{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizaciones de datos con Python"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Esta notebook fue creada originalmente como un blog post por [Raúl E. López Briega](http://relopezbriega.com.ar/) en [Matemáticas, análisis de datos y python](http://relopezbriega.github.io). El contenido esta bajo la licencia BSD.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img alt=\"Visualizaciones de datos con Python\" title=\"Visualizaciones de datos con Python\" src=\"http://relopezbriega.github.io/images/DataViz.png\" high=400px width=600px>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introducción\n",
    "\n",
    "Las visualizaciones son una herramienta fundamental para entender y compartir ideas sobre los datos. La visualización correcta puede ayudar a expresar una idea central, o abrir un espacio para una más profunda investigación; con ella se puede conseguir que todo el mundo hable sobre un [conjunto de datos](https://es.wikipedia.org/wiki/Conjunto_de_datos), o compartir una visión sobre lo que los datos nos quieren decir.\n",
    "\n",
    "Una buena visualización puede dar a quien la observa un sentido rico y amplio de un [conjunto de datos](https://es.wikipedia.org/wiki/Conjunto_de_datos). Puede comunicar los datos de manera precisa a la vez que expone los lugares en dónde se necesita más información o dónde una hipótesis no se sostiene. Por otra parte, la visualización nos proporciona un lienzo para aplicar nuestras propias ideas, experiencias y conocimientos cuando observamos y analizamos datos, permitiendo realizar múltiples interpretaciones. Si como dice el dicho *\"una imagen vale más que mil palabras\"*, un gráfico interactivo bien elegido entonces podría valer cientos de [pruebas estadísticas](https://es.wikipedia.org/wiki/Contraste_de_hip%C3%B3tesis).\n",
    "\n",
    "## Librerías para visualizar datos en Python\n",
    "\n",
    "Como bien sabemos, la comunidad de [Python](http://python.org/) es muy grande, por lo tanto vamos a poder encontrar un gran número de librerías para visualizar datos. Al tener tanta variedad de opciones, a veces se hace realmente difícil determinar cuando utilizar cada una de ellas. En este artículo yo voy a presentar solo cuatro que creo que cubren un gran abanico de casos:\n",
    "\n",
    "* **[Matplotlib](http://matplotlib.org/gallery.html)**: Que es la más antigua y se convirtió en la librería por defecto para visualizaciones de datos; muchas otras están basadas en ella. Es extremadamente potente, pero con ese poder viene aparejada la complejidad. Se puede hacer prácticamente de todo con [Matplotlib](http://matplotlib.org/gallery.html) pero no siempre es tan fácil de averiguar como hacerlo. Los que siguen el [blog](http://relopezbriega.github.io/) me habrán visto utilizarla en varios artículos.\n",
    "\n",
    "\n",
    "* **[Bokeh](http://bokeh.pydata.org/en/latest/)**: Una de las más jóvenes librerías de visualizaciones, pero no por ello menos potente. [Bokeh](http://bokeh.pydata.org/en/latest/) es una librería para visualizaciones interactivas diseñada para funcionar en los navegadores web modernos. Su objetivo es proporcionar una construcción elegante y concisa de gráficos modernos al estilo de [D3.js](https://d3js.org/), y para ampliar esta capacidad con la interactividad y buen rendimiento sobre grandes volúmenes de datos. [Bokeh](http://bokeh.pydata.org/en/latest/) puede ayudar a cualquier persona a crear en forma rápida y sencilla gráficos interactivos, *dashboards* y aplicaciones de datos. Puede crear tanto gráficos estáticos como gráficos interactivos en el servidor de [Bokeh](http://bokeh.pydata.org/en/latest/docs/user_guide/server.html).\n",
    "\n",
    "\n",
    "* **[Seaborn](https://stanford.edu/~mwaskom/software/seaborn/)**: Si de gráficos estadísticos se trata, [Seaborn](https://stanford.edu/~mwaskom/software/seaborn/) es la librería que deberíamos utilizar, con ella podemos crear gráficos estadísticos informativos y atractivos de forma muy sencilla. Es una de las tantas librerías que se basan en [Matplotlib](http://matplotlib.org/gallery.html) pero nos ofrece varias características interesantes tales como temas, paletas de colores, funciones y herramientas para visualizar [distribuciones](http://relopezbriega.github.io/blog/2016/06/29/distribuciones-de-probabilidad-con-python/) de una o varias [variables aleatorias](https://es.wikipedia.org/wiki/Variable_aleatoria), [regresiones lineales](https://es.wikipedia.org/wiki/Regresi%C3%B3n_lineal), [series de tiempo](https://es.wikipedia.org/wiki/Serie_temporal), entre muchas otras. Con ella podemos construir visualizaciones complejas en forma sencilla.\n",
    "\n",
    "\n",
    "* **[Folium](https://folium.readthedocs.io/en/latest/)**: Si lo que necesitamos es visualizar datos de [geolocalización](https://es.wikipedia.org/wiki/Geolocalizaci%C3%B3n) en mapas interactivos, entonces [Folium](https://folium.readthedocs.io/en/latest/) es una muy buena opción. Esta librería de [Python](http://python.org/) es una herramienta sumamente poderosa para realizar mapas al estilo [leaflet.js](http://leafletjs.com/). El hecho de que los resultados de [Folium](https://folium.readthedocs.io/en/latest/) son interactivos hace que esta librería sea útil para la construcción de *dashboards*.\n",
    "\n",
    "## ¿Cómo elegir la visualización adecuada?\n",
    "\n",
    "Una de las primeras preguntas que nos debemos realizar al explorar datos es ¿qué método de visualización es más efectivo?. Para intentar responder esta pregunta podemos utilizar la siguiente guía: \n",
    "\n",
    "<img alt=\"Visualizaciones de datos con Python\" title=\"Visualizaciones de datos con Python\" src=\"http://relopezbriega.github.io/images/chartchooserincolor.jpg\" high=400px width=600px>\n",
    "\n",
    "Como podemos ver, la guía se divide en cuatro categorías principales y luego se clasifican los distintos métodos de visualización que mejor representan cada una de esas categorías. Veamos un poco más en detalle cada una de ellas:\n",
    "\n",
    "* **[Distribuciones](http://relopezbriega.github.io/blog/2016/06/29/distribuciones-de-probabilidad-con-python/)**: En esta categoría intentamos comprender como los datos se distribuyen. Se suelen utilizar en el comienzo de la etapa de exploración de datos, cuando queremos comprender las variables. Aquí también nos vamos a encontrar con variables de dos tipos [cuantitativas](http://relopezbriega.github.io/blog/2016/03/13/analisis-de-datos-cuantitativos-con-python/) y [categóricas](http://relopezbriega.github.io/blog/2016/02/29/analisis-de-datos-categoricos-con-python/). Dependiendo del tipo y cantidad de variables, el método de visualización que vamos a utilizar.\n",
    "\n",
    "* **Comparaciones**: En esta categoría el objetivo es comparar valores a través de diferentes categorías y con el tiempo (tendencia). Los tipos de gráficos más comunes en esta categoría son los [diagramas de barras](https://es.wikipedia.org/wiki/Diagrama_de_barras) para cuando estamos comparando elementos o categorías y los [diagramas de puntos y líneas](https://en.wikipedia.org/wiki/Line_chart) cuando comparamos variables [cuantitativas](http://relopezbriega.github.io/blog/2016/03/13/analisis-de-datos-cuantitativos-con-python/).\n",
    "\n",
    "* **Relaciones**: Aquí el objetivo es comprender la relación entre dos o más variables. La visualización más utilizada en esta categoría es el [gráfico de dispersión](https://es.wikipedia.org/wiki/Diagrama_de_dispersi%C3%B3n).\n",
    "\n",
    "* **Composiciones**: En esta categoría el objetivo es comprender como esta compuesta o distribuida una variable; ya sea a través del tiempo o en forma estática. Las visualizaciones más comunes aquí son los [diagramas de barras](https://es.wikipedia.org/wiki/Diagrama_de_barras) y los [gráficos de tortas](https://es.wikipedia.org/wiki/Gr%C3%A1fico_circular).\n",
    "\n",
    "## Ejemplos en Python\n",
    "\n",
    "Luego de esta introducción es hora de ensuciarse las manos y ponerse a jugar con algunos ejemplos en el uso de cada una de estas 4 librerías que nos ofrece [Python](http://python.org/) para visualización de datos. Obviamente los ejemplos van a ser sencillos ya que un tutorial exhaustivo sobre cada herramienta requeriría mucho más espacio.\n",
    "\n",
    "### Matplotlib\n",
    "\n",
    "Comencemos con [Matplotlib](http://matplotlib.org/gallery.html); como les comentaba, es tal vez la librería más utilizada para gráficos en 2d. El objeto `pyplot` nos proporciona la interfase principal sobre la que podemos crear las visualizaciones de datos con esta librería."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"http://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"0f67c312-b93b-41ef-9215-63bfa5199b1f\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(global) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = \"1\";\n",
       "\n",
       "  if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force !== \"\") {\n",
       "    window._bokeh_onload_callbacks = [];\n",
       "    window._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "\n",
       "  \n",
       "  if (typeof (window._bokeh_timeout) === \"undefined\" || force !== \"\") {\n",
       "    window._bokeh_timeout = Date.now() + 5000;\n",
       "    window._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    if (window.Bokeh !== undefined) {\n",
       "      Bokeh.$(\"#0f67c312-b93b-41ef-9215-63bfa5199b1f\").text(\"BokehJS successfully loaded.\");\n",
       "    } else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    delete window._bokeh_onload_callbacks\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    window._bokeh_onload_callbacks.push(callback);\n",
       "    if (window._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    window._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        window._bokeh_is_loading--;\n",
       "        if (window._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"0f67c312-b93b-41ef-9215-63bfa5199b1f\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '0f67c312-b93b-41ef-9215-63bfa5199b1f' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = ['https://cdn.pydata.org/bokeh/release/bokeh-0.12.2.min.js', 'https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.2.min.js', 'https://cdn.pydata.org/bokeh/release/bokeh-compiler-0.12.2.min.js'];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "      Bokeh.$(\"#0f67c312-b93b-41ef-9215-63bfa5199b1f\").text(\"BokehJS is loading...\");\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.2.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.2.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.2.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.2.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((window.Bokeh !== undefined) || (force === \"1\")) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i](window.Bokeh);\n",
       "      }if (force === \"1\") {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!window._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      window._bokeh_failed_load = true;\n",
       "    } else if (!force) {\n",
       "      var cell = $(\"#0f67c312-b93b-41ef-9215-63bfa5199b1f\").parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (window._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(this));"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# <!-- collapse=True -->\n",
    "# importando modulos necesarios\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pydataset import data\n",
    "import re\n",
    "\n",
    "# librerías de visualizaciones\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt \n",
    "from bokeh.io import output_notebook, show\n",
    "from bokeh.charts import Histogram, Scatter\n",
    "import folium\n",
    "\n",
    "# graficos incrustados\n",
    "%matplotlib inline\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Cargamos algunos datasets de ejemplo\n",
    "iris = data('iris')\n",
    "tips = data('tips')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAAFpCAYAAAARChjbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJEwhhBCiEv4f6C/UMhADUaIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdf07ebf828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ejemplo matplotlib\n",
    "# graficanco funciones seno y coseno\n",
    "X = np.linspace(-np.pi, np.pi, 256, endpoint=True)\n",
    "C, S = np.cos(X), np.sin(X)\n",
    "\n",
    "# configurando el tamaño de la figura\n",
    "plt.figure(figsize=(8, 6))\n",
    "# dibujando las curvas\n",
    "plt.plot(X, C, color=\"blue\", linewidth=2.5, linestyle=\"-\", label=\"coseno\")\n",
    "plt.plot(X, S, color=\"red\",  linewidth=2.5, linestyle=\"-\", label=\"seno\")\n",
    "# personalizando los valores de los ejes\n",
    "plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi],\n",
    "          [r'$-\\pi$', r'$-\\pi/2$', r'$0$', r'$+\\pi/2$', r'$+\\pi$'])\n",
    "\n",
    "plt.yticks([-1, 0, +1],\n",
    "          [r'$-1$', r'$0$', r'$+1$'])\n",
    "# agregando la leyenda\n",
    "plt.legend(loc='upper left')\n",
    "# moviendo los ejes de coordenadas\n",
    "ax = plt.gca()  # get current axis\n",
    "ax.spines['right'].set_color('none')\n",
    "ax.spines['top'].set_color('none')\n",
    "ax.xaxis.set_ticks_position('bottom')\n",
    "ax.spines['bottom'].set_position(('data',0))\n",
    "ax.yaxis.set_ticks_position('left')\n",
    "ax.spines['left'].set_position(('data',0))\n",
    "# mostrando el resultado\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "En este primer ejemplo vemos como podemos acceder a la API de [Matplotlib](http://matplotlib.org/gallery.html) desde el objeto `pyplot` e ir dando forma al gráfico. Veamos ahora unos ejemplos con el dataset iris."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sepal.Length</th>\n",
       "      <th>Sepal.Width</th>\n",
       "      <th>Petal.Length</th>\n",
       "      <th>Petal.Width</th>\n",
       "      <th>Species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Sepal.Length  Sepal.Width  Petal.Length  Petal.Width Species\n",
       "1           5.1          3.5           1.4          0.2  setosa\n",
       "2           4.9          3.0           1.4          0.2  setosa\n",
       "3           4.7          3.2           1.3          0.2  setosa\n",
       "4           4.6          3.1           1.5          0.2  setosa\n",
       "5           5.0          3.6           1.4          0.2  setosa"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Ejemplo con iris\n",
    "# histograma de Petal.Length\n",
    "iris.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# separo en especies\n",
    "setosa = iris[iris.Species == 'setosa']\n",
    "versicolor = iris[iris.Species == 'versicolor']\n",
    "virginica = iris[iris.Species == 'virginica']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmAAAAH4CAYAAADttlFjAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/x/6+CDlbwDS7QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdf045155c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# crear histograma\n",
    "plt.figure(figsize=(10, 8))\n",
    "n, bins, patches = plt.hist(setosa['Petal.Length'], 12, \n",
    "                            facecolor='red', label='setosa')\n",
    "n, bins, patches = plt.hist(versicolor['Petal.Length'], 12, \n",
    "                            facecolor='green', label='versicolor')\n",
    "n, bins, patches = plt.hist(virginica['Petal.Length'], 12, \n",
    "                            facecolor='blue', label='virginica')\n",
    "plt.legend(loc='top_right')\n",
    "plt.title('Histograma largo del pétalo')\n",
    "plt.xlabel('largo del pétalo')\n",
    "plt.ylabel('cuenta largo del pétalo')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmgAAAH4CAYAAAD+YRGXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSZKkzvwECOT6lhhaVtwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdf044b0f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ejemplo diagrama de dispersion entre Petal.Length y Petal.Width\n",
    "plt.figure(figsize=(10, 8))\n",
    "plt.scatter(setosa['Petal.Length'], setosa['Petal.Width'], \n",
    "            c='red', label='setosa')\n",
    "plt.scatter(versicolor['Petal.Length'], versicolor['Petal.Width'], \n",
    "            c='green', label='versicolor')\n",
    "plt.scatter(virginica['Petal.Length'], virginica['Petal.Width'], \n",
    "            c='blue', label='virginica')\n",
    "plt.title('Tamaño del pétalo')\n",
    "plt.xlabel('Largo del pétalo (cm)')\n",
    "plt.ylabel('Ancho del pétalo (cm)')\n",
    "plt.legend(loc='top_left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bokeh\n",
    "\n",
    "[Bokeh](http://bokeh.pydata.org/en/latest/) además de generar unos hermosos gráficos interactivos nos permite realizar gráficos complejos en forma muy sencilla. La interfase de alto nivel con la que vamos a trabajar principalmente para generar visualizaciones con esta librería es `bokeh.charts`. Repitamos los ejemplos que realizamos anteriormente sobre el dataset iris y veamos que sencillo que es realizarlos con [Bokeh](http://bokeh.pydata.org/en/latest/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"plotdiv\" id=\"c195cf80-93de-4663-b5d3-f106a1051aec\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "  \n",
       "    var force = \"\";\n",
       "  \n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force !== \"\") {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "  \n",
       "  \n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force !== \"\") {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "  \n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "  \n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        Bokeh.$(\"#c195cf80-93de-4663-b5d3-f106a1051aec\").text(\"BokehJS successfully loaded.\");\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "  \n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "  \n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"c195cf80-93de-4663-b5d3-f106a1051aec\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'c195cf80-93de-4663-b5d3-f106a1051aec' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "  \n",
       "    var js_urls = [];\n",
       "  \n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        Bokeh.$(function() {\n",
       "            var docs_json = {\"9a7ef9a1-1421-4082-99ad-6e5085ca7300\":{\"roots\":{\"references\":[{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(6.7, 6.9]\"],\"color\":[\"#407ee7\"],\"fill_alpha\":[0.6],\"height\":[1.0],\"label\":[\"(6.7, 6.9]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.1999999999999993],\"x\":[\"6.800000000000001\"],\"y\":[0.5]}},\"id\":\"f0919d08-3312-4eb1-9203-d799f245e6ac\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"axis_label\":\"Count( Petal.Length )\",\"formatter\":{\"id\":\"c3c1ce28-d2d4-44e7-ad49-3561d2c59f93\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"11045096-f9bf-453f-ab37-ae3b16279d10\",\"subtype\":\"Chart\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"8b75d8f4-692d-46b5-8161-191c87ac53d0\",\"type\":\"BasicTicker\"}},\"id\":\"0a7db6c1-eb28-4900-9bdf-1d93ba9cb5e5\",\"type\":\"LinearAxis\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"d8b4a2de-5be2-42de-9bb0-550541660d68\",\"type\":\"Rect\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"de23b9c7-1fa0-4bde-950f-dd7a950cddc1\",\"type\":\"Rect\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(1.5, 1.6]\"],\"color\":[\"#f22c40\"],\"fill_alpha\":[0.6],\"height\":[0.0],\"label\":[\"(1.5, 1.6]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.07500000000000018],\"x\":[\"1.55\"],\"y\":[0.0]}},\"id\":\"7d34c7ce-0b4d-46b1-b52e-5060ef3e7fc8\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"below\":[{\"id\":\"65c588cf-89f1-43bc-93f4-1ab62f536b61\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"0a7db6c1-eb28-4900-9bdf-1d93ba9cb5e5\",\"type\":\"LinearAxis\"}],\"renderers\":[{\"id\":\"65b3ec7f-68f8-4773-bc4f-fc7249739ad4\",\"type\":\"BoxAnnotation\"},{\"id\":\"36511e12-214f-4304-a6d6-29bd5a432678\",\"type\":\"GlyphRenderer\"},{\"id\":\"d50b7377-77b1-4d59-b5d4-3596eabedf1b\",\"type\":\"GlyphRenderer\"},{\"id\":\"1adfccc6-6cd0-428d-b448-55ad3556b10b\",\"type\":\"GlyphRenderer\"},{\"id\":\"6584ad63-c9cd-4c40-86c6-1089a9b60d0f\",\"type\":\"GlyphRenderer\"},{\"id\":\"a9ac49d3-5728-40e2-9b96-cc8e87459f11\",\"type\":\"GlyphRenderer\"},{\"id\":\"3953359b-7cbf-4f92-ac48-d7e946f5da8f\",\"type\":\"GlyphRenderer\"},{\"id\":\"1c22c604-377c-43df-9911-72a7c1c0fcdc\",\"type\":\"GlyphRenderer\"},{\"id\":\"57407940-9fcc-40f2-a7be-93b285aae9e3\",\"type\":\"GlyphRenderer\"},{\"id\":\"5f2942c5-803d-4c89-b331-f25318d170a9\",\"type\":\"GlyphRenderer\"},{\"id\":\"d23a806d-8cf1-44d1-a75f-2f214751f842\",\"type\":\"GlyphRenderer\"},{\"id\":\"0d30e117-2f9d-4731-b823-66dfd38e639c\",\"type\":\"GlyphRenderer\"},{\"id\":\"b420e134-cf91-427c-b267-bfb8d03b9c86\",\"type\":\"GlyphRenderer\"},{\"id\":\"d32373e1-c6f4-4f9b-a126-a2b6b1e6015c\",\"type\":\"GlyphRenderer\"},{\"id\":\"99021687-61c6-4ef6-9f5b-9e8c33093b4d\",\"type\":\"GlyphRenderer\"},{\"id\":\"a2c440a9-b3e4-4ccf-95b2-b0d01cae766b\",\"type\":\"GlyphRenderer\"},{\"id\":\"74ad0c86-2d16-4f7a-9a52-9bf87ee943dc\",\"type\":\"GlyphRenderer\"},{\"id\":\"4d5c02ae-1ef9-4dc7-854d-da02e7bfae05\",\"type\":\"GlyphRenderer\"},{\"id\":\"2bb1c3ce-0233-42f3-b87e-70e089d0a0fe\",\"type\":\"GlyphRenderer\"},{\"id\":\"00b0bc04-4582-44b4-b685-3fecdcd5405a\",\"type\":\"GlyphRenderer\"},{\"id\":\"54dbde3c-1354-4de1-bd7a-63cf83fa0ffa\",\"type\":\"GlyphRenderer\"},{\"id\":\"d94405dd-7d4e-43f6-9f40-3f9d037bcd34\",\"type\":\"GlyphRenderer\"},{\"id\":\"76fdaea6-4520-4acd-a374-3898b7087165\",\"type\":\"GlyphRenderer\"},{\"id\":\"4f214efb-7718-46f8-ad1d-db22eb046cd9\",\"type\":\"GlyphRenderer\"},{\"id\":\"6a916ded-3ce1-43ff-a8f8-6bd97ede2ac5\",\"type\":\"GlyphRenderer\"},{\"id\":\"91998099-89a6-4938-a8b2-3f06cbf18308\",\"type\":\"GlyphRenderer\"},{\"id\":\"e8ee0648-accf-4eec-9d42-ee61ca622048\",\"type\":\"GlyphRenderer\"},{\"id\":\"453ec58b-0d01-4a9f-945b-a19c5464a7c1\",\"type\":\"GlyphRenderer\"},{\"id\":\"14dc7813-2970-41f3-ba9c-6f6cda3970c9\",\"type\":\"GlyphRenderer\"},{\"id\":\"13782731-bbbb-4240-88a7-35929bc0c496\",\"type\":\"GlyphRenderer\"},{\"id\":\"74dc2f94-589b-408e-afa0-e9957b2cdca1\",\"type\":\"GlyphRenderer\"},{\"id\":\"db55a27a-d062-4fdd-a78d-bf702fc14f91\",\"type\":\"GlyphRenderer\"},{\"id\":\"a99be2a3-d708-4868-8123-b3025ac7a9eb\",\"type\":\"GlyphRenderer\"},{\"id\":\"18dbee68-9d0a-4476-b264-a21c7ff6c0fc\",\"type\":\"GlyphRenderer\"},{\"id\":\"a8bffd51-3e3c-4b99-a636-44f92fd7821a\",\"type\":\"GlyphRenderer\"},{\"id\":\"7684a062-ce50-4e22-89ac-a24647378a6b\",\"type\":\"GlyphRenderer\"},{\"id\":\"b7f5cce1-f6dd-47d2-80fd-bc12ae18401b\",\"type\":\"GlyphRenderer\"},{\"id\":\"ebd307bb-49ce-42a0-9983-7551927b1dd8\",\"type\":\"Legend\"},{\"id\":\"65c588cf-89f1-43bc-93f4-1ab62f536b61\",\"type\":\"LinearAxis\"},{\"id\":\"0a7db6c1-eb28-4900-9bdf-1d93ba9cb5e5\",\"type\":\"LinearAxis\"},{\"id\":\"4343e9e9-a240-4174-9829-7ec76f67ec39\",\"type\":\"Grid\"}],\"title\":{\"id\":\"26780f07-f264-4ebc-a91d-c436d5e85dc6\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"9bf3c871-b086-4c1d-b7e3-cd60db2e64bb\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"7cde5e44-4da9-432b-847e-6472ebb9e0c0\",\"type\":\"Toolbar\"},\"x_mapper_type\":\"auto\",\"x_range\":{\"id\":\"c0c01d28-e83a-4a5b-aa15-a683b132b950\",\"type\":\"Range1d\"},\"y_mapper_type\":\"auto\",\"y_range\":{\"id\":\"dc51d7a0-661b-4b48-95c7-b7cea750f377\",\"type\":\"Range1d\"}},\"id\":\"11045096-f9bf-453f-ab37-ae3b16279d10\",\"subtype\":\"Chart\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"f6784e6e-1643-4bdc-b6b4-213cf3fabb8c\",\"type\":\"BasicTicker\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"c49a4520-6132-483a-bbfe-7efa69605cf4\",\"type\":\"Rect\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(3.4, 3.5]\"],\"color\":[\"#5ab738\"],\"fill_alpha\":[0.6],\"height\":[2.0],\"label\":[\"(3.4, 3.5]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.17499999999999982],\"x\":[\"3.45\"],\"y\":[1.0]}},\"id\":\"f7b1ad74-75f0-4188-a294-00817e70d879\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(4.7, 4.9]\"],\"color\":[\"#407ee7\"],\"fill_alpha\":[0.6],\"height\":[2.0],\"label\":[\"(4.7, 4.9]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.20000000000000018],\"x\":[\"4.800000000000001\"],\"y\":[1.0]}},\"id\":\"c610f030-60ea-42d7-a6ec-4fe4ea68cee4\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(4.8, 4.9]\"],\"color\":[\"#5ab738\"],\"fill_alpha\":[0.6],\"height\":[4.0],\"label\":[\"(4.8, 4.9]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.17499999999999982],\"x\":[\"4.85\"],\"y\":[2.0]}},\"id\":\"a144c79a-986b-48f5-acb7-1d11f88ddb98\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"01767a08-0689-45ab-bb04-0e494141694c\",\"type\":\"PanTool\"},{\"id\":\"33b9928a-6f78-43d3-9703-8ba925f70680\",\"type\":\"WheelZoomTool\"},{\"id\":\"04948cd0-b032-42ef-9507-cccf60ac14e3\",\"type\":\"BoxZoomTool\"},{\"id\":\"8d91f9ba-606f-43d2-922a-4b4a89232e66\",\"type\":\"SaveTool\"},{\"id\":\"28d55f5f-9ea8-4891-88b6-2cc48662a398\",\"type\":\"ResetTool\"},{\"id\":\"f1471099-0de8-4b4a-8664-314236e91d91\",\"type\":\"HelpTool\"}]},\"id\":\"7cde5e44-4da9-432b-847e-6472ebb9e0c0\",\"type\":\"Toolbar\"},{\"attributes\":{\"data_source\":{\"id\":\"0fb9b06c-0bc4-412d-8e8d-b76767245486\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"f080a166-8ce2-495f-8396-7a2a36d34d6d\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"18dbee68-9d0a-4476-b264-a21c7ff6c0fc\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(5.5, 5.7]\"],\"color\":[\"#407ee7\"],\"fill_alpha\":[0.6],\"height\":[6.0],\"label\":[\"(5.5, 5.7]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.20000000000000018],\"x\":[\"5.6\"],\"y\":[3.0]}},\"id\":\"8d3e00f4-599b-4b89-a37f-bbd5e20b3a3a\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(4.4, 4.6]\"],\"color\":[\"#5ab738\"],\"fill_alpha\":[0.6],\"height\":[11.0],\"label\":[\"(4.4, 4.6]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.17499999999999982],\"x\":[\"4.5\"],\"y\":[5.5]}},\"id\":\"6997341d-616a-441c-a92f-bf944506ea15\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"f7b1ad74-75f0-4188-a294-00817e70d879\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"8351723e-ed98-42c1-96e4-c659fb25805d\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"a2c440a9-b3e4-4ccf-95b2-b0d01cae766b\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(1.8, 1.8]\"],\"color\":[\"#f22c40\"],\"fill_alpha\":[0.6],\"height\":[0.0],\"label\":[\"(1.8, 1.8]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.07499999999999996],\"x\":[\"1.8\"],\"y\":[0.0]}},\"id\":\"2d3b8826-5904-4d7b-b066-f14a5d6575ba\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"plot\":{\"id\":\"11045096-f9bf-453f-ab37-ae3b16279d10\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"f1471099-0de8-4b4a-8664-314236e91d91\",\"type\":\"HelpTool\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"99f89837-6c58-43fe-a7e7-68f956bfc265\",\"type\":\"Rect\"},{\"attributes\":{},\"id\":\"8b75d8f4-692d-46b5-8161-191c87ac53d0\",\"type\":\"BasicTicker\"},{\"attributes\":{\"data_source\":{\"id\":\"7e7e3616-0f52-4aea-b0d5-f35fd6014e76\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"4ead34d7-1c73-41b8-ba8e-39143a9da986\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"91998099-89a6-4938-a8b2-3f06cbf18308\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"9c12aba0-bb79-40f7-9ed0-e56564ce3795\",\"type\":\"Rect\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"[4.5, 4.7]\"],\"color\":[\"#407ee7\"],\"fill_alpha\":[0.6],\"height\":[1.0],\"label\":[\"[4.5, 4.7]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.20000000000000018],\"x\":[\"4.6\"],\"y\":[0.5]}},\"id\":\"7e7e3616-0f52-4aea-b0d5-f35fd6014e76\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(6.3, 6.5]\"],\"color\":[\"#407ee7\"],\"fill_alpha\":[0.6],\"height\":[1.0],\"label\":[\"(6.3, 6.5]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.1999999999999993],\"x\":[\"6.4\"],\"y\":[0.5]}},\"id\":\"b8caa1af-0a95-441e-87a8-75299dd912d7\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"2d3b8826-5904-4d7b-b066-f14a5d6575ba\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"652ddbec-0873-40db-a0ae-66f832788023\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"0d30e117-2f9d-4731-b823-66dfd38e639c\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"data_source\":{\"id\":\"8d3e00f4-599b-4b89-a37f-bbd5e20b3a3a\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"86f5a87e-9113-4062-9be9-71482851fbf4\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"74dc2f94-589b-408e-afa0-e9957b2cdca1\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"data_source\":{\"id\":\"6f74eb57-be16-4e39-9c55-a5357bf06e8c\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"de23b9c7-1fa0-4bde-950f-dd7a950cddc1\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"d32373e1-c6f4-4f9b-a126-a2b6b1e6015c\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"data_source\":{\"id\":\"f50c290c-9a0d-46c1-b06d-02432e3ed4d7\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"1bb2865b-928e-4d4b-b9e1-6c5850c034b8\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"db55a27a-d062-4fdd-a78d-bf702fc14f91\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"data_source\":{\"id\":\"7526af5b-d39b-42d4-9f2b-c652c313dab2\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"35e46d23-f3f7-4e0c-9128-15dcfbdafe77\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"3953359b-7cbf-4f92-ac48-d7e946f5da8f\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"26c90387-b300-4bf0-95c9-7412b64db554\",\"type\":\"Rect\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(6.5, 6.7]\"],\"color\":[\"#407ee7\"],\"fill_alpha\":[0.6],\"height\":[3.0],\"label\":[\"(6.5, 6.7]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.20000000000000107],\"x\":[\"6.6\"],\"y\":[1.5]}},\"id\":\"9eb3dfd4-bc18-46d2-942e-7c84d93900c2\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"b9eee02f-7a94-4e05-b27d-8f54fc6f10b0\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"d8b4a2de-5be2-42de-9bb0-550541660d68\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"00b0bc04-4582-44b4-b685-3fecdcd5405a\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null,\"end\":7.097812500000001,\"start\":0.8146875000000001},\"id\":\"c0c01d28-e83a-4a5b-aa15-a683b132b950\",\"type\":\"Range1d\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"86f5a87e-9113-4062-9be9-71482851fbf4\",\"type\":\"Rect\"},{\"attributes\":{\"data_source\":{\"id\":\"c2e1fe56-41c4-4a24-be85-01a0a088a228\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"9c12aba0-bb79-40f7-9ed0-e56564ce3795\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"54dbde3c-1354-4de1-bd7a-63cf83fa0ffa\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(1.4, 1.5]\"],\"color\":[\"#f22c40\"],\"fill_alpha\":[0.6],\"height\":[13.0],\"label\":[\"(1.4, 1.5]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.07499999999999996],\"x\":[\"1.45\"],\"y\":[6.5]}},\"id\":\"2cf4059b-f475-4e7a-ad98-62b6a916e262\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"a6d20e7d-b9c8-404d-ab8d-8c230ab70714\",\"type\":\"Rect\"},{\"attributes\":{\"data_source\":{\"id\":\"99070434-8683-414b-acc7-2154b21380c3\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"71b1fd33-c505-43b4-92fe-e40258d933fd\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"36511e12-214f-4304-a6d6-29bd5a432678\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"data_source\":{\"id\":\"f44df727-4cac-4374-96d8-ef0851413fa6\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"0680f1d7-a780-40c3-a7dd-fbb5bdf6209e\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"13782731-bbbb-4240-88a7-35929bc0c496\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"76846e18-e4cb-4f33-9f4c-58f4f2703a56\",\"type\":\"Rect\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(1.2, 1.3]\"],\"color\":[\"#f22c40\"],\"fill_alpha\":[0.6],\"height\":[0.0],\"label\":[\"(1.2, 1.3]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.07499999999999996],\"x\":[\"1.25\"],\"y\":[0.0]}},\"id\":\"2b13a05d-9444-464f-b00d-72bbba77fde5\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"c555888d-6099-4f08-a212-2801b85d632e\",\"type\":\"Rect\"},{\"attributes\":{\"data_source\":{\"id\":\"a952c612-c391-418c-9b12-65bb7c1323f3\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"34da3089-0c20-43ba-b380-58674d133744\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"4d5c02ae-1ef9-4dc7-854d-da02e7bfae05\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"4e1a0571-a9b8-4f63-8801-698fa1f61372\",\"type\":\"Rect\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"0680f1d7-a780-40c3-a7dd-fbb5bdf6209e\",\"type\":\"Rect\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"f932210c-c7f5-4a26-ad41-b3f024c3ef6d\",\"type\":\"Rect\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(5.7, 5.9]\"],\"color\":[\"#407ee7\"],\"fill_alpha\":[0.6],\"height\":[6.0],\"label\":[\"(5.7, 5.9]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.20000000000000018],\"x\":[\"5.800000000000001\"],\"y\":[3.0]}},\"id\":\"f50c290c-9a0d-46c1-b06d-02432e3ed4d7\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(1.1, 1.2]\"],\"color\":[\"#f22c40\"],\"fill_alpha\":[0.6],\"height\":[2.0],\"label\":[\"(1.1, 1.2]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.07500000000000018],\"x\":[\"1.15\"],\"y\":[1.0]}},\"id\":\"29ff4a76-00e2-4dc4-a886-d6beb2e374d5\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"71b1fd33-c505-43b4-92fe-e40258d933fd\",\"type\":\"Rect\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"16a90b24-083d-4317-9520-6d9fdb1d59da\",\"type\":\"Rect\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(4.9, 5.1]\"],\"color\":[\"#5ab738\"],\"fill_alpha\":[0.6],\"height\":[2.0],\"label\":[\"(4.9, 5.1]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.17499999999999982],\"x\":[\"5.0\"],\"y\":[1.0]}},\"id\":\"122ae1dd-4006-4254-b2a1-790acf1fdeef\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(4.0, 4.2]\"],\"color\":[\"#5ab738\"],\"fill_alpha\":[0.6],\"height\":[7.0],\"label\":[\"(4.0, 4.2]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.17499999999999982],\"x\":[\"4.1\"],\"y\":[3.5]}},\"id\":\"b9eee02f-7a94-4e05-b27d-8f54fc6f10b0\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(5.9, 6.1]\"],\"color\":[\"#407ee7\"],\"fill_alpha\":[0.6],\"height\":[7.0],\"label\":[\"(5.9, 6.1]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.20000000000000018],\"x\":[\"6.0\"],\"y\":[3.5]}},\"id\":\"b68ba484-3287-4881-8e6b-25e29bf58249\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"652ddbec-0873-40db-a0ae-66f832788023\",\"type\":\"Rect\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"8d5eec3d-9456-45f0-9229-db8d6e680a31\",\"type\":\"Rect\"},{\"attributes\":{\"legends\":[[\"setosa\",[{\"id\":\"36511e12-214f-4304-a6d6-29bd5a432678\",\"type\":\"GlyphRenderer\"},{\"id\":\"d50b7377-77b1-4d59-b5d4-3596eabedf1b\",\"type\":\"GlyphRenderer\"},{\"id\":\"1adfccc6-6cd0-428d-b448-55ad3556b10b\",\"type\":\"GlyphRenderer\"},{\"id\":\"6584ad63-c9cd-4c40-86c6-1089a9b60d0f\",\"type\":\"GlyphRenderer\"},{\"id\":\"a9ac49d3-5728-40e2-9b96-cc8e87459f11\",\"type\":\"GlyphRenderer\"},{\"id\":\"3953359b-7cbf-4f92-ac48-d7e946f5da8f\",\"type\":\"GlyphRenderer\"},{\"id\":\"1c22c604-377c-43df-9911-72a7c1c0fcdc\",\"type\":\"GlyphRenderer\"},{\"id\":\"57407940-9fcc-40f2-a7be-93b285aae9e3\",\"type\":\"GlyphRenderer\"},{\"id\":\"5f2942c5-803d-4c89-b331-f25318d170a9\",\"type\":\"GlyphRenderer\"},{\"id\":\"d23a806d-8cf1-44d1-a75f-2f214751f842\",\"type\":\"GlyphRenderer\"},{\"id\":\"0d30e117-2f9d-4731-b823-66dfd38e639c\",\"type\":\"GlyphRenderer\"},{\"id\":\"b420e134-cf91-427c-b267-bfb8d03b9c86\",\"type\":\"GlyphRenderer\"}]],[\"versicolor\",[{\"id\":\"d32373e1-c6f4-4f9b-a126-a2b6b1e6015c\",\"type\":\"GlyphRenderer\"},{\"id\":\"99021687-61c6-4ef6-9f5b-9e8c33093b4d\",\"type\":\"GlyphRenderer\"},{\"id\":\"a2c440a9-b3e4-4ccf-95b2-b0d01cae766b\",\"type\":\"GlyphRenderer\"},{\"id\":\"74ad0c86-2d16-4f7a-9a52-9bf87ee943dc\",\"type\":\"GlyphRenderer\"},{\"id\":\"4d5c02ae-1ef9-4dc7-854d-da02e7bfae05\",\"type\":\"GlyphRenderer\"},{\"id\":\"2bb1c3ce-0233-42f3-b87e-70e089d0a0fe\",\"type\":\"GlyphRenderer\"},{\"id\":\"00b0bc04-4582-44b4-b685-3fecdcd5405a\",\"type\":\"GlyphRenderer\"},{\"id\":\"54dbde3c-1354-4de1-bd7a-63cf83fa0ffa\",\"type\":\"GlyphRenderer\"},{\"id\":\"d94405dd-7d4e-43f6-9f40-3f9d037bcd34\",\"type\":\"GlyphRenderer\"},{\"id\":\"76fdaea6-4520-4acd-a374-3898b7087165\",\"type\":\"GlyphRenderer\"},{\"id\":\"4f214efb-7718-46f8-ad1d-db22eb046cd9\",\"type\":\"GlyphRenderer\"},{\"id\":\"6a916ded-3ce1-43ff-a8f8-6bd97ede2ac5\",\"type\":\"GlyphRenderer\"}]],[\"virginica\",[{\"id\":\"91998099-89a6-4938-a8b2-3f06cbf18308\",\"type\":\"GlyphRenderer\"},{\"id\":\"e8ee0648-accf-4eec-9d42-ee61ca622048\",\"type\":\"GlyphRenderer\"},{\"id\":\"453ec58b-0d01-4a9f-945b-a19c5464a7c1\",\"type\":\"GlyphRenderer\"},{\"id\":\"14dc7813-2970-41f3-ba9c-6f6cda3970c9\",\"type\":\"GlyphRenderer\"},{\"id\":\"13782731-bbbb-4240-88a7-35929bc0c496\",\"type\":\"GlyphRenderer\"},{\"id\":\"74dc2f94-589b-408e-afa0-e9957b2cdca1\",\"type\":\"GlyphRenderer\"},{\"id\":\"db55a27a-d062-4fdd-a78d-bf702fc14f91\",\"type\":\"GlyphRenderer\"},{\"id\":\"a99be2a3-d708-4868-8123-b3025ac7a9eb\",\"type\":\"GlyphRenderer\"},{\"id\":\"18dbee68-9d0a-4476-b264-a21c7ff6c0fc\",\"type\":\"GlyphRenderer\"},{\"id\":\"a8bffd51-3e3c-4b99-a636-44f92fd7821a\",\"type\":\"GlyphRenderer\"},{\"id\":\"7684a062-ce50-4e22-89ac-a24647378a6b\",\"type\":\"GlyphRenderer\"},{\"id\":\"b7f5cce1-f6dd-47d2-80fd-bc12ae18401b\",\"type\":\"GlyphRenderer\"}]]],\"plot\":{\"id\":\"11045096-f9bf-453f-ab37-ae3b16279d10\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"ebd307bb-49ce-42a0-9983-7551927b1dd8\",\"type\":\"Legend\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"65b3ec7f-68f8-4773-bc4f-fc7249739ad4\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"8260b0c1-d1d4-4ea6-b5c0-cede9d9b148b\",\"type\":\"Rect\"},{\"attributes\":{\"plot\":{\"id\":\"11045096-f9bf-453f-ab37-ae3b16279d10\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"01767a08-0689-45ab-bb04-0e494141694c\",\"type\":\"PanTool\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"f080a166-8ce2-495f-8396-7a2a36d34d6d\",\"type\":\"Rect\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(1.6, 1.7]\"],\"color\":[\"#f22c40\"],\"fill_alpha\":[0.6],\"height\":[7.0],\"label\":[\"(1.6, 1.7]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.07499999999999973],\"x\":[\"1.65\"],\"y\":[3.5]}},\"id\":\"74e11ba5-53d0-4bad-9aa3-380a3cf30f62\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"b7cc61ce-3be9-42d4-b7a7-f157df14105d\",\"type\":\"Rect\"},{\"attributes\":{},\"id\":\"41f1fafd-e3dd-4cbe-ae3f-c63382b1b03c\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"data_source\":{\"id\":\"b68ba484-3287-4881-8e6b-25e29bf58249\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"76846e18-e4cb-4f33-9f4c-58f4f2703a56\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"a99be2a3-d708-4868-8123-b3025ac7a9eb\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"data_source\":{\"id\":\"2cf4059b-f475-4e7a-ad98-62b6a916e262\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"16a90b24-083d-4317-9520-6d9fdb1d59da\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"1c22c604-377c-43df-9911-72a7c1c0fcdc\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"954264d8-6012-4c7d-b0ac-4425e2cbce75\",\"type\":\"Rect\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(1.1, 1.1]\"],\"color\":[\"#f22c40\"],\"fill_alpha\":[0.6],\"height\":[1.0],\"label\":[\"(1.1, 1.1]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.07499999999999996],\"x\":[\"1.1\"],\"y\":[0.5]}},\"id\":\"31e98faf-0be6-4bfc-8595-b5f76e6d6116\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(3.2, 3.4]\"],\"color\":[\"#5ab738\"],\"fill_alpha\":[0.6],\"height\":[2.0],\"label\":[\"(3.2, 3.4]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.17500000000000027],\"x\":[\"3.3\"],\"y\":[1.0]}},\"id\":\"3706bae4-a773-47f0-a96e-f2c07adbd601\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"[3.0, 3.2]\"],\"color\":[\"#5ab738\"],\"fill_alpha\":[0.6],\"height\":[1.0],\"label\":[\"[3.0, 3.2]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.17499999999999982],\"x\":[\"3.1\"],\"y\":[0.5]}},\"id\":\"6f74eb57-be16-4e39-9c55-a5357bf06e8c\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"9da9aea0-c0fd-4ecf-8f37-50d46903dd4e\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"c555888d-6099-4f08-a212-2801b85d632e\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"d23a806d-8cf1-44d1-a75f-2f214751f842\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"data_source\":{\"id\":\"6997341d-616a-441c-a92f-bf944506ea15\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"13690294-4149-4694-b35c-e861baab8952\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"d94405dd-7d4e-43f6-9f40-3f9d037bcd34\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"71836376-11cb-44e4-8dd2-2baae9fd5d7a\",\"type\":\"Rect\"},{\"attributes\":{\"data_source\":{\"id\":\"41ebf089-64d1-49a4-bce8-68f7436952a1\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"71836376-11cb-44e4-8dd2-2baae9fd5d7a\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"a9ac49d3-5728-40e2-9b96-cc8e87459f11\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"axis_label\":\"Petal.Length\",\"formatter\":{\"id\":\"41f1fafd-e3dd-4cbe-ae3f-c63382b1b03c\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"11045096-f9bf-453f-ab37-ae3b16279d10\",\"subtype\":\"Chart\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"f6784e6e-1643-4bdc-b6b4-213cf3fabb8c\",\"type\":\"BasicTicker\"}},\"id\":\"65c588cf-89f1-43bc-93f4-1ab62f536b61\",\"type\":\"LinearAxis\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(3.9, 4.0]\"],\"color\":[\"#5ab738\"],\"fill_alpha\":[0.6],\"height\":[8.0],\"label\":[\"(3.9, 4.0]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.17499999999999982],\"x\":[\"3.95\"],\"y\":[4.0]}},\"id\":\"1ca15bdf-f407-4282-9a89-3bb23c6b9809\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"13690294-4149-4694-b35c-e861baab8952\",\"type\":\"Rect\"},{\"attributes\":{\"data_source\":{\"id\":\"122ae1dd-4006-4254-b2a1-790acf1fdeef\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"c49a4520-6132-483a-bbfe-7efa69605cf4\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"6a916ded-3ce1-43ff-a8f8-6bd97ede2ac5\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(4.6, 4.8]\"],\"color\":[\"#5ab738\"],\"fill_alpha\":[0.6],\"height\":[8.0],\"label\":[\"(4.6, 4.8]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.1750000000000007],\"x\":[\"4.699999999999999\"],\"y\":[4.0]}},\"id\":\"85fdd08b-006e-491b-89df-ea5277a32035\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"b8caa1af-0a95-441e-87a8-75299dd912d7\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"f665bceb-bc09-4ea3-bcd0-4f40c54bb0aa\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"a8bffd51-3e3c-4b99-a636-44f92fd7821a\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"d0feb6f4-2b2e-4050-b574-6296e0e162a7\",\"type\":\"Rect\"},{\"attributes\":{\"data_source\":{\"id\":\"cacbfcb9-1efc-4e64-a1d2-98e09ba01027\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"4e1a0571-a9b8-4f63-8801-698fa1f61372\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"453ec58b-0d01-4a9f-945b-a19c5464a7c1\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"4ead34d7-1c73-41b8-ba8e-39143a9da986\",\"type\":\"Rect\"},{\"attributes\":{},\"id\":\"9bf3c871-b086-4c1d-b7e3-cd60db2e64bb\",\"type\":\"ToolEvents\"},{\"attributes\":{\"data_source\":{\"id\":\"9eb3dfd4-bc18-46d2-942e-7c84d93900c2\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"f932210c-c7f5-4a26-ad41-b3f024c3ef6d\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"7684a062-ce50-4e22-89ac-a24647378a6b\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"overlay\":{\"id\":\"65b3ec7f-68f8-4773-bc4f-fc7249739ad4\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"11045096-f9bf-453f-ab37-ae3b16279d10\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"04948cd0-b032-42ef-9507-cccf60ac14e3\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(1.3, 1.4]\"],\"color\":[\"#f22c40\"],\"fill_alpha\":[0.6],\"height\":[7.0],\"label\":[\"(1.3, 1.4]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.07499999999999996],\"x\":[\"1.35\"],\"y\":[3.5]}},\"id\":\"41ebf089-64d1-49a4-bce8-68f7436952a1\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"66ab54dc-c349-43fc-be95-13ac22b1cf16\",\"type\":\"Rect\"},{\"attributes\":{\"data_source\":{\"id\":\"31e98faf-0be6-4bfc-8595-b5f76e6d6116\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"c0d2e5af-b2aa-491d-8aa3-ff52dc596b91\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"d50b7377-77b1-4d59-b5d4-3596eabedf1b\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"plot\":{\"id\":\"11045096-f9bf-453f-ab37-ae3b16279d10\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"33b9928a-6f78-43d3-9703-8ba925f70680\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1bb2865b-928e-4d4b-b9e1-6c5850c034b8\",\"type\":\"Rect\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"c0d2e5af-b2aa-491d-8aa3-ff52dc596b91\",\"type\":\"Rect\"},{\"attributes\":{\"callback\":null,\"end\":14.3},\"id\":\"dc51d7a0-661b-4b48-95c7-b7cea750f377\",\"type\":\"Range1d\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(5.1, 5.3]\"],\"color\":[\"#407ee7\"],\"fill_alpha\":[0.6],\"height\":[4.0],\"label\":[\"(5.1, 5.3]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.20000000000000018],\"x\":[\"5.199999999999999\"],\"y\":[2.0]}},\"id\":\"a46bc75e-5dff-4c2e-9be9-579f4e9351df\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"c3c1ce28-d2d4-44e7-ad49-3561d2c59f93\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(4.9, 5.1]\"],\"color\":[\"#407ee7\"],\"fill_alpha\":[0.6],\"height\":[13.0],\"label\":[\"(4.9, 5.1]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.1999999999999993],\"x\":[\"5.0\"],\"y\":[6.5]}},\"id\":\"cacbfcb9-1efc-4e64-a1d2-98e09ba01027\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(3.7, 3.9]\"],\"color\":[\"#5ab738\"],\"fill_alpha\":[0.6],\"height\":[2.0],\"label\":[\"(3.7, 3.9]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.17500000000000027],\"x\":[\"3.8\"],\"y\":[1.0]}},\"id\":\"a952c612-c391-418c-9b12-65bb7c1323f3\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"11045096-f9bf-453f-ab37-ae3b16279d10\",\"subtype\":\"Chart\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"8b75d8f4-692d-46b5-8161-191c87ac53d0\",\"type\":\"BasicTicker\"}},\"id\":\"4343e9e9-a240-4174-9829-7ec76f67ec39\",\"type\":\"Grid\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"f665bceb-bc09-4ea3-bcd0-4f40c54bb0aa\",\"type\":\"Rect\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"35e46d23-f3f7-4e0c-9128-15dcfbdafe77\",\"type\":\"Rect\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(5.3, 5.5]\"],\"color\":[\"#407ee7\"],\"fill_alpha\":[0.6],\"height\":[5.0],\"label\":[\"(5.3, 5.5]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.20000000000000018],\"x\":[\"5.4\"],\"y\":[2.5]}},\"id\":\"f44df727-4cac-4374-96d8-ef0851413fa6\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"b0bf96e6-5dd5-4f8c-8d9d-30840bc1ee49\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"d0feb6f4-2b2e-4050-b574-6296e0e162a7\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"b420e134-cf91-427c-b267-bfb8d03b9c86\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"data_source\":{\"id\":\"0e943dfb-b301-4af6-a2e9-d05397655d44\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"c7c713be-38c6-4df1-a87d-9baa9e551955\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"74ad0c86-2d16-4f7a-9a52-9bf87ee943dc\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"[1.0, 1.1]\"],\"color\":[\"#f22c40\"],\"fill_alpha\":[0.6],\"height\":[1.0],\"label\":[\"[1.0, 1.1]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.07499999999999996],\"x\":[\"1.05\"],\"y\":[0.5]}},\"id\":\"99070434-8683-414b-acc7-2154b21380c3\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"1ca15bdf-f407-4282-9a89-3bb23c6b9809\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"6a4fdb98-e275-49c2-a53f-4920f1e243ab\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"2bb1c3ce-0233-42f3-b87e-70e089d0a0fe\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"plot\":null,\"text\":null},\"id\":\"26780f07-f264-4ebc-a91d-c436d5e85dc6\",\"type\":\"Title\"},{\"attributes\":{\"data_source\":{\"id\":\"7d34c7ce-0b4d-46b1-b52e-5060ef3e7fc8\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"05cca864-9908-4c5d-aff8-32be1d0c8a03\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"57407940-9fcc-40f2-a7be-93b285aae9e3\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"data_source\":{\"id\":\"c610f030-60ea-42d7-a6ec-4fe4ea68cee4\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"99f89837-6c58-43fe-a7e7-68f956bfc265\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"e8ee0648-accf-4eec-9d42-ee61ca622048\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(6.1, 6.3]\"],\"color\":[\"#407ee7\"],\"fill_alpha\":[0.6],\"height\":[1.0],\"label\":[\"(6.1, 6.3]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.20000000000000018],\"x\":[\"6.199999999999999\"],\"y\":[0.5]}},\"id\":\"0fb9b06c-0bc4-412d-8e8d-b76767245486\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"c7c713be-38c6-4df1-a87d-9baa9e551955\",\"type\":\"Rect\"},{\"attributes\":{\"data_source\":{\"id\":\"3706bae4-a773-47f0-a96e-f2c07adbd601\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"954264d8-6012-4c7d-b0ac-4425e2cbce75\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"99021687-61c6-4ef6-9f5b-9e8c33093b4d\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(3.5, 3.7]\"],\"color\":[\"#5ab738\"],\"fill_alpha\":[0.6],\"height\":[1.0],\"label\":[\"(3.5, 3.7]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.17499999999999982],\"x\":[\"3.6\"],\"y\":[0.5]}},\"id\":\"0e943dfb-b301-4af6-a2e9-d05397655d44\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"f0919d08-3312-4eb1-9203-d799f245e6ac\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"b7cc61ce-3be9-42d4-b7a7-f157df14105d\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"b7f5cce1-f6dd-47d2-80fd-bc12ae18401b\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"plot\":{\"id\":\"11045096-f9bf-453f-ab37-ae3b16279d10\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"8d91f9ba-606f-43d2-922a-4b4a89232e66\",\"type\":\"SaveTool\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(1.8, 1.9]\"],\"color\":[\"#f22c40\"],\"fill_alpha\":[0.6],\"height\":[2.0],\"label\":[\"(1.8, 1.9]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.07499999999999996],\"x\":[\"1.85\"],\"y\":[1.0]}},\"id\":\"b0bf96e6-5dd5-4f8c-8d9d-30840bc1ee49\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(4.2, 4.4]\"],\"color\":[\"#5ab738\"],\"fill_alpha\":[0.6],\"height\":[2.0],\"label\":[\"(4.2, 4.4]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.17499999999999982],\"x\":[\"4.300000000000001\"],\"y\":[1.0]}},\"id\":\"c2e1fe56-41c4-4a24-be85-01a0a088a228\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"29ff4a76-00e2-4dc4-a886-d6beb2e374d5\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"8d5eec3d-9456-45f0-9229-db8d6e680a31\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"1adfccc6-6cd0-428d-b448-55ad3556b10b\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"34da3089-0c20-43ba-b380-58674d133744\",\"type\":\"Rect\"},{\"attributes\":{\"data_source\":{\"id\":\"2b13a05d-9444-464f-b00d-72bbba77fde5\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"66ab54dc-c349-43fc-be95-13ac22b1cf16\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"6584ad63-c9cd-4c40-86c6-1089a9b60d0f\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"data_source\":{\"id\":\"a46bc75e-5dff-4c2e-9be9-579f4e9351df\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"26c90387-b300-4bf0-95c9-7412b64db554\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"14dc7813-2970-41f3-ba9c-6f6cda3970c9\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"data_source\":{\"id\":\"85fdd08b-006e-491b-89df-ea5277a32035\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"8260b0c1-d1d4-4ea6-b5c0-cede9d9b148b\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"76fdaea6-4520-4acd-a374-3898b7087165\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(1.4, 1.4]\"],\"color\":[\"#f22c40\"],\"fill_alpha\":[0.6],\"height\":[13.0],\"label\":[\"(1.4, 1.4]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.07499999999999996],\"x\":[\"1.4\"],\"y\":[6.5]}},\"id\":\"7526af5b-d39b-42d4-9f2b-c652c313dab2\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"74e11ba5-53d0-4bad-9aa3-380a3cf30f62\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"95219816-4281-446c-a402-62a6bb83995b\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"5f2942c5-803d-4c89-b331-f25318d170a9\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"95219816-4281-446c-a402-62a6bb83995b\",\"type\":\"Rect\"},{\"attributes\":{\"data_source\":{\"id\":\"a144c79a-986b-48f5-acb7-1d11f88ddb98\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"a6d20e7d-b9c8-404d-ab8d-8c230ab70714\",\"type\":\"Rect\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"4f214efb-7718-46f8-ad1d-db22eb046cd9\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"8351723e-ed98-42c1-96e4-c659fb25805d\",\"type\":\"Rect\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"05cca864-9908-4c5d-aff8-32be1d0c8a03\",\"type\":\"Rect\"},{\"attributes\":{\"fill_alpha\":{\"field\":\"fill_alpha\"},\"fill_color\":{\"field\":\"color\"},\"height\":{\"field\":\"height\",\"units\":\"data\"},\"line_color\":{\"field\":\"line_color\"},\"width\":{\"field\":\"width\",\"units\":\"data\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"6a4fdb98-e275-49c2-a53f-4920f1e243ab\",\"type\":\"Rect\"},{\"attributes\":{\"plot\":{\"id\":\"11045096-f9bf-453f-ab37-ae3b16279d10\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"28d55f5f-9ea8-4891-88b6-2cc48662a398\",\"type\":\"ResetTool\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"color\",\"label\",\"x\",\"line_color\",\"width\",\"height\",\"line_alpha\",\"fill_alpha\",\"y\"],\"data\":{\"chart_index\":[\"(1.7, 1.8]\"],\"color\":[\"#f22c40\"],\"fill_alpha\":[0.6],\"height\":[4.0],\"label\":[\"(1.7, 1.8]\"],\"line_alpha\":[1.0],\"line_color\":[\"black\"],\"width\":[0.07500000000000018],\"x\":[\"1.75\"],\"y\":[2.0]}},\"id\":\"9da9aea0-c0fd-4ecf-8f37-50d46903dd4e\",\"type\":\"ColumnDataSource\"}],\"root_ids\":[\"11045096-f9bf-453f-ab37-ae3b16279d10\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.2\"}};\n",
       "            var render_items = [{\"docid\":\"9a7ef9a1-1421-4082-99ad-6e5085ca7300\",\"elementid\":\"c195cf80-93de-4663-b5d3-f106a1051aec\",\"modelid\":\"11045096-f9bf-453f-ab37-ae3b16279d10\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "        });\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "  \n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === \"1\")) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === \"1\") {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (!force) {\n",
       "        var cell = $(\"#c195cf80-93de-4663-b5d3-f106a1051aec\").parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "  \n",
       "    }\n",
       "  \n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ejemplo de histograma de Petal.Length\n",
    "# solo 2 lineas de código\n",
    "hist = Histogram(iris, values=\"Petal.Length\", color=\"Species\",\n",
    "                 legend=\"top_right\", bins=12)\n",
    "show(hist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"plotdiv\" id=\"ab950219-9790-4c01-8a06-67fa0b5f89e7\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "  \n",
       "    var force = \"\";\n",
       "  \n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force !== \"\") {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "  \n",
       "  \n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force !== \"\") {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "  \n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "  \n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        Bokeh.$(\"#ab950219-9790-4c01-8a06-67fa0b5f89e7\").text(\"BokehJS successfully loaded.\");\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "  \n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "  \n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"ab950219-9790-4c01-8a06-67fa0b5f89e7\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'ab950219-9790-4c01-8a06-67fa0b5f89e7' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "  \n",
       "    var js_urls = [];\n",
       "  \n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        Bokeh.$(function() {\n",
       "            var docs_json = {\"759303cb-f221-4e8e-8eee-555189b6cd91\":{\"roots\":{\"references\":[{\"attributes\":{\"plot\":{\"id\":\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"a533ef92-e4f9-4bce-890a-609515944a02\",\"type\":\"ResetTool\"},{\"attributes\":{\"axis_label\":\"Petal.Width\",\"formatter\":{\"id\":\"92489249-e75e-4958-b198-0a9b2e7d50ec\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\",\"subtype\":\"Chart\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"323f04d2-87d9-4a08-83da-edb5d413b9c1\",\"type\":\"BasicTicker\"}},\"id\":\"55a820ac-900a-4faf-a84c-4553f36ae46b\",\"type\":\"LinearAxis\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"9e8e7715-81bd-4ddc-b910-0813b5ae8e15\",\"type\":\"PanTool\"},{\"id\":\"99cd1fc0-415a-46cd-9288-7ffd0765ee72\",\"type\":\"WheelZoomTool\"},{\"id\":\"23f70c92-cd53-46eb-8f92-058e7a2a82d9\",\"type\":\"BoxZoomTool\"},{\"id\":\"87804e55-93dc-4211-9a10-3c498e5fdefa\",\"type\":\"SaveTool\"},{\"id\":\"a533ef92-e4f9-4bce-890a-609515944a02\",\"type\":\"ResetTool\"},{\"id\":\"c56fbf00-fa8a-4f2b-9469-d3f0455c1b34\",\"type\":\"HelpTool\"}]},\"id\":\"dd9b0607-d230-4e42-9619-71e758f69c95\",\"type\":\"Toolbar\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.7},\"fill_color\":{\"value\":\"#5ab738\"},\"line_color\":{\"value\":\"#5ab738\"},\"size\":{\"units\":\"screen\",\"value\":8},\"x\":{\"field\":\"x_values\"},\"y\":{\"field\":\"y_values\"}},\"id\":\"491b68ae-f79e-4d5e-a703-35872def6516\",\"type\":\"Square\"},{\"attributes\":{\"data_source\":{\"id\":\"30098c0b-f052-45ff-b52d-38088ee33c6a\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"491b68ae-f79e-4d5e-a703-35872def6516\",\"type\":\"Square\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"3d1734f2-150d-4be1-858c-ea278bb06948\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"below\":[{\"id\":\"2f67b147-7fb4-4ee9-8d7f-3279e9fce20b\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"55a820ac-900a-4faf-a84c-4553f36ae46b\",\"type\":\"LinearAxis\"}],\"renderers\":[{\"id\":\"4e35114f-ab56-4e77-9fa2-066e58a4be2d\",\"type\":\"BoxAnnotation\"},{\"id\":\"55ea4a08-e14d-4986-a3c5-65bc3fe6184d\",\"type\":\"GlyphRenderer\"},{\"id\":\"3d1734f2-150d-4be1-858c-ea278bb06948\",\"type\":\"GlyphRenderer\"},{\"id\":\"da012400-a2ac-4c0c-b102-7bbd17e3104a\",\"type\":\"GlyphRenderer\"},{\"id\":\"caf01d4d-f6e4-41f9-9532-b3e14065bfc8\",\"type\":\"Legend\"},{\"id\":\"2f67b147-7fb4-4ee9-8d7f-3279e9fce20b\",\"type\":\"LinearAxis\"},{\"id\":\"55a820ac-900a-4faf-a84c-4553f36ae46b\",\"type\":\"LinearAxis\"},{\"id\":\"f249f8df-6378-4708-92c5-fc18f4d9ab0d\",\"type\":\"Grid\"},{\"id\":\"f7059893-dae5-48c5-8148-bcd6af6fbca1\",\"type\":\"Grid\"}],\"title\":{\"id\":\"85fccbff-a31c-4584-8d3d-3558c773eb3c\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"9390d8c4-2b02-4dfb-8a1a-b1b1d19fbc4a\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"dd9b0607-d230-4e42-9619-71e758f69c95\",\"type\":\"Toolbar\"},\"x_mapper_type\":\"auto\",\"x_range\":{\"id\":\"53cec0e4-d0da-4c18-bda6-63879ea04b5a\",\"type\":\"Range1d\"},\"y_mapper_type\":\"auto\",\"y_range\":{\"id\":\"0ad5466e-d73b-4137-9a97-b9993f242fcc\",\"type\":\"Range1d\"}},\"id\":\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\",\"subtype\":\"Chart\",\"type\":\"Plot\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.7},\"fill_color\":{\"value\":\"#407ee7\"},\"line_color\":{\"value\":\"#407ee7\"},\"size\":{\"units\":\"screen\",\"value\":8},\"x\":{\"field\":\"x_values\"},\"y\":{\"field\":\"y_values\"}},\"id\":\"0a5d9d12-b4c5-46f8-b0c9-7a31deba66b9\",\"type\":\"Triangle\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x_values\",\"y_values\"],\"data\":{\"Species\":[\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\",\"virginica\"],\"chart_index\":[{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"},{\"Species\":\"virginica\"}],\"x_values\":[6.0,5.1,5.9,5.6,5.8,6.6,4.5,6.3,5.8,6.1,5.1,5.3,5.5,5.0,5.1,5.3,5.5,6.7,6.9,5.0,5.7,4.9,6.7,4.9,5.7,6.0,4.8,4.9,5.6,5.8,6.1,6.4,5.6,5.1,5.6,6.1,5.6,5.5,4.8,5.4,5.6,5.1,5.1,5.9,5.7,5.2,5.0,5.2,5.4,5.1],\"y_values\":[2.5,1.9,2.1,1.8,2.2,2.1,1.7,1.8,1.8,2.5,2.0,1.9,2.1,2.0,2.4,2.3,1.8,2.2,2.3,1.5,2.3,2.0,2.0,1.8,2.1,1.8,1.8,1.8,2.1,1.6,1.9,2.0,2.2,1.5,1.4,2.3,2.4,1.8,1.8,2.1,2.4,2.3,1.9,2.3,2.5,2.3,1.9,2.0,2.3,1.8]}},\"id\":\"4f398212-e76d-4540-8a8f-92df566049cd\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x_values\",\"y_values\"],\"data\":{\"Species\":[\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\",\"setosa\"],\"chart_index\":[{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"},{\"Species\":\"setosa\"}],\"x_values\":[1.4,1.4,1.3,1.5,1.4,1.7,1.4,1.5,1.4,1.5,1.5,1.6,1.4,1.1,1.2,1.5,1.3,1.4,1.7,1.5,1.7,1.5,1.0,1.7,1.9,1.6,1.6,1.5,1.4,1.6,1.6,1.5,1.5,1.4,1.5,1.2,1.3,1.4,1.3,1.5,1.3,1.3,1.3,1.6,1.9,1.4,1.6,1.4,1.5,1.4],\"y_values\":[0.2,0.2,0.2,0.2,0.2,0.4,0.3,0.2,0.2,0.1,0.2,0.2,0.1,0.1,0.2,0.4,0.4,0.3,0.3,0.3,0.2,0.4,0.2,0.5,0.2,0.2,0.4,0.2,0.2,0.2,0.2,0.4,0.1,0.2,0.2,0.2,0.2,0.1,0.2,0.2,0.3,0.3,0.2,0.6,0.4,0.3,0.2,0.2,0.2,0.2]}},\"id\":\"a349c093-1e2c-406d-8164-6bec9f4d1db3\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"data_source\":{\"id\":\"a349c093-1e2c-406d-8164-6bec9f4d1db3\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"81044132-8f4c-4f2f-98c0-8cb4b96d8325\",\"type\":\"Circle\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"55ea4a08-e14d-4986-a3c5-65bc3fe6184d\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"4e35114f-ab56-4e77-9fa2-066e58a4be2d\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"plot\":{\"id\":\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"9e8e7715-81bd-4ddc-b910-0813b5ae8e15\",\"type\":\"PanTool\"},{\"attributes\":{\"plot\":null,\"text\":\"Tama\\u00f1o del petalo\"},\"id\":\"85fccbff-a31c-4584-8d3d-3558c773eb3c\",\"type\":\"Title\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.7},\"fill_color\":{\"value\":\"#f22c40\"},\"line_color\":{\"value\":\"#f22c40\"},\"size\":{\"units\":\"screen\",\"value\":8},\"x\":{\"field\":\"x_values\"},\"y\":{\"field\":\"y_values\"}},\"id\":\"81044132-8f4c-4f2f-98c0-8cb4b96d8325\",\"type\":\"Circle\"},{\"attributes\":{},\"id\":\"323f04d2-87d9-4a08-83da-edb5d413b9c1\",\"type\":\"BasicTicker\"},{\"attributes\":{\"overlay\":{\"id\":\"4e35114f-ab56-4e77-9fa2-066e58a4be2d\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"23f70c92-cd53-46eb-8f92-058e7a2a82d9\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"callback\":null,\"end\":2.74,\"start\":-0.13999999999999999},\"id\":\"0ad5466e-d73b-4137-9a97-b9993f242fcc\",\"type\":\"Range1d\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x_values\",\"y_values\"],\"data\":{\"Species\":[\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\",\"versicolor\"],\"chart_index\":[{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"},{\"Species\":\"versicolor\"}],\"x_values\":[4.7,4.5,4.9,4.0,4.6,4.5,4.7,3.3,4.6,3.9,3.5,4.2,4.0,4.7,3.6,4.4,4.5,4.1,4.5,3.9,4.8,4.0,4.9,4.7,4.3,4.4,4.8,5.0,4.5,3.5,3.8,3.7,3.9,5.1,4.5,4.5,4.7,4.4,4.1,4.0,4.4,4.6,4.0,3.3,4.2,4.2,4.2,4.3,3.0,4.1],\"y_values\":[1.4,1.5,1.5,1.3,1.5,1.3,1.6,1.0,1.3,1.4,1.0,1.5,1.0,1.4,1.3,1.4,1.5,1.0,1.5,1.1,1.8,1.3,1.5,1.2,1.3,1.4,1.4,1.7,1.5,1.0,1.1,1.0,1.2,1.6,1.5,1.6,1.5,1.3,1.3,1.3,1.2,1.4,1.2,1.0,1.3,1.2,1.3,1.3,1.1,1.3]}},\"id\":\"30098c0b-f052-45ff-b52d-38088ee33c6a\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"c36cace6-8b07-4c31-b641-01cd9060fd10\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"plot\":{\"id\":\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"c56fbf00-fa8a-4f2b-9469-d3f0455c1b34\",\"type\":\"HelpTool\"},{\"attributes\":{\"plot\":{\"id\":\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\",\"subtype\":\"Chart\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"7f586ebc-3e90-45c3-91f3-18145932fa14\",\"type\":\"BasicTicker\"}},\"id\":\"f249f8df-6378-4708-92c5-fc18f4d9ab0d\",\"type\":\"Grid\"},{\"attributes\":{\"data_source\":{\"id\":\"4f398212-e76d-4540-8a8f-92df566049cd\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"0a5d9d12-b4c5-46f8-b0c9-7a31deba66b9\",\"type\":\"Triangle\"},\"hover_glyph\":null,\"nonselection_glyph\":null,\"selection_glyph\":null},\"id\":\"da012400-a2ac-4c0c-b102-7bbd17e3104a\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null,\"end\":7.49,\"start\":0.4099999999999999},\"id\":\"53cec0e4-d0da-4c18-bda6-63879ea04b5a\",\"type\":\"Range1d\"},{\"attributes\":{},\"id\":\"9390d8c4-2b02-4dfb-8a1a-b1b1d19fbc4a\",\"type\":\"ToolEvents\"},{\"attributes\":{},\"id\":\"92489249-e75e-4958-b198-0a9b2e7d50ec\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"plot\":{\"id\":\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"99cd1fc0-415a-46cd-9288-7ffd0765ee72\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"legends\":[[\"setosa\",[{\"id\":\"55ea4a08-e14d-4986-a3c5-65bc3fe6184d\",\"type\":\"GlyphRenderer\"}]],[\"versicolor\",[{\"id\":\"3d1734f2-150d-4be1-858c-ea278bb06948\",\"type\":\"GlyphRenderer\"}]],[\"virginica\",[{\"id\":\"da012400-a2ac-4c0c-b102-7bbd17e3104a\",\"type\":\"GlyphRenderer\"}]]],\"location\":\"top_left\",\"plot\":{\"id\":\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"caf01d4d-f6e4-41f9-9532-b3e14065bfc8\",\"type\":\"Legend\"},{\"attributes\":{\"plot\":{\"id\":\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\",\"subtype\":\"Chart\",\"type\":\"Plot\"}},\"id\":\"87804e55-93dc-4211-9a10-3c498e5fdefa\",\"type\":\"SaveTool\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\",\"subtype\":\"Chart\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"323f04d2-87d9-4a08-83da-edb5d413b9c1\",\"type\":\"BasicTicker\"}},\"id\":\"f7059893-dae5-48c5-8148-bcd6af6fbca1\",\"type\":\"Grid\"},{\"attributes\":{\"axis_label\":\"Petal.Length\",\"formatter\":{\"id\":\"c36cace6-8b07-4c31-b641-01cd9060fd10\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\",\"subtype\":\"Chart\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"7f586ebc-3e90-45c3-91f3-18145932fa14\",\"type\":\"BasicTicker\"}},\"id\":\"2f67b147-7fb4-4ee9-8d7f-3279e9fce20b\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"7f586ebc-3e90-45c3-91f3-18145932fa14\",\"type\":\"BasicTicker\"}],\"root_ids\":[\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.2\"}};\n",
       "            var render_items = [{\"docid\":\"759303cb-f221-4e8e-8eee-555189b6cd91\",\"elementid\":\"ab950219-9790-4c01-8a06-67fa0b5f89e7\",\"modelid\":\"ba86df0a-4ca1-46f5-b426-d8c77b0de1c5\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "        });\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "  \n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === \"1\")) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === \"1\") {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (!force) {\n",
       "        var cell = $(\"#ab950219-9790-4c01-8a06-67fa0b5f89e7\").parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "  \n",
       "    }\n",
       "  \n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ejemplo diagrama de dispersion entre Petal.Length y Petal.Width\n",
    "# solo 2 lineas de código\n",
    "disp = Scatter(iris, x='Petal.Length', y='Petal.Width', color='Species', \n",
    "            legend='top_left', marker='Species', title=\"Tamaño del petalo\")\n",
    "show(disp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Seaborn\n",
    "\n",
    "[Seaborn](https://stanford.edu/~mwaskom/software/seaborn/) tiene su énfasis en los gráficos estadísticos. Nos permite realizar fácilmente gráficos de regresión y de las principales distribuciones; pero donde realmente brilla [Seaborn](https://stanford.edu/~mwaskom/software/seaborn/) es en su capacidad de visualizar muchas características diferentes a la vez. Veamos algunos ejemplos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAECCAYAAADuGCyPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdf044110f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ejemplo gráfico de distribuciones\n",
    "x = np.random.normal(size=100)\n",
    "dist= sns.distplot(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "1       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "2       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "3       21.01  3.50    Male     No  Sun  Dinner     3\n",
       "4       23.68  3.31    Male     No  Sun  Dinner     2\n",
       "5       24.59  3.61  Female     No  Sun  Dinner     4"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Ejemplo gráfico regresión con tips dataset\n",
    "tips.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYQAAAERCAYAAAB7FtAjAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdf044b9160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "reg = sns.regplot(x=\"total_bill\", y=\"tip\", data=tips)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAALJCAYAAAA6dvUdAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdf043a6898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ejemplo pairplot con datase iris\n",
    "g = sns.pairplot(iris, hue=\"Species\", diag_kind=\"hist\")  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAoEAAADSCAYAAAA11hrIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRURERMqQGoEiIiIiZUiNQBEREZEy9P8BQZB48+nmYGIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdf03dfe7b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ejemplo FacetGrid con iris\n",
    "g = sns.FacetGrid(iris, col=\"Species\")\n",
    "g = g.map(plt.scatter, \"Petal.Length\", \"Petal.Width\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Folium\n",
    "\n",
    "Por último, veamos un ejemplo de como utilizar [Folium](https://folium.readthedocs.io/en/latest/). Ya que yo soy adepto al uso de la bicicleta para moverme por la ciudad, y muchas veces se hace difícil encontrar una bicicletería en donde poder encontrar repuestos o reparar la bicicleta; en este ejemplo vamos a crear un mapa interactivo del barrio de <a href=\"https://es.wikipedia.org/wiki/Palermo_(Buenos_Aires)\">Palermo</a> en donde vamos a marcar la ubicación de los negocios de bicicleterías. Esta información la podemos extraer del padrón que ofrece el [gobierno de la Ciudad de Buenos Aires](http://www.buenosaires.gob.ar/) en su [portal de datos](http://data.buenosaires.gob.ar/). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>WKT</th>\n",
       "      <th>ID</th>\n",
       "      <th>NOMBRE</th>\n",
       "      <th>DIRECCION</th>\n",
       "      <th>TELEFONO</th>\n",
       "      <th>EMAIL</th>\n",
       "      <th>WEB</th>\n",
       "      <th>MECANICA_S</th>\n",
       "      <th>HORARIO_DE</th>\n",
       "      <th>CALLE</th>\n",
       "      <th>ALTURA</th>\n",
       "      <th>DIRECCION_</th>\n",
       "      <th>BARRIO</th>\n",
       "      <th>COMUNA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POINT (-58.466041249451614 -34.557060215984805)</td>\n",
       "      <td>52</td>\n",
       "      <td>11 A FONDO</td>\n",
       "      <td>CONGRESO 2757</td>\n",
       "      <td>45421835</td>\n",
       "      <td>info@11afondo.com</td>\n",
       "      <td>HTTP://WWW.11AFONDO.COM</td>\n",
       "      <td>NO</td>\n",
       "      <td>LUN A VIE DE 10 A 14 Y DE 16 A 20/SAB DE 10 A 14</td>\n",
       "      <td>CONGRESO AV.</td>\n",
       "      <td>2757</td>\n",
       "      <td>CONGRESO AV. 2757</td>\n",
       "      <td>NUÑEZ</td>\n",
       "      <td>COMUNA 13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POINT (-58.41279876038783 -34.591915372813645)</td>\n",
       "      <td>32</td>\n",
       "      <td>AMERICAN BIKE</td>\n",
       "      <td>AV. CNEL. DIAZ 1664</td>\n",
       "      <td>48220889</td>\n",
       "      <td>info@americanbike.com.ar</td>\n",
       "      <td>HTTP://WWW.AMERICANBIKE.COM.AR/</td>\n",
       "      <td>SI</td>\n",
       "      <td>LUN A VIER DE 10 A 14 Y DE 15 A 20.30 / SAB DE 10 A 14 Y DE 15 A 20</td>\n",
       "      <td>DIAZ, CNEL. AV.</td>\n",
       "      <td>1664</td>\n",
       "      <td>DIAZ, CNEL. AV. 1664</td>\n",
       "      <td>PALERMO</td>\n",
       "      <td>COMUNA 14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POINT (-58.425646989945932 -34.580365554062418)</td>\n",
       "      <td>30</td>\n",
       "      <td>ANDINO BIKES</td>\n",
       "      <td>GUEMES 4818</td>\n",
       "      <td>47753677</td>\n",
       "      <td>andino_bike@hotmail.com</td>\n",
       "      <td>HTTP://WWW.ANDINOBIKE.COM.AR/</td>\n",
       "      <td>NO</td>\n",
       "      <td>LUN A VIER DE 9 A 19 / SAB DE 10:00 - 17:00</td>\n",
       "      <td>GUEMES</td>\n",
       "      <td>4818</td>\n",
       "      <td>GUEMES 4818</td>\n",
       "      <td>PALERMO</td>\n",
       "      <td>COMUNA 14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POINT (-58.437608880680997 -34.6045094278806)</td>\n",
       "      <td>107</td>\n",
       "      <td>BABE BIKES</td>\n",
       "      <td>WARNES 10</td>\n",
       "      <td>48549862</td>\n",
       "      <td>info@babebikes.com.ar</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WARNES</td>\n",
       "      <td>10</td>\n",
       "      <td>WARNES AV. 10</td>\n",
       "      <td>VILLA CRESPO</td>\n",
       "      <td>COMUNA 15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POINT (-58.439598908303168 -34.58547499220991)</td>\n",
       "      <td>118</td>\n",
       "      <td>BELGRAVIA TAILOR MADE BICYLES</td>\n",
       "      <td>BONPLAND 1459</td>\n",
       "      <td>1544291001</td>\n",
       "      <td>hola@belgravia.com.ar</td>\n",
       "      <td>WWW.FACEBOOK.COM/BELGRAVIABIKES</td>\n",
       "      <td>NO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BONPLAND</td>\n",
       "      <td>1459</td>\n",
       "      <td>BONPLAND 1459</td>\n",
       "      <td>PALERMO</td>\n",
       "      <td>COMUNA 14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               WKT   ID  \\\n",
       "0  POINT (-58.466041249451614 -34.557060215984805)   52   \n",
       "1   POINT (-58.41279876038783 -34.591915372813645)   32   \n",
       "2  POINT (-58.425646989945932 -34.580365554062418)   30   \n",
       "3    POINT (-58.437608880680997 -34.6045094278806)  107   \n",
       "4   POINT (-58.439598908303168 -34.58547499220991)  118   \n",
       "\n",
       "                          NOMBRE            DIRECCION    TELEFONO  \\\n",
       "0                     11 A FONDO        CONGRESO 2757    45421835   \n",
       "1                  AMERICAN BIKE  AV. CNEL. DIAZ 1664    48220889   \n",
       "2                   ANDINO BIKES          GUEMES 4818    47753677   \n",
       "3                     BABE BIKES            WARNES 10    48549862   \n",
       "4  BELGRAVIA TAILOR MADE BICYLES        BONPLAND 1459  1544291001   \n",
       "\n",
       "                      EMAIL                              WEB MECANICA_S  \\\n",
       "0         info@11afondo.com          HTTP://WWW.11AFONDO.COM         NO   \n",
       "1  info@americanbike.com.ar  HTTP://WWW.AMERICANBIKE.COM.AR/         SI   \n",
       "2   andino_bike@hotmail.com    HTTP://WWW.ANDINOBIKE.COM.AR/         NO   \n",
       "3     info@babebikes.com.ar                              NaN         NO   \n",
       "4     hola@belgravia.com.ar  WWW.FACEBOOK.COM/BELGRAVIABIKES         NO   \n",
       "\n",
       "                                                            HORARIO_DE  \\\n",
       "0                     LUN A VIE DE 10 A 14 Y DE 16 A 20/SAB DE 10 A 14   \n",
       "1  LUN A VIER DE 10 A 14 Y DE 15 A 20.30 / SAB DE 10 A 14 Y DE 15 A 20   \n",
       "2                          LUN A VIER DE 9 A 19 / SAB DE 10:00 - 17:00   \n",
       "3                                                                  NaN   \n",
       "4                                                                  NaN   \n",
       "\n",
       "             CALLE  ALTURA            DIRECCION_        BARRIO     COMUNA  \n",
       "0     CONGRESO AV.    2757     CONGRESO AV. 2757         NUÑEZ  COMUNA 13  \n",
       "1  DIAZ, CNEL. AV.    1664  DIAZ, CNEL. AV. 1664       PALERMO  COMUNA 14  \n",
       "2           GUEMES    4818           GUEMES 4818       PALERMO  COMUNA 14  \n",
       "3           WARNES      10         WARNES AV. 10  VILLA CRESPO  COMUNA 15  \n",
       "4         BONPLAND    1459         BONPLAND 1459       PALERMO  COMUNA 14  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dataset de bicicleterías de Ciudad de Buenos Aires\n",
    "# descargado desde http://data.buenosaires.gob.ar/dataset/bicicleterias\n",
    "bici = pd.read_csv('data/bicicleterias.csv', sep=';')\n",
    "bici.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# corregimos el campo de coordenadas del dataset.\n",
    "def coord(c):\n",
    "    coor = re.findall(r'-?\\d+\\.\\d{7}', c)\n",
    "    coords = [float(s) for s in coor]\n",
    "    return coords[::-1]\n",
    "\n",
    "bici['WKT'] = bici['WKT'].apply(coord)\n",
    "\n",
    "# filtramos solo las bicicleterías de palermo\n",
    "bici_palermo = bici[bici.BARRIO == 'PALERMO'][['WKT', 'NOMBRE']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# creamos el mapa con folium\n",
    "mapa = folium.Map(location=[-34.588889, -58.430556], zoom_start=13)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# agregamos los markers con el nombre de cada bicicletería.\n",
    "for index, row in bici_palermo.iterrows():\n",
    "    mapa.simple_marker(row['WKT'], \n",
    "                   popup=row['NOMBRE'], marker_color='red',\n",
    "                   marker_icon='info-sign')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><iframe src=\"data:text/html;base64,
        <!DOCTYPE html>
        <head>
            
        
            <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
        
            
        
            <script src="https://cdnjs.cloudflare.com/ajax/libs/leaflet/0.7.3/leaflet.js"></script>
        
        
        
            
        
            <script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.1/jquery.min.js"></script>
        
        
        
            
        
            <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
        
        
        
            
        
            <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.min.js"></script>
        
        
        
            
        
            <script src="https://cdnjs.cloudflare.com/ajax/libs/leaflet.markercluster/0.4.0/leaflet.markercluster-src.js"></script>
        
        
        
            
        
            <script src="https://cdnjs.cloudflare.com/ajax/libs/leaflet.markercluster/0.4.0/leaflet.markercluster.js"></script>
        
        
        
            
        
            <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/leaflet/0.7.3/leaflet.css" />
        
        
        
            
        
            <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css" />
        
        
        
            
        
            <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css" />
        
        
        
            
        
            <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.1.0/css/font-awesome.min.css" />
        
        
        
            
        
            <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css" />
        
        
        
            
        
            <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/leaflet.markercluster/0.4.0/MarkerCluster.Default.css" />
        
        
        
            
        
            <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/leaflet.markercluster/0.4.0/MarkerCluster.css" />
        
        
        
            
        
            <link rel="stylesheet" href="https://raw.githubusercontent.com/python-visualization/folium/master/folium/templates/leaflet.awesome.rotate.css" />
        
        
        
            
            <style>

            html, body {
                width: 100%;
                height: 100%;
                margin: 0;
                padding: 0;
                }

            #map {
                position:absolute;
                top:0;
                bottom:0;
                right:0;
                left:0;
                }
            </style>
            
        
            
            <style> #map_e01b9b9ef72d47fcbde9f91917546943 {
                position : relative;
                width : 100.0%;
                height: 100.0%;
                left: 0.0%;
                top: 0.0%;
                }
            </style>
        
        
        
        </head>
        <body>
            
        
            
            <div class="folium-map" id="map_e01b9b9ef72d47fcbde9f91917546943" ></div>
        
        
        
        </body>
        <script>
            
        
            

            var southWest = L.latLng(-90, -180);
            var northEast = L.latLng(90, 180);
            var bounds = L.latLngBounds(southWest, northEast);

            var map_e01b9b9ef72d47fcbde9f91917546943 = L.map('map_e01b9b9ef72d47fcbde9f91917546943', {
                                           center:[-34.588889,-58.430556],
                                           zoom: 13,
                                           maxBounds: bounds,
                                           layers: [],
                                           crs: L.CRS.EPSG3857
                                         });
            
        
        
            
            var tile_layer_c541cff4a0534f6cb2af4907c1381794 = L.tileLayer(
                'https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png',
                {
                    maxZoom: 18,
                    minZoom: 1,
                    attribution: 'Data by <a href="http://openstreetmap.org">OpenStreetMap</a>, under <a href="http://www.openstreetmap.org/copyright">ODbL</a>.',
                    detectRetina: false
                    }
                ).addTo(map_e01b9b9ef72d47fcbde9f91917546943);

        
        
            

            var marker_b9e39b74e3494859b30bc5fabd088364 = L.marker(
                [-34.5919153,-58.4127987],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_ae1c91557da94e949d5215a4c4a53128 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_b9e39b74e3494859b30bc5fabd088364.setIcon(icon_ae1c91557da94e949d5215a4c4a53128);
            
        
            
            var popup_2a1084c7107348e6bdba81e689ba5a21 = L.popup({maxWidth: '300'});

            
                var html_78ac0f7d333e42f286c9485687f4a19c = $('         <div id="html_78ac0f7d333e42f286c9485687f4a19c"                 style="width: 100.0%; height: 100.0%;">                 AMERICAN BIKE</div>                 ')[0];
                popup_2a1084c7107348e6bdba81e689ba5a21.setContent(html_78ac0f7d333e42f286c9485687f4a19c);
            

            marker_b9e39b74e3494859b30bc5fabd088364.bindPopup(popup_2a1084c7107348e6bdba81e689ba5a21);

            
        
        
            

            var marker_b1f8230b61524e2c8fe5a78550c570a1 = L.marker(
                [-34.5803655,-58.4256469],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_42ed9d058ca946e1895e25cb8e50bacd = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_b1f8230b61524e2c8fe5a78550c570a1.setIcon(icon_42ed9d058ca946e1895e25cb8e50bacd);
            
        
            
            var popup_aaed185903e6469c971cfd4e32411ce1 = L.popup({maxWidth: '300'});

            
                var html_42c4991906dc4eebbaf61824e4253e4b = $('         <div id="html_42c4991906dc4eebbaf61824e4253e4b"                 style="width: 100.0%; height: 100.0%;">                 ANDINO BIKES</div>                 ')[0];
                popup_aaed185903e6469c971cfd4e32411ce1.setContent(html_42c4991906dc4eebbaf61824e4253e4b);
            

            marker_b1f8230b61524e2c8fe5a78550c570a1.bindPopup(popup_aaed185903e6469c971cfd4e32411ce1);

            
        
        
            

            var marker_1448ee68ef7b4de8a10dad32d6a38724 = L.marker(
                [-34.5854749,-58.4395989],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_a8d17c93de4549dc8a779f73101ea91d = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_1448ee68ef7b4de8a10dad32d6a38724.setIcon(icon_a8d17c93de4549dc8a779f73101ea91d);
            
        
            
            var popup_ac46e6eb86e54fa18a47096f10dc4866 = L.popup({maxWidth: '300'});

            
                var html_01877ffc3c644d16af2c4b87d7e90519 = $('         <div id="html_01877ffc3c644d16af2c4b87d7e90519"                 style="width: 100.0%; height: 100.0%;">                 BELGRAVIA TAILOR MADE BICYLES</div>                 ')[0];
                popup_ac46e6eb86e54fa18a47096f10dc4866.setContent(html_01877ffc3c644d16af2c4b87d7e90519);
            

            marker_1448ee68ef7b4de8a10dad32d6a38724.bindPopup(popup_ac46e6eb86e54fa18a47096f10dc4866);

            
        
        
            

            var marker_0c5e8cd585b24de992d9c204b5dcf07f = L.marker(
                [-34.5952714,-58.4168278],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_b45d601852a24b7e899872dd2b3de9fd = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_0c5e8cd585b24de992d9c204b5dcf07f.setIcon(icon_b45d601852a24b7e899872dd2b3de9fd);
            
        
            
            var popup_8bdc36b848eb431fb36954b95fd8e780 = L.popup({maxWidth: '300'});

            
                var html_934390136360484dbffbbb87976ce002 = $('         <div id="html_934390136360484dbffbbb87976ce002"                 style="width: 100.0%; height: 100.0%;">                 BICICITY</div>                 ')[0];
                popup_8bdc36b848eb431fb36954b95fd8e780.setContent(html_934390136360484dbffbbb87976ce002);
            

            marker_0c5e8cd585b24de992d9c204b5dcf07f.bindPopup(popup_8bdc36b848eb431fb36954b95fd8e780);

            
        
        
            

            var marker_58ecfe3c577046f2b8058051907a87bb = L.marker(
                [-34.592305,-58.4256879],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_49688a17a5c548aeaefd3f92ed4e7b1c = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_58ecfe3c577046f2b8058051907a87bb.setIcon(icon_49688a17a5c548aeaefd3f92ed4e7b1c);
            
        
            
            var popup_12bb0696f5f3484da5bfe00a98b152fd = L.popup({maxWidth: '300'});

            
                var html_fcb91b1736ed469db61a09d16cf0eeca = $('         <div id="html_fcb91b1736ed469db61a09d16cf0eeca"                 style="width: 100.0%; height: 100.0%;">                 BICICLETAS ARAOZ</div>                 ')[0];
                popup_12bb0696f5f3484da5bfe00a98b152fd.setContent(html_fcb91b1736ed469db61a09d16cf0eeca);
            

            marker_58ecfe3c577046f2b8058051907a87bb.bindPopup(popup_12bb0696f5f3484da5bfe00a98b152fd);

            
        
        
            

            var marker_fbaa42b14ec74ed0a2b43055c51a231a = L.marker(
                [-34.5829444,-58.4267014],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_f73d7bf432c843d6bc9b64b857452449 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_fbaa42b14ec74ed0a2b43055c51a231a.setIcon(icon_f73d7bf432c843d6bc9b64b857452449);
            
        
            
            var popup_aa11b9549f8d45159577cf5ecf9fef76 = L.popup({maxWidth: '300'});

            
                var html_5e8051fa97e1411cb30b5c8fc2952ab0 = $('         <div id="html_5e8051fa97e1411cb30b5c8fc2952ab0"                 style="width: 100.0%; height: 100.0%;">                 BICICLETERIA ORENSE</div>                 ')[0];
                popup_aa11b9549f8d45159577cf5ecf9fef76.setContent(html_5e8051fa97e1411cb30b5c8fc2952ab0);
            

            marker_fbaa42b14ec74ed0a2b43055c51a231a.bindPopup(popup_aa11b9549f8d45159577cf5ecf9fef76);

            
        
        
            

            var marker_fb4f9b2bbda64fb2a14c1dc179de2970 = L.marker(
                [-34.5859087,-58.4423915],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_777c8365c89e43c39a3e35911b22ed0f = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_fb4f9b2bbda64fb2a14c1dc179de2970.setIcon(icon_777c8365c89e43c39a3e35911b22ed0f);
            
        
            
            var popup_51aa55d239f8485ca857eafe3191cbc9 = L.popup({maxWidth: '300'});

            
                var html_fd54b5c2f5b84d7e8946af1f631efefc = $('         <div id="html_fd54b5c2f5b84d7e8946af1f631efefc"                 style="width: 100.0%; height: 100.0%;">                 BICICLETERIA ORENSE</div>                 ')[0];
                popup_51aa55d239f8485ca857eafe3191cbc9.setContent(html_fd54b5c2f5b84d7e8946af1f631efefc);
            

            marker_fb4f9b2bbda64fb2a14c1dc179de2970.bindPopup(popup_51aa55d239f8485ca857eafe3191cbc9);

            
        
        
            

            var marker_f91d0b937d744901bbe6b82e361e97d1 = L.marker(
                [-34.5899427,-58.4298812],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_64d987bdfe574a0db7f06604528bb43c = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_f91d0b937d744901bbe6b82e361e97d1.setIcon(icon_64d987bdfe574a0db7f06604528bb43c);
            
        
            
            var popup_a9c217376f314144a3eea6dc4b809431 = L.popup({maxWidth: '300'});

            
                var html_c57e374538d544d383d533c3bdcfe0fe = $('         <div id="html_c57e374538d544d383d533c3bdcfe0fe"                 style="width: 100.0%; height: 100.0%;">                 BICIUP</div>                 ')[0];
                popup_a9c217376f314144a3eea6dc4b809431.setContent(html_c57e374538d544d383d533c3bdcfe0fe);
            

            marker_f91d0b937d744901bbe6b82e361e97d1.bindPopup(popup_a9c217376f314144a3eea6dc4b809431);

            
        
        
            

            var marker_bdc575267b824a1394fa9c91da0b071e = L.marker(
                [-34.5862359,-58.4159566],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_1342e215e1e9493aa068966c7485196c = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_bdc575267b824a1394fa9c91da0b071e.setIcon(icon_1342e215e1e9493aa068966c7485196c);
            
        
            
            var popup_b989d2b253504f999e3a81d0fc094e27 = L.popup({maxWidth: '300'});

            
                var html_e26d917b7e9a4874917dd3ed71308242 = $('         <div id="html_e26d917b7e9a4874917dd3ed71308242"                 style="width: 100.0%; height: 100.0%;">                 BLACK BIKE</div>                 ')[0];
                popup_b989d2b253504f999e3a81d0fc094e27.setContent(html_e26d917b7e9a4874917dd3ed71308242);
            

            marker_bdc575267b824a1394fa9c91da0b071e.bindPopup(popup_b989d2b253504f999e3a81d0fc094e27);

            
        
        
            

            var marker_521a5177a72f405eb84edf03631f894e = L.marker(
                [-34.5801394,-58.4140531],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_222b5ab9fb074a7ea2892c1402ef66d2 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_521a5177a72f405eb84edf03631f894e.setIcon(icon_222b5ab9fb074a7ea2892c1402ef66d2);
            
        
            
            var popup_b5120afa84044402a3139b672a49c9ab = L.popup({maxWidth: '300'});

            
                var html_1074b87487d6407c823316e6fa0dc322 = $('         <div id="html_1074b87487d6407c823316e6fa0dc322"                 style="width: 100.0%; height: 100.0%;">                 CANAGLIA (LAFINUR)</div>                 ')[0];
                popup_b5120afa84044402a3139b672a49c9ab.setContent(html_1074b87487d6407c823316e6fa0dc322);
            

            marker_521a5177a72f405eb84edf03631f894e.bindPopup(popup_b5120afa84044402a3139b672a49c9ab);

            
        
        
            

            var marker_2ac2eab002564ca49d946a67d65a60a5 = L.marker(
                [-34.5826065,-58.4400564],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_e375069440fb4e719b4a71ba3fe20559 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_2ac2eab002564ca49d946a67d65a60a5.setIcon(icon_e375069440fb4e719b4a71ba3fe20559);
            
        
            
            var popup_d6c3281479cf40ddafd82d44f3d8795c = L.popup({maxWidth: '300'});

            
                var html_421ef84a507d4426ab924ea07a602efe = $('         <div id="html_421ef84a507d4426ab924ea07a602efe"                 style="width: 100.0%; height: 100.0%;">                 HOLLYWOOD BIKES</div>                 ')[0];
                popup_d6c3281479cf40ddafd82d44f3d8795c.setContent(html_421ef84a507d4426ab924ea07a602efe);
            

            marker_2ac2eab002564ca49d946a67d65a60a5.bindPopup(popup_d6c3281479cf40ddafd82d44f3d8795c);

            
        
        
            

            var marker_1c8430ef770a4024a107610547f477de = L.marker(
                [-34.5818763,-58.4074446],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_6b36ee6b93764d3fa4c2c4787cb2c696 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_1c8430ef770a4024a107610547f477de.setIcon(icon_6b36ee6b93764d3fa4c2c4787cb2c696);
            
        
            
            var popup_06eac273fc31451b97561ee70402a81c = L.popup({maxWidth: '300'});

            
                var html_90a88e4a9988446d98edefd065dcf58b = $('         <div id="html_90a88e4a9988446d98edefd065dcf58b"                 style="width: 100.0%; height: 100.0%;">                 LUCKY BIKES</div>                 ')[0];
                popup_06eac273fc31451b97561ee70402a81c.setContent(html_90a88e4a9988446d98edefd065dcf58b);
            

            marker_1c8430ef770a4024a107610547f477de.bindPopup(popup_06eac273fc31451b97561ee70402a81c);

            
        
        
            

            var marker_ff13009f091d48ac9371b14e7ed5b7e0 = L.marker(
                [-34.5780059,-58.4309194],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_f77734955f2b42d4a9f2c43d381a525c = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_ff13009f091d48ac9371b14e7ed5b7e0.setIcon(icon_f77734955f2b42d4a9f2c43d381a525c);
            
        
            
            var popup_b9069bff56f7460ab3cbc9fcad83c177 = L.popup({maxWidth: '300'});

            
                var html_c4a5aaf228f94086bcfb8529b850d945 = $('         <div id="html_c4a5aaf228f94086bcfb8529b850d945"                 style="width: 100.0%; height: 100.0%;">                 MILLENIUM BIKE</div>                 ')[0];
                popup_b9069bff56f7460ab3cbc9fcad83c177.setContent(html_c4a5aaf228f94086bcfb8529b850d945);
            

            marker_ff13009f091d48ac9371b14e7ed5b7e0.bindPopup(popup_b9069bff56f7460ab3cbc9fcad83c177);

            
        
        
            

            var marker_56336a2597794a2f91a7b957dada5e8e = L.marker(
                [-34.584625,-58.4379089],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_d3a88a3ae49a4f50acd2bf4a96811c8e = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_56336a2597794a2f91a7b957dada5e8e.setIcon(icon_d3a88a3ae49a4f50acd2bf4a96811c8e);
            
        
            
            var popup_e24293c8d4d64f87b0d0d9335cadaee6 = L.popup({maxWidth: '300'});

            
                var html_b2edc1371c484d0ea657c99150a661db = $('         <div id="html_b2edc1371c484d0ea657c99150a661db"                 style="width: 100.0%; height: 100.0%;">                 MONOCHROME</div>                 ')[0];
                popup_e24293c8d4d64f87b0d0d9335cadaee6.setContent(html_b2edc1371c484d0ea657c99150a661db);
            

            marker_56336a2597794a2f91a7b957dada5e8e.bindPopup(popup_e24293c8d4d64f87b0d0d9335cadaee6);

            
        
        
            

            var marker_6481e2b08b3a43f48200ff288349905e = L.marker(
                [-34.5889148,-58.4315935],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_80d03459a84947ae9a20e65048d30c93 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_6481e2b08b3a43f48200ff288349905e.setIcon(icon_80d03459a84947ae9a20e65048d30c93);
            
        
            
            var popup_31088b1e36874f28961730ac5d538dd4 = L.popup({maxWidth: '300'});

            
                var html_d5d9a66c37b6401f982302de3d9f7321 = $('         <div id="html_d5d9a66c37b6401f982302de3d9f7321"                 style="width: 100.0%; height: 100.0%;">                 MUVIN</div>                 ')[0];
                popup_31088b1e36874f28961730ac5d538dd4.setContent(html_d5d9a66c37b6401f982302de3d9f7321);
            

            marker_6481e2b08b3a43f48200ff288349905e.bindPopup(popup_31088b1e36874f28961730ac5d538dd4);

            
        
        
            

            var marker_84679ed5e4f748aab3428a70ac570562 = L.marker(
                [-34.5847008,-58.4155972],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_7a55782edb9c405abe27ebf33250a449 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_84679ed5e4f748aab3428a70ac570562.setIcon(icon_7a55782edb9c405abe27ebf33250a449);
            
        
            
            var popup_12ed30e23e1241b9b2b6fba57d8f8802 = L.popup({maxWidth: '300'});

            
                var html_9002b94af56849c985f91d3e7ac70002 = $('         <div id="html_9002b94af56849c985f91d3e7ac70002"                 style="width: 100.0%; height: 100.0%;">                 NEW BIKES</div>                 ')[0];
                popup_12ed30e23e1241b9b2b6fba57d8f8802.setContent(html_9002b94af56849c985f91d3e7ac70002);
            

            marker_84679ed5e4f748aab3428a70ac570562.bindPopup(popup_12ed30e23e1241b9b2b6fba57d8f8802);

            
        
        
            

            var marker_f2425e3ccac848bebd05a01b18dcd71b = L.marker(
                [-34.5907058,-58.4249961],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_cb706b8565f244638ebe845cfd8fe39b = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_f2425e3ccac848bebd05a01b18dcd71b.setIcon(icon_cb706b8565f244638ebe845cfd8fe39b);
            
        
            
            var popup_eb07ed444e7842079612bb74960a3195 = L.popup({maxWidth: '300'});

            
                var html_8aed04c856744c14a21a18cde07e30c6 = $('         <div id="html_8aed04c856744c14a21a18cde07e30c6"                 style="width: 100.0%; height: 100.0%;">                 ONLY BIKES DE RODADOS LUCERN</div>                 ')[0];
                popup_eb07ed444e7842079612bb74960a3195.setContent(html_8aed04c856744c14a21a18cde07e30c6);
            

            marker_f2425e3ccac848bebd05a01b18dcd71b.bindPopup(popup_eb07ed444e7842079612bb74960a3195);

            
        
        
            

            var marker_4178fc3452cd4b2abb9f7994761de508 = L.marker(
                [-34.5813777,-58.425982],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_4084c3015c2240dca490d5543d52fb08 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_4178fc3452cd4b2abb9f7994761de508.setIcon(icon_4084c3015c2240dca490d5543d52fb08);
            
        
            
            var popup_b230a53ccb374ffcaa8618723ca3987d = L.popup({maxWidth: '300'});

            
                var html_3cd5e12cc83c48ce9f0ddb934a156171 = $('         <div id="html_3cd5e12cc83c48ce9f0ddb934a156171"                 style="width: 100.0%; height: 100.0%;">                 RODA2ORO</div>                 ')[0];
                popup_b230a53ccb374ffcaa8618723ca3987d.setContent(html_3cd5e12cc83c48ce9f0ddb934a156171);
            

            marker_4178fc3452cd4b2abb9f7994761de508.bindPopup(popup_b230a53ccb374ffcaa8618723ca3987d);

            
        
        
            

            var marker_e02798f7084d42779aed98906c34800d = L.marker(
                [-34.5858022,-58.436122],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_a44323d5535c447695a14fc549e7d825 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_e02798f7084d42779aed98906c34800d.setIcon(icon_a44323d5535c447695a14fc549e7d825);
            
        
            
            var popup_0756003a70e7479bb71a80206ce641ea = L.popup({maxWidth: '300'});

            
                var html_62c5ec866a344d3686d14ccd6c9f0b37 = $('         <div id="html_62c5ec866a344d3686d14ccd6c9f0b37"                 style="width: 100.0%; height: 100.0%;">                 ROUEN</div>                 ')[0];
                popup_0756003a70e7479bb71a80206ce641ea.setContent(html_62c5ec866a344d3686d14ccd6c9f0b37);
            

            marker_e02798f7084d42779aed98906c34800d.bindPopup(popup_0756003a70e7479bb71a80206ce641ea);

            
        
        
            

            var marker_b528f0b0abb643d9a7100c6d1bd3cc8f = L.marker(
                [-34.5858419,-58.4361678],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_a78c15585c6447a9b655442b399f32cb = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_b528f0b0abb643d9a7100c6d1bd3cc8f.setIcon(icon_a78c15585c6447a9b655442b399f32cb);
            
        
            
            var popup_6b61b6c5f8774d04a41d6085095a6b3e = L.popup({maxWidth: '300'});

            
                var html_04cca14c81154febb66d5abed1f97d95 = $('         <div id="html_04cca14c81154febb66d5abed1f97d95"                 style="width: 100.0%; height: 100.0%;">                 ROUEN</div>                 ')[0];
                popup_6b61b6c5f8774d04a41d6085095a6b3e.setContent(html_04cca14c81154febb66d5abed1f97d95);
            

            marker_b528f0b0abb643d9a7100c6d1bd3cc8f.bindPopup(popup_6b61b6c5f8774d04a41d6085095a6b3e);

            
        
        
            

            var marker_46da0d29d58a43a8a4b064d7cfbb4d06 = L.marker(
                [-34.5885901,-58.436033],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_a452c8dcba854f88bd770d1513eae2ee = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_46da0d29d58a43a8a4b064d7cfbb4d06.setIcon(icon_a452c8dcba854f88bd770d1513eae2ee);
            
        
            
            var popup_fb224f1588a147c38208e93b15434d52 = L.popup({maxWidth: '300'});

            
                var html_077cabe75d20498b87f820573d5122f9 = $('         <div id="html_077cabe75d20498b87f820573d5122f9"                 style="width: 100.0%; height: 100.0%;">                 SOHO BIKE</div>                 ')[0];
                popup_fb224f1588a147c38208e93b15434d52.setContent(html_077cabe75d20498b87f820573d5122f9);
            

            marker_46da0d29d58a43a8a4b064d7cfbb4d06.bindPopup(popup_fb224f1588a147c38208e93b15434d52);

            
        
        
            

            var marker_79c908f78752470e8c66e2b434186276 = L.marker(
                [-34.5646537,-58.4353238],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_8c852a71a7034ec1b728533ad9bc3dc7 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_79c908f78752470e8c66e2b434186276.setIcon(icon_8c852a71a7034ec1b728533ad9bc3dc7);
            
        
            
            var popup_26e6a7e1d9e94ed783c9e8dc3f477a54 = L.popup({maxWidth: '300'});

            
                var html_06663b8ba72641e1a77a777060bfab39 = $('         <div id="html_06663b8ba72641e1a77a777060bfab39"                 style="width: 100.0%; height: 100.0%;">                 SOLDANI CYCLING</div>                 ')[0];
                popup_26e6a7e1d9e94ed783c9e8dc3f477a54.setContent(html_06663b8ba72641e1a77a777060bfab39);
            

            marker_79c908f78752470e8c66e2b434186276.bindPopup(popup_26e6a7e1d9e94ed783c9e8dc3f477a54);

            
        
        
            

            var marker_0afb51d7d04d4b12abaaebb24ae6d8a0 = L.marker(
                [-34.5900407,-58.4239993],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_793ff04b586248158e2e68ce07dff2bc = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_0afb51d7d04d4b12abaaebb24ae6d8a0.setIcon(icon_793ff04b586248158e2e68ce07dff2bc);
            
        
            
            var popup_9c2e46f6521f47b1a5833e9e359c61b2 = L.popup({maxWidth: '300'});

            
                var html_d554e910f145470984d1d9cbc122e7f3 = $('         <div id="html_d554e910f145470984d1d9cbc122e7f3"                 style="width: 100.0%; height: 100.0%;">                 SOLDANI CYCLING</div>                 ')[0];
                popup_9c2e46f6521f47b1a5833e9e359c61b2.setContent(html_d554e910f145470984d1d9cbc122e7f3);
            

            marker_0afb51d7d04d4b12abaaebb24ae6d8a0.bindPopup(popup_9c2e46f6521f47b1a5833e9e359c61b2);

            
        
        
            

            var marker_8031bd00034e4b71a9879888e2786044 = L.marker(
                [-34.5811436,-58.4090271],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_efcb30a76ab5454c878e77e311e56a5e = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_8031bd00034e4b71a9879888e2786044.setIcon(icon_efcb30a76ab5454c878e77e311e56a5e);
            
        
            
            var popup_def617985d974f4baedf473824b21174 = L.popup({maxWidth: '300'});

            
                var html_fdd8e53a12f44df58e7161b4744a9f2e = $('         <div id="html_fdd8e53a12f44df58e7161b4744a9f2e"                 style="width: 100.0%; height: 100.0%;">                 TU HOGAR SUSTENTABLE</div>                 ')[0];
                popup_def617985d974f4baedf473824b21174.setContent(html_fdd8e53a12f44df58e7161b4744a9f2e);
            

            marker_8031bd00034e4b71a9879888e2786044.bindPopup(popup_def617985d974f4baedf473824b21174);

            
        
        
            

            var marker_0840be4ce59a4a44953004d1b99c6c4c = L.marker(
                [-34.5947856,-58.4227541],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_e01b9b9ef72d47fcbde9f91917546943);
            
        
            

                var icon_6c80c6fcfe3b4eb1ae9e11f45eb09e06 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_0840be4ce59a4a44953004d1b99c6c4c.setIcon(icon_6c80c6fcfe3b4eb1ae9e11f45eb09e06);
            
        
            
            var popup_835fc9ba08e4492fac37a7547903d5c1 = L.popup({maxWidth: '300'});

            
                var html_972c14d7f35046dc8a592f9a2afdfd4f = $('         <div id="html_972c14d7f35046dc8a592f9a2afdfd4f"                 style="width: 100.0%; height: 100.0%;">                 VIDA SANA BIKE</div>                 ')[0];
                popup_835fc9ba08e4492fac37a7547903d5c1.setContent(html_972c14d7f35046dc8a592f9a2afdfd4f);
            

            marker_0840be4ce59a4a44953004d1b99c6c4c.bindPopup(popup_835fc9ba08e4492fac37a7547903d5c1);

            
        
        
        
        </script>
        \" style=\"position:absolute;width:100%;height:100%;left:0;top:0;\"></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7fdf0435dcf8>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# visualizamos el mapa con los markers\n",
    "mapa"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Aquí concluye este artículo, ya no hay excusas para graficar sus datos, como vimos [Python](http://python.org/) cuenta con herramientas que son fáciles de usar y muy poderosas. A divertirse!\n",
    "\n",
    "Saludos!\n",
    "\n",
    "*Este post fue escrito utilizando IPython notebook. Pueden descargar este [notebook](https://github.com/relopezbriega/relopezbriega.github.io/blob/master/downloads/DataViz.ipynb) o ver su version estática en [nbviewer](http://nbviewer.ipython.org/github/relopezbriega/relopezbriega.github.io/blob/master/downloads/DataViz.ipynb).*"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}