Bar_Chart_Practice.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In workspaces like this one, you will be able to practice visualization techniques you've seen in the course materials. In this particular workspace, you'll practice creating single-variable plots for categorical data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# prerequisite package imports\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sb\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "# solution script imports\n",
    "from solutions_univ import bar_chart_solution_1, bar_chart_solution_2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this workspace, you'll be working with this dataset comprised of attributes of creatures in the video game series Pokémon. The data was assembled from the database of information found in [this GitHub repository](https://github.com/veekun/pokedex/tree/master/pokedex/data/csv)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>species</th>\n",
       "      <th>generation_id</th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>base_experience</th>\n",
       "      <th>type_1</th>\n",
       "      <th>type_2</th>\n",
       "      <th>hp</th>\n",
       "      <th>attack</th>\n",
       "      <th>defense</th>\n",
       "      <th>speed</th>\n",
       "      <th>special-attack</th>\n",
       "      <th>special-defense</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>bulbasaur</td>\n",
       "      <td>1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>6.9</td>\n",
       "      <td>64</td>\n",
       "      <td>grass</td>\n",
       "      <td>poison</td>\n",
       "      <td>45</td>\n",
       "      <td>49</td>\n",
       "      <td>49</td>\n",
       "      <td>45</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>ivysaur</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>142</td>\n",
       "      <td>grass</td>\n",
       "      <td>poison</td>\n",
       "      <td>60</td>\n",
       "      <td>62</td>\n",
       "      <td>63</td>\n",
       "      <td>60</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>venusaur</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>236</td>\n",
       "      <td>grass</td>\n",
       "      <td>poison</td>\n",
       "      <td>80</td>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>charmander</td>\n",
       "      <td>1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>8.5</td>\n",
       "      <td>62</td>\n",
       "      <td>fire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39</td>\n",
       "      <td>52</td>\n",
       "      <td>43</td>\n",
       "      <td>65</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>charmeleon</td>\n",
       "      <td>1</td>\n",
       "      <td>1.1</td>\n",
       "      <td>19.0</td>\n",
       "      <td>142</td>\n",
       "      <td>fire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58</td>\n",
       "      <td>64</td>\n",
       "      <td>58</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id     species  generation_id  height  weight  base_experience type_1  \\\n",
       "0   1   bulbasaur              1     0.7     6.9               64  grass   \n",
       "1   2     ivysaur              1     1.0    13.0              142  grass   \n",
       "2   3    venusaur              1     2.0   100.0              236  grass   \n",
       "3   4  charmander              1     0.6     8.5               62   fire   \n",
       "4   5  charmeleon              1     1.1    19.0              142   fire   \n",
       "\n",
       "   type_2  hp  attack  defense  speed  special-attack  special-defense  \n",
       "0  poison  45      49       49     45              65               65  \n",
       "1  poison  60      62       63     60              80               80  \n",
       "2  poison  80      82       83     80             100              100  \n",
       "3     NaN  39      52       43     65              60               50  \n",
       "4     NaN  58      64       58     80              80               65  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pokemon = pd.read_csv('./data/pokemon.csv')\n",
    "pokemon.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Task 1**: There have been quite a few Pokémon introduced over the series' history. How many were introduced in each generation? Create a _bar chart_ of these frequencies using the 'generation_id' column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9dcd1cd0f0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9dcd342208>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# YOUR CODE HERE\n",
    "base_color = sb.color_palette()[0]\n",
    "\n",
    "# the question asks how many were introduced in each generation. sb.countplot() can acheive it\n",
    "sb.countplot(data=pokemon , x='generation_id' , color = base_color  )\n",
    "# here do not need to order it by counts because the bar categories are ordinal "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Task 2**: Each Pokémon species has one or two 'types' that play a part in its offensive and defensive capabilities. How frequent is each type? The code below creates a new dataframe that puts all of the type counts in a single column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>species</th>\n",
       "      <th>type_level</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>bulbasaur</td>\n",
       "      <td>type_1</td>\n",
       "      <td>grass</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>ivysaur</td>\n",
       "      <td>type_1</td>\n",
       "      <td>grass</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>venusaur</td>\n",
       "      <td>type_1</td>\n",
       "      <td>grass</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>charmander</td>\n",
       "      <td>type_1</td>\n",
       "      <td>fire</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>charmeleon</td>\n",
       "      <td>type_1</td>\n",
       "      <td>fire</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id     species type_level   type\n",
       "0   1   bulbasaur     type_1  grass\n",
       "1   2     ivysaur     type_1  grass\n",
       "2   3    venusaur     type_1  grass\n",
       "3   4  charmander     type_1   fire\n",
       "4   5  charmeleon     type_1   fire"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pkmn_types = pokemon.melt(id_vars = ['id','species'], \n",
    "                          value_vars = ['type_1', 'type_2'], \n",
    "                          var_name = 'type_level', value_name = 'type').dropna()\n",
    "pkmn_types.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Your task is to use this dataframe to create a _relative frequency_ plot of the proportion of Pokémon with each type, _sorted_ from most frequent to least. **Hint**: The sum across bars should be greater than 100%, since many Pokémon have two types. Keep this in mind when considering a denominator to compute relative frequencies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'proportion')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9dccfb9710>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "#base_color = sb.color_palette()[0]\n",
    "#sb.countplot( data = pkmn_types , y = 'type',color=base_color)\n",
    "# the above code works ,just it calculate the counts not proportion\n",
    "\n",
    "\n",
    "# get order of bars by frequency \n",
    "type_counts = pkmn_types['type'].value_counts() # type_counts : ordered by frequency \n",
    "type_order = type_counts.index #type_order: each count's respond type\n",
    "\n",
    "\n",
    "# compute the largest proportion   max frequency / total unique species\n",
    "num_pokemon = pkmn_types['species'].unique().shape[0] # .shape gives (807,) so need to access 0 index\n",
    "max_type_count = type_counts[0] # get the first type count \n",
    "max_prop = max_type_count / num_pokemon\n",
    "\n",
    "\n",
    "# establishb tick locations and create plots \n",
    "tick_props = np.arange(0,max_prop , 0.02)\n",
    "tick_names = ['{:0.2f}'.format(v) for v in tick_props]\n",
    "\n",
    "base_color = sb.color_palette()[0]\n",
    "sb.countplot( data = pkmn_types , y = 'type',color=base_color, order = type_order)\n",
    "# too many types, use y axis is easier to list \n",
    "plt.xticks( tick_props*num_pokemon , tick_names )\n",
    "plt.xlabel('proportion')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}