700>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12,3))\n",
    "pc = ax.imshow(df_rad_min, cmap='plasma', aspect='auto',\n",
    "               norm=mpl.colors.Normalize(vmin=0, vmax=1000))\n",
    "xFmt = mdates.DateFormatter('%H')\n",
    "yFmt = mdates.DateFormatter('%Y-%m-%d')\n",
    "ax.xaxis.set_major_formatter(xFmt)\n",
    "ax.yaxis.set_major_formatter(yFmt)\n",
    "xtickvalues = df_rad_min.columns.get_level_values(0) # Indice superior (horas) en el multiindice \n",
    "ax.set_xticks(range(0, len(xtickvalues),6),xtickvalues[range(0, len(xtickvalues),6)])\n",
    "ax.set_yticks(range(0, len(df_rad_min.index)),df_rad_min.index)\n",
    "ax.set_xlabel(\"hora\")\n",
    "ax.set_ylabel(\"día\")\n",
    "ax.set_title(\"Radiación Solar en Atlacomulco ($W/m^2$)\")\n",
    "fig.colorbar(pc)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "362a6987",
   "metadata": {},
   "source": [
    "## Consejos útiles"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84eb9f7f",
   "metadata": {},
   "source": [
    "### ¿Qué formato de salida debo escoger?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "91e496c5",
   "metadata": {},
   "source": [
    "Como diría un buen gallego, depende. Depende del gráfico que estemos generando, pero en general para empezar escoged PNG. Una breve explicación sobre formatos que puede aclarar algunas ideas:\n",
    "\n",
    "* El formato GIF está limitado a 256 colores y es un formato de compresión sin pérdida de información, una elección habitual para su uso en la Web. GIF es una buena opción para guardar dibujos de líneas, texto o iconos con un tamaño de fichero pequeño.\n",
    "* El formato PNG es también un formato de compresión sin pérdida de información, una elección habitual para su uso en la Web. PNG es una buena opción para guardar dibujos de líneas, texto o iconos con un tamaño de fichero pequeño.\n",
    "* El formato JPG es un formato de compresión con pérdida de información. Esto lo hace útil para almacenar fotografías con un tamaño menor que un BMP. JPG es una opción habitual en la Web porque está comprimido. Para guardar dibujos de líneas, texto, e iconos con un tamaño de fichero menor GIF o PNG son mejores opciones porque no tienen pérdidas.\n",
    "\n",
    "JPEGs son para fotografías e imágenes realistas. PNGs son para dibujos con líneas, imágenes con una gran cantidad de texto e imágenes con pocos colores. GIFs no sirven en general."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "152bd3b4",
   "metadata": {},
   "source": [
    "### Producción masiva: acelerando Matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24607f5b",
   "metadata": {},
   "source": [
    "Este consejo va más enfocado al dibujo de mapas, donde la generación de gráficos puede llevar bastante tiempo. Si tenemos que crear una gran cantidad de gráficos o mapas veremos que los procesos llevan bastante tiempo. Si dichos gráficos tienen características en común, por ejemplo el mapa de fondo (proyección, líneas de costa, colores, extensión) es adecuado reutilizar dicho trabajo para los gráficos siguientes.\n",
    "\n",
    "Una opción es limpiar parte de la figura que hemos realizado en lugar de construirla de nuevo. De este modo únicamente cambiamos los datos sobre el gráfico de fondo ya creado.\n",
    "\n",
    "Cabe también pensar en la serialización de objetos a través del módulo pickle, para ser reutilizados posteriormente.\n",
    "\n",
    "En general, no solo para la generación de gráficos, lo primero es hacer que nuestro programa funcione, lo segundo es optimizarlo."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "769f4a0f",
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   "source": [
    "### Un último consejo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc711d06",
   "metadata": {},
   "source": [
    "Matplotlib está muy bien, pero no nos obsesionemos  ;-)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d89f8d36",
   "metadata": {},
   "source": [
    "![](_images/523_decline.png)"
   ]
  }
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