NeuroIA/holland_viz.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"https://colab.research.google.com/github/institutohumai/cursos-python/blob/neuro/NeuroIA/holland_viz.ipynb\"> <img src='https://colab.research.google.com/assets/colab-badge.svg' /> </a>\n",
    "    <div align=\"center\"> Recordá abrir en una nueva pestaña </div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Corrección y Análisis en Orientación Vocacional\n",
    "\n",
    "En esta notebook analisamos y exploramos resultados del test Holland para orientación vocacional:\n",
    "\n",
    "- https://en.wikipedia.org/wiki/Strong_Interest_Inventory\n",
    "- https://openpsychometrics.org/tests/RIASEC/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "sns.set()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# My answers\n",
    "circuladas = '1,2,3,4,8,9,10,13,14,15,16,19,20,22,23,24,25,26,27,28,29,30,31,32,33,34,43,44,45,46,47,51,52,53,56,57,58,61,62,63,68,70,71,73,74,75,79,81,87,89,90'.split(',')\n",
    "categorias = 'R,I,A,S,E,C'.split(',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "puntajes = {cat: len([p for p in circuladas if int(p) in [i for i in range(categorias.index(cat) + 1, 91, 6)]]) for cat in categorias}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'R': 9, 'I': 11, 'A': 12, 'S': 10, 'E': 6, 'C': 3}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "puntajes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!-- TEASER_END -->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Some sample data\n",
    "\n",
    "nombres = 'mati, giuli, fer v, mago, consu, delfi, meli, fer p, peter'.split(', ')\n",
    "\n",
    "data = np.array([\n",
    "    [9, 11, 12, 10, 6, 3],\n",
    "    [12, 14, 12, 14, 12, 12],\n",
    "    [11, 9, 6, 8, 7, 7],\n",
    "    [1, 13, 6, 10, 7, 0],\n",
    "    [6, 7, 0, 7, 4, 8],\n",
    "    [2, 7, 4, 11, 7, 9],\n",
    "    [3, 9,7,13, 8, 9],\n",
    "    [3, 7, 5, 7, 6, 1],\n",
    "    [5, 6, 2, 4, 2, 2]] \n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(data, columns = categorias, index = nombres)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R</th>\n",
       "      <th>I</th>\n",
       "      <th>A</th>\n",
       "      <th>S</th>\n",
       "      <th>E</th>\n",
       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.8</td>\n",
       "      <td>9.2</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.3</td>\n",
       "      <td>6.6</td>\n",
       "      <td>5.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>2.7</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>12.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          R     I     A     S     E     C\n",
       "count   9.0   9.0   9.0   9.0   9.0   9.0\n",
       "mean    5.8   9.2   6.0   9.3   6.6   5.7\n",
       "std     4.0   2.9   4.0   3.2   2.7   4.2\n",
       "min     1.0   6.0   0.0   4.0   2.0   0.0\n",
       "25%     3.0   7.0   4.0   7.0   6.0   2.0\n",
       "50%     5.0   9.0   6.0  10.0   7.0   7.0\n",
       "75%     9.0  11.0   7.0  11.0   7.0   9.0\n",
       "max    12.0  14.0  12.0  14.0  12.0  12.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().round(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize':(15,5)})\n",
    "ax = df.plot.bar()\n",
    "\n",
    "for p in ax.patches:\n",
    "    ax.annotate(str(p.get_height()), (p.get_x() * 1.0, p.get_height() * 1.04), rotation=50)\n",
    "    \n",
    "plt.xticks(rotation=45);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": false
       },
       "data": [
        {
         "fill": "toself",
         "hovertemplate": "%{r}",
         "name": "mati",
         "r": [
          9,
          11,
          12,
          10,
          6,
          3
         ],
         "theta": [
          "R",
          "I",
          "A",
          "S",
          "E",
          "C"
         ],
         "type": "scatterpolar"
        },
        {
         "fill": "toself",
         "hovertemplate": "%{r}",
         "name": "giuli",
         "r": [
          12,
          14,
          12,
          14,
          12,
          12
         ],
         "theta": [
          "R",
          "I",
          "A",
          "S",
          "E",
          "C"
         ],
         "type": "scatterpolar"
        },
        {
         "fill": "toself",
         "hovertemplate": "%{r}",
         "name": "fer v",
         "r": [
          11,
          9,
          6,
          8,
          7,
          7
         ],
         "theta": [
          "R",
          "I",
          "A",
          "S",
          "E",
          "C"
         ],
         "type": "scatterpolar"
        },
        {
         "fill": "toself",
         "hovertemplate": "%{r}",
         "name": "mago",
         "r": [
          1,
          13,
          6,
          10,
          7,
          0
         ],
         "theta": [
          "R",
          "I",
          "A",
          "S",
          "E",
          "C"
         ],
         "type": "scatterpolar"
        },
        {
         "fill": "toself",
         "hovertemplate": "%{r}",
         "name": "consu",
         "r": [
          6,
          7,
          0,
          7,
          4,
          8
         ],
         "theta": [
          "R",
          "I",
          "A",
          "S",
          "E",
          "C"
         ],
         "type": "scatterpolar"
        },
        {
         "fill": "toself",
         "hovertemplate": "%{r}",
         "name": "delfi",
         "r": [
          2,
          7,
          4,
          11,
          7,
          9
         ],
         "theta": [
          "R",
          "I",
          "A",
          "S",
          "E",
          "C"
         ],
         "type": "scatterpolar"
        },
        {
         "fill": "toself",
         "hovertemplate": "%{r}",
         "name": "meli",
         "r": [
          3,
          9,
          7,
          13,
          8,
          9
         ],
         "theta": [
          "R",
          "I",
          "A",
          "S",
          "E",
          "C"
         ],
         "type": "scatterpolar"
        },
        {
         "fill": "toself",
         "hovertemplate": "%{r}",
         "name": "fer p",
         "r": [
          3,
          7,
          5,
          7,
          6,
          1
         ],
         "theta": [
          "R",
          "I",
          "A",
          "S",
          "E",
          "C"
         ],
         "type": "scatterpolar"
        },
        {
         "fill": "toself",
         "hovertemplate": "%{r}",
         "name": "peter",
         "r": [
          5,
          6,
          2,
          4,
          2,
          2
         ],
         "theta": [
          "R",
          "I",
          "A",
          "S",
          "E",
          "C"
         ],
         "type": "scatterpolar"
        }
       ],
       "layout": {
        "autosize": true,
        "polar": {
         "angularaxis": {
          "type": "category"
         },
         "radialaxis": {
          "autorange": true,
          "range": [
           0,
           14.4
          ],
          "type": "linear",
          "visible": false
         }
        },
        "showlegend": true,
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        }
       }
      },
      "image/png": "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",
      "text/html": [
       "<div>\n",
       "        \n",
       "        \n",
       "            <div id=\"0ccad1f7-2309-43e3-9917-b1444ddce70a\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
       "            <script type=\"text/javascript\">\n",
       "                require([\"plotly\"], function(Plotly) {\n",
       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    \n",
       "                if (document.getElementById(\"0ccad1f7-2309-43e3-9917-b1444ddce70a\")) {\n",
       "                    Plotly.newPlot(\n",
       "                        '0ccad1f7-2309-43e3-9917-b1444ddce70a',\n",
       "                        [{\"fill\": \"toself\", \"hovertemplate\": \"%{r}\", \"name\": \"mati\", \"r\": [9, 11, 12, 10, 6, 3], \"theta\": [\"R\", \"I\", \"A\", \"S\", \"E\", \"C\"], \"type\": \"scatterpolar\"}, {\"fill\": \"toself\", \"hovertemplate\": \"%{r}\", \"name\": \"giuli\", \"r\": [12, 14, 12, 14, 12, 12], \"theta\": [\"R\", \"I\", \"A\", \"S\", \"E\", \"C\"], \"type\": \"scatterpolar\"}, {\"fill\": \"toself\", \"hovertemplate\": \"%{r}\", \"name\": \"fer v\", \"r\": [11, 9, 6, 8, 7, 7], \"theta\": [\"R\", \"I\", \"A\", \"S\", \"E\", \"C\"], \"type\": \"scatterpolar\"}, {\"fill\": \"toself\", \"hovertemplate\": \"%{r}\", \"name\": \"mago\", \"r\": [1, 13, 6, 10, 7, 0], \"theta\": [\"R\", \"I\", \"A\", \"S\", \"E\", \"C\"], \"type\": \"scatterpolar\"}, {\"fill\": \"toself\", \"hovertemplate\": \"%{r}\", \"name\": \"consu\", \"r\": [6, 7, 0, 7, 4, 8], \"theta\": [\"R\", \"I\", \"A\", \"S\", \"E\", \"C\"], \"type\": \"scatterpolar\"}, {\"fill\": \"toself\", \"hovertemplate\": \"%{r}\", \"name\": \"delfi\", \"r\": [2, 7, 4, 11, 7, 9], \"theta\": [\"R\", \"I\", \"A\", \"S\", \"E\", \"C\"], \"type\": \"scatterpolar\"}, {\"fill\": \"toself\", \"hovertemplate\": \"%{r}\", \"name\": \"meli\", \"r\": [3, 9, 7, 13, 8, 9], \"theta\": [\"R\", \"I\", \"A\", \"S\", \"E\", \"C\"], \"type\": \"scatterpolar\"}, {\"fill\": \"toself\", \"hovertemplate\": \"%{r}\", \"name\": \"fer p\", \"r\": [3, 7, 5, 7, 6, 1], \"theta\": [\"R\", \"I\", \"A\", \"S\", \"E\", \"C\"], \"type\": \"scatterpolar\"}, {\"fill\": \"toself\", \"hovertemplate\": \"%{r}\", \"name\": \"peter\", \"r\": [5, 6, 2, 4, 2, 2], \"theta\": [\"R\", \"I\", \"A\", \"S\", \"E\", \"C\"], \"type\": \"scatterpolar\"}],\n",
       "                        {\"polar\": {\"radialaxis\": {\"visible\": false}}, \"showlegend\": true, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}},\n",
       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('0ccad1f7-2309-43e3-9917-b1444ddce70a');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.offline as py\n",
    "import plotly.graph_objs as go\n",
    "from plotly.subplots import make_subplots\n",
    "\n",
    "data = [go.Scatterpolar(\n",
    "      r = df.iloc[i].values,\n",
    "      theta = df.columns,\n",
    "      fill = 'toself',\n",
    "      name = df.index[i],\n",
    "      hovertemplate = '%{r}'\n",
    "    ) for i in range(df.shape[0])]\n",
    "\n",
    "layout = go.Layout(\n",
    "  polar = dict(\n",
    "    radialaxis = dict(\n",
    "      visible = False,\n",
    "    )\n",
    "  ),\n",
    "  showlegend = True\n",
    ")\n",
    "\n",
    "fig = go.Figure(data=data, layout=layout)\n",
    "py.iplot(fig, filename = \"radar\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_person = 0\n",
    "serie = df.loc[:, list('AIRCES')].iloc[n_person]\n",
    "tipo = serie.idxmax()\n",
    "diferenciacion = serie.max() - serie.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": false
       },
       "data": [
        {
         "fill": "toself",
         "hoverlabel": {
          "font": {
           "size": 20
          }
         },
         "hovertemplate": "%{r}",
         "name": "mati",
         "r": [
          12,
          11,
          10,
          9,
          6,
          3
         ],
         "subplot": "polar",
         "theta": [
          "A",
          "I",
          "S",
          "R",
          "E",
          "C"
         ],
         "type": "scatterpolar"
        },
        {
         "hoverlabel": {
          "font": {
           "size": 20
          }
         },
         "hovertemplate": "%{y}",
         "marker": {
          "color": [
           12,
           11,
           10,
           9,
           6,
           3
          ],
          "colorscale": [
           [
            0,
            "rgb(247,251,255)"
           ],
           [
            0.125,
            "rgb(222,235,247)"
           ],
           [
            0.25,
            "rgb(198,219,239)"
           ],
           [
            0.375,
            "rgb(158,202,225)"
           ],
           [
            0.5,
            "rgb(107,174,214)"
           ],
           [
            0.625,
            "rgb(66,146,198)"
           ],
           [
            0.75,
            "rgb(33,113,181)"
           ],
           [
            0.875,
            "rgb(8,81,156)"
           ],
           [
            1,
            "rgb(8,48,107)"
           ]
          ]
         },
         "name": "mati",
         "type": "bar",
         "x": [
          "A",
          "I",
          "S",
          "R",
          "E",
          "C"
         ],
         "xaxis": "x",
         "y": [
          12,
          11,
          10,
          9,
          6,
          3
         ],
         "yaxis": "y"
        }
       ],
       "layout": {
        "autosize": true,
        "font": {
         "color": "#7f7f7f",
         "family": "Courier New, monospace",
         "size": 18
        },
        "polar": {
         "angularaxis": {
          "type": "category"
         },
         "domain": {
          "x": [
           0.55,
           1
          ],
          "y": [
           0,
           1
          ]
         },
         "radialaxis": {
          "autorange": true,
          "range": [
           0,
           12.342857142857143
          ],
          "type": "linear",
          "visible": false
         }
        },
        "showlegend": false,
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "font": {
          "size": 40
         },
         "text": "Diferenciación: 9 \n Tipo: A",
         "x": 0.5,
         "xref": "container"
        },
        "xaxis": {
         "anchor": "y",
         "autorange": true,
         "domain": [
          0,
          0.45
         ],
         "range": [
          -0.5,
          5.5
         ],
         "type": "category"
        },
        "yaxis": {
         "anchor": "x",
         "autorange": true,
         "domain": [
          0,
          1
         ],
         "range": [
          0,
          12.631578947368421
         ],
         "type": "linear"
        }
       }
      },
      "image/png": "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",
      "text/html": [
       "<div>\n",
       "        \n",
       "        \n",
       "            <div id=\"f56615e4-529c-4efd-b8d0-3014c087eac4\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
       "            <script type=\"text/javascript\">\n",
       "                require([\"plotly\"], function(Plotly) {\n",
       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    \n",
       "                if (document.getElementById(\"f56615e4-529c-4efd-b8d0-3014c087eac4\")) {\n",
       "                    Plotly.newPlot(\n",
       "                        'f56615e4-529c-4efd-b8d0-3014c087eac4',\n",
       "                        [{\"fill\": \"toself\", \"hoverlabel\": {\"font\": {\"size\": 20}}, \"hovertemplate\": \"%{r}\", \"name\": \"mati\", \"r\": [12, 11, 10, 9, 6, 3], \"subplot\": \"polar\", \"theta\": [\"A\", \"I\", \"S\", \"R\", \"E\", \"C\"], \"type\": \"scatterpolar\"}, {\"hoverlabel\": {\"font\": {\"size\": 20}}, \"hovertemplate\": \"%{y}\", \"marker\": {\"color\": [12, 11, 10, 9, 6, 3], \"colorscale\": [[0.0, \"rgb(247,251,255)\"], [0.125, \"rgb(222,235,247)\"], [0.25, \"rgb(198,219,239)\"], [0.375, \"rgb(158,202,225)\"], [0.5, \"rgb(107,174,214)\"], [0.625, \"rgb(66,146,198)\"], [0.75, \"rgb(33,113,181)\"], [0.875, \"rgb(8,81,156)\"], [1.0, \"rgb(8,48,107)\"]]}, \"name\": \"mati\", \"type\": \"bar\", \"x\": [\"A\", \"I\", \"S\", \"R\", \"E\", \"C\"], \"xaxis\": \"x\", \"y\": [12, 11, 10, 9, 6, 3], \"yaxis\": \"y\"}],\n",
       "                        {\"font\": {\"color\": \"#7f7f7f\", \"family\": \"Courier New, monospace\", \"size\": 18}, \"polar\": {\"domain\": {\"x\": [0.55, 1.0], \"y\": [0.0, 1.0]}, \"radialaxis\": {\"visible\": false}}, \"showlegend\": false, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"font\": {\"size\": 40}, \"text\": \"Diferenciaci\\u00f3n: 9 \\n Tipo: A\", \"x\": 0.5, \"xref\": \"container\"}, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 0.45]}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0]}},\n",
       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('f56615e4-529c-4efd-b8d0-3014c087eac4');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = make_subplots(rows=1, cols=2, \n",
    "                   specs=[[{\"type\": \"xy\"}, {\"type\": \"polar\"}]])\n",
    "\n",
    "fig.add_trace(\n",
    "    go.Scatterpolar(\n",
    "      r = serie.values,\n",
    "      theta = serie.index,\n",
    "      fill = 'toself',\n",
    "      name = serie.name,\n",
    "      hovertemplate = '%{r}',\n",
    "      hoverlabel = dict(font=dict(size=20)), \n",
    "     ),\n",
    "    row=1, col=2\n",
    ")\n",
    "\n",
    "serie.sort_values(ascending=False, inplace=True)\n",
    "\n",
    "fig.add_trace(\n",
    "    go.Bar(\n",
    "    x= serie.index, \n",
    "    y= serie.values, \n",
    "    hovertemplate = '%{y}',\n",
    "    hoverlabel = dict(font=dict(size=20)), \n",
    "    name = serie.name,\n",
    "    marker={'color':serie.values, 'colorscale': 'Blues'}\n",
    "    ),\n",
    "    row=1, col=1\n",
    ")\n",
    "\n",
    "fig.update_layout(\n",
    "    polar = dict(\n",
    "            radialaxis = dict(\n",
    "                       visible = False,\n",
    "                       )), \n",
    "    title = go.layout.Title(\n",
    "            text = f'Diferenciación: {diferenciacion} \\n Tipo: {tipo}',\n",
    "            xref = \"container\",\n",
    "            x=0.5),\n",
    "    title_font=dict(\n",
    "                size=40),\n",
    "    font=dict(family='Courier New, monospace', \n",
    "              size=18, \n",
    "              color='#7f7f7f'),\n",
    "    showlegend = False\n",
    "    )\n",
    "\n",
    "py.iplot(fig, filename='/home/matias/Matias/OVO/holland_plot.html')"
   ]
  }
 ],
 "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}