sitc/ml21/visualization/02_Comparison_Charts.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "![](images/EscUpmPolit_p.gif \"UPM\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "# Course Notes for Learning Intelligent Systems"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Department of Telematic Engineering Systems, Universidad Politécnica de Madrid, © Carlos A. Iglesias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "## [Introduction to  Visualization](00_Intro_Visualization.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# Comparison charts\n",
    "Charts for comparing  data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "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>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>0</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>1</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>2</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
    "\n",
    "df = sns.load_dataset('tips')\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Countplot\n",
    "Distribution of values of a categorical variable. It can be seen like a histogram. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='sex', ylabel='count'>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='sex', data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='sex', ylabel='count'>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='sex', hue='day',  data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='count', ylabel='sex'>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We cannnot use both x and y in a countplot\n",
    "sns.countplot(y='sex', hue='time',  data=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Barplot\n",
    "Show point estimates and confidence intervals (ci) as rectangular bars. By default, ci = 95."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='sex', ylabel='tip'>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=\"sex\", y=\"tip\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='time', ylabel='tip'>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=\"time\", y=\"tip\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='day', ylabel='tip'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjcAAAGwCAYAAABVdURTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAk/UlEQVR4nO3df1BV953/8ddV5ILyw0oFr/ESsbbEYDUW2oqNStYGFzLWzrgdt+1EDaZdWmOMDHGLbpNpsllcQ1I0NRAnCnFsmszOVTeTGEeaAKb+aIPBrdlBN+lYoXrxZwLKJpcfnu8ffr2bGxDBwD33fng+Zu4M59xzLu/bU/WZc84Fh2VZlgAAAAwxzO4BAAAABhJxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjRNg9QLBdvXpVZ86cUWxsrBwOh93jAACAPrAsS5cvX9b48eM1bFjv52aGXNycOXNGbrfb7jEAAMAtaGpq0oQJE3rdZsjFTWxsrKRr/+PExcXZPA0AAOiL1tZWud1u/7/jvRlycXP9UlRcXBxxAwBAmOnLLSXcUAwAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADCKrXFTVlamadOm+X+JZWZmpt58880bbl9TUyOHw9Htcfz48SBODQAAQpmtvxV8woQJWr9+vSZPnixJeumll7Rw4ULV19crLS3thvudOHEi4Dd6jx07dtBnBQDAbqtWrdL58+clXfu3b+PGjTZPFJpsjZsFCxYELD/11FMqKyvT4cOHe42bxMREjR49epCnAwAgtJw/f15nz561e4yQFzL33HR1demVV15RW1ubMjMze912xowZcrlcmjdvnqqrq3vd1ufzqbW1NeABAADMZXvcHDt2TDExMXI6ncrPz9euXbt055139rity+XSli1b5PF4tHPnTqWmpmrevHnav3//DV+/uLhY8fHx/ofb7R6stwIAAEKAw7Isy84B2tvb1djYqI8//lgej0cvvviiamtrbxg4n7dgwQI5HA699tprPT7v8/nk8/n8y62trXK73WppaQm4bwcAgFD3ox/9yH9ZKikpSS+//LLNEwVPa2ur4uPj+/Tvt6333EhSZGSk/4bijIwMvfvuu9q4caNeeOGFPu0/c+ZM7dix44bPO51OOZ3OAZkVAACEPtsvS32eZVkBZ1pupr6+Xi6XaxAnAgAA4cTWMzdr165VTk6O3G63Ll++rFdeeUU1NTXau3evJKmoqEinT5/W9u3bJUmlpaWaOHGi0tLS1N7erh07dsjj8cjj8dj5NgAAQAixNW7Onj2r+++/X16vV/Hx8Zo2bZr27t2re++9V5Lk9XrV2Njo3769vV2FhYU6ffq0oqOjlZaWpjfeeEO5ubl2vQUAABBibL+hONj6c0MSAAChhBuK+/bvd8jdcwMAAPBFEDcAAMAoxA0AADAKcQMAAIxC3AAAAKPY/hOKAQC3btWqVTp//rwkaezYsdq4caPNEwH2I24AIIydP3/e/9FgANdwWQoAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABG4dcvAACGlNo5c+0e4ZZ9GjFccjiufd3cHNbvRZLm7q8dlNflzA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMAqflgIMs2rVKp0/f16SNHbsWG3cuNHmiQAguIgbwDDnz5/X2bNn7R4DAGzDZSkAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUfghfkMAP7EWADCUEDdDAD+xFgAwlHBZCgAAGIW4AQAARiFuAACAUYgbAABgFFvjpqysTNOmTVNcXJzi4uKUmZmpN998s9d9amtrlZ6erqioKE2aNEnl5eVBmhYAAIQDW+NmwoQJWr9+verq6lRXV6e/+7u/08KFC/Xf//3fPW5/8uRJ5ebmavbs2aqvr9fatWv18MMPy+PxBHlyAAAQqmz9KPiCBQsClp966imVlZXp8OHDSktL67Z9eXm5kpOTVVpaKkmaMmWK6urqVFJSokWLFgVjZAAAEOJC5p6brq4uvfLKK2pra1NmZmaP2xw6dEjZ2dkB6+bPn6+6ujp1dHT0uI/P51Nra2vAAwAAmMv2uDl27JhiYmLkdDqVn5+vXbt26c477+xx2+bmZiUlJQWsS0pKUmdnpy5cuNDjPsXFxYqPj/c/3G73gL8HAAAQOmz/CcWpqak6evSoPv74Y3k8Hi1dulS1tbU3DByHwxGwbFlWj+uvKyoqUkFBgX+5tbWVwAEQ4DvPfcfuEW6Zs9Uph679/dfc2hzW70WSDqw8YPcIIS3OkiTrM1+jJ7bHTWRkpCZPnixJysjI0LvvvquNGzfqhRde6LbtuHHj1NzcHLDu3LlzioiIUEJCQo+v73Q65XQ6B35wAACC7IGuLrtHCAu2X5b6PMuy5PP5enwuMzNTVVVVAev27dunjIwMjRgxIhjjAQCAEGdr3Kxdu1bvvPOO/vrXv+rYsWNat26dampq9OMf/1jStUtKS5Ys8W+fn5+vU6dOqaCgQA0NDdq2bZu2bt2qwsJCu94CAAAIMbZeljp79qzuv/9+eb1excfHa9q0adq7d6/uvfdeSZLX61VjY6N/+5SUFO3Zs0erV6/W5s2bNX78eG3atImPgQMAAD9b42br1q29Pl9ZWdlt3dy5c/Xee+8N0kQAACDchdw9NwAAAF8EcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCgRdg8QLtIf3W73CLcs7qMr/or1fnQlrN+LJB15eondIwAAQhhnbgAAgFGIGwAAYBTiBgAAGIV7boAeND7xdbtHuGWdHydIGv7/vz4T1u9FkpIfO2b3CADCDGduAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAUPgoOAGHMirZ6/BoYyogbAAhj7XPa7R4BCDlclgIAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRbI2b4uJiffOb31RsbKwSExP1/e9/XydOnOh1n5qaGjkcjm6P48ePB2lqAAAQymyNm9raWq1YsUKHDx9WVVWVOjs7lZ2drba2tpvue+LECXm9Xv/jq1/9ahAmBgAAoc7WX5y5d+/egOWKigolJibqyJEjmjNnTq/7JiYmavTo0YM4HQAACEchdc9NS0uLJGnMmDE33XbGjBlyuVyaN2+eqqurb7idz+dTa2trwAMAAJgrZOLGsiwVFBTo7rvv1tSpU2+4ncvl0pYtW+TxeLRz506lpqZq3rx52r9/f4/bFxcXKz4+3v9wu92D9RYAAEAIsPWy1Gc99NBD+vOf/6w//OEPvW6Xmpqq1NRU/3JmZqaamppUUlLS46WsoqIiFRQU+JdbW1sJHAAADBYSZ25Wrlyp1157TdXV1ZowYUK/9585c6Y++OCDHp9zOp2Ki4sLeAAAAHPZeubGsiytXLlSu3btUk1NjVJSUm7pderr6+VyuQZ4OnNcHTGqx68BADCRrXGzYsUKvfzyy/rP//xPxcbGqrm5WZIUHx+v6OhoSdcuK50+fVrbt2+XJJWWlmrixIlKS0tTe3u7duzYIY/HI4/HY9v7CHVXUnPsHgEAgKCxNW7KysokSVlZWQHrKyoqtGzZMkmS1+tVY2Oj/7n29nYVFhbq9OnTio6OVlpamt544w3l5uYGa2wAABDCbL8sdTOVlZUBy2vWrNGaNWsGaSIAABDuQuKGYgAAgIFC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCgRdg8AYGCNcXb1+DUADBXEDWCYtTM
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=\"day\", y=\"tip\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='day', ylabel='tip'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=\"day\", y=\"tip\", hue=\"sex\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='tip', ylabel='day'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=\"tip\", y=\"day\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='tip', ylabel='day'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=\"tip\", y=\"day\", hue='sex', data=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "# References\n",
    "[Seaborn](http://seaborn.pydata.org/index.html) documentation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "## Licence\n",
    "The notebook is freely licensed under under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/).  \n",
    "\n",
    "© Carlos A. Iglesias, Universidad Politécnica de Madrid."
   ]
  }
 ],
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