viz_viz.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "caa9ab06-f9c7-4cb8-bc20-95a938cb5f73",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import numpy as np \n",
    "import matplotlib.pyplot as plt \n",
    "import seaborn as sb \n",
    "\n",
    "%matplotlib inline "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "93bb236a-e22c-4e94-bc8a-190382491910",
   "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>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(\"pokemon.csv\")\n",
    "\n",
    "pokemon.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a92547ac-733d-4578-8cb7-bc759cf91dac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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      "text/plain": [
       "[(0.12156862745098039, 0.4666666666666667, 0.7058823529411765),\n",
       " (1.0, 0.4980392156862745, 0.054901960784313725),\n",
       " (0.17254901960784313, 0.6274509803921569, 0.17254901960784313),\n",
       " (0.8392156862745098, 0.15294117647058825, 0.1568627450980392),\n",
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       " (0.7372549019607844, 0.7411764705882353, 0.13333333333333333),\n",
       " (0.09019607843137255, 0.7450980392156863, 0.8117647058823529)]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sb.color_palette()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "433d3ce0-0d19-4be0-8e10-3719d608bcb7",
   "metadata": {},
   "outputs": [],
   "source": [
    "base_color = sb.color_palette()[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f8cc596-7adb-4a01-abe0-6c6835f3a389",
   "metadata": {},
   "source": [
    "**I will choose the second one it's my favourite** "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ef83ee7e-52ad-4859-90d7-bac5923a58ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('int64')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pokemon.generation_id.dtype"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b79da88-001b-40d3-a1f8-bacdb2e801e1",
   "metadata": {},
   "source": [
    "**`generation_id` looks like it's an integer column though it's a categorical column** "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d9d68fa-f462-4982-ab0f-d89132b71624",
   "metadata": {},
   "source": [
    "## Now to our plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5d95261f-79f8-4fb8-98ac-e6ade8548272",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(data = pokemon, x = \"generation_id\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ff84fa1-eb63-4e3b-995e-36bbfa70c4f9",
   "metadata": {},
   "source": [
    "**Let's fix a few things**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "aa82ab5a-02cf-4991-a1c1-5b1a64758a83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(data = pokemon, x = \"generation_id\", color = base_color);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "64f176f0-64eb-4f0c-a87f-5e93f1683922",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "generation_id\n",
       "5    156\n",
       "1    151\n",
       "3    135\n",
       "4    107\n",
       "2    100\n",
       "7     86\n",
       "6     72\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pokemon.generation_id.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ba88af98-b7b9-41eb-b80a-3622a7332bcd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[5, 1, 3, 4, 2, 7, 6]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Order_ID = list(pokemon.generation_id.value_counts().index)\n",
    "Order_ID"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "85764c6f-3c50-4596-a35f-95d518c74413",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(data = pokemon, x = \"generation_id\", color = base_color, order = Order_ID);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e406ee2-db5b-435c-88f6-15a5a4f3856f",
   "metadata": {},
   "source": [
    "**Since our column is Norminal** "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77cd90f3-5603-40f6-b282-828fb6ca01b2",
   "metadata": {},
   "source": [
    "## Let's check out matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3068dc61-5b0f-4930-be8e-8bddd0a177fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = pokemon[\"generation_id\"].unique()\n",
    "\n",
    "y = pokemon[\"generation_id\"].value_counts(sort = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bb07275e-27b4-42b4-b92b-5c82aa481104",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1, 2, 3, 4, 5, 6, 7]),\n",
       " generation_id\n",
       " 1    151\n",
       " 2    100\n",
       " 3    135\n",
       " 4    107\n",
       " 5    156\n",
       " 6     72\n",
       " 7     86\n",
       " Name: count, dtype: int64)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x, y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7168f713-c124-4bcd-8eea-b058cb88bb89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(x, y)\n",
    "\n",
    "plt.xlabel(\"generation_id\")\n",
    "plt.ylabel(\"Counts\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ab135e3-a72c-46f4-ab08-52f3aef35af2",
   "metadata": {},
   "source": [
    "## Let's use another column "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1f448f17-aae6-4fd6-b3a7-4cb34f0a12cd",
   "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>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": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pokemon.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2c50f40c-0636-4495-acbd-9a1005a3a3a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('O')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pokemon.type_1.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d2207dbf-4770-4160-bd63-b993058e39e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='type_1', ylabel='count'>"
      ]
     },
     "execution_count": 16,
     "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": [
    "sb.countplot(data = pokemon, x = \"type_1\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a52d8e5-4b2d-4f16-8e49-ac0d07c2870c",
   "metadata": {},
   "source": [
    "**Let's clean it up abit**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0c23dcf8-8aae-43ca-946a-72cb6df74b47",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(data = pokemon, x = \"type_1\", color = base_color);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "22e8e13e-c2a8-45b9-8675-550a26b8f3e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type_1\n",
       "water       114\n",
       "normal      105\n",
       "grass        78\n",
       "bug          72\n",
       "fire         53\n",
       "psychic      53\n",
       "rock         46\n",
       "electric     40\n",
       "poison       34\n",
       "ground       32\n",
       "dark         29\n",
       "fighting     29\n",
       "ghost        27\n",
       "dragon       27\n",
       "steel        24\n",
       "ice          23\n",
       "fairy        18\n",
       "flying        3\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pokemon.type_1.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "da455035-4a0c-4ab2-b511-28ecefe0714e",
   "metadata": {},
   "outputs": [],
   "source": [
    "Order_type1 = pokemon.type_1.value_counts().index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5416ab00-824f-44b5-be7f-669b0134d6d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(data = pokemon, x = \"type_1\", color = base_color, order = Order_type1);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "886f2fde-8585-46e0-af4d-35d71974045e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(data = pokemon, x = \"type_1\", color = base_color, order = Order_type1)\n",
    "\n",
    "plt.xticks(rotation = 45);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5234c647-d723-4aca-9f4f-e1fc9862f831",
   "metadata": {},
   "source": [
    "**What if we change x to y as an argunts in seaborn** "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6ce19deb-2a32-4d70-a27c-2e06e09b9063",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='count', ylabel='type_1'>"
      ]
     },
     "execution_count": 22,
     "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": [
    "sb.countplot(data = pokemon,  y = \"type_1\", color = base_color, order = Order_type1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd2874b7-c549-4533-9af4-c1e057c9791a",
   "metadata": {},
   "source": [
    "**Nice we still convay the sam info but we changed out axis**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5f5879a-d6a3-4b0d-967f-5773bda14151",
   "metadata": {},
   "source": [
    "**It seems that our water and normal pokemon are quite common than flying pokemone**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bdbd2d5-096a-4fc2-a690-a8cbb8d275d8",
   "metadata": {},
   "source": [
    "## Relative vs Absolut Frequency "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d32903c9-835f-4f8c-abd8-a17ea2961dae",
   "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>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": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pokemon.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "02a1e02c-0914-4f27-8f99-5b9948ff49ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "pkm_types = pokemon.melt(id_vars = ['id','species'],\n",
    "                         value_vars = [\"type_1\", \"type_2\"],\n",
    "                         var_name = \"type_levels\", value_name = \"type\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61f656da-7074-4e0e-a0f3-d9f14c8f854b",
   "metadata": {},
   "source": [
    "**Let's see what is going on here**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "379f13fe-c92f-4d05-892f-8c8bfe80e176",
   "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>id</th>\n",
       "      <th>species</th>\n",
       "      <th>type_levels</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_levels   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": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pkm_types.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "37624e15-da63-4d6b-b2dc-99373f2a4058",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id               0\n",
       "species          0\n",
       "type_levels      0\n",
       "type           402\n",
       "dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pkm_types.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "8c933a6b-0eb6-4947-a4b4-d97fc367c2fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                   0\n",
       "species              0\n",
       "generation_id        0\n",
       "height               0\n",
       "weight               0\n",
       "base_experience      0\n",
       "type_1               0\n",
       "type_2             402\n",
       "hp                   0\n",
       "attack               0\n",
       "defense              0\n",
       "speed                0\n",
       "special-attack       0\n",
       "special-defense      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pokemon.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6737f29-ca09-4ba7-b39c-b520e31e9d8b",
   "metadata": {},
   "source": [
    "**That explains it**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1426fd52-ec7f-496c-b3df-647bfb592fcd",
   "metadata": {},
   "source": [
    "Let's drop the missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e3069686-cb8a-4402-bef8-59c33cac230a",
   "metadata": {},
   "outputs": [],
   "source": [
    "pkm_types = pkm_types.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2cf6c847-bb79-4d34-be31-09ce20e6e88a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id             0\n",
       "species        0\n",
       "type_levels    0\n",
       "type           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pkm_types.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f84da97e-641c-44f6-82e8-cd498354a795",
   "metadata": {},
   "source": [
    "**Great**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8d52cfe5-7886-49b4-aedc-78591aa0807b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original number of observations: 807 or pokemon type df observations 1212\n"
     ]
    }
   ],
   "source": [
    "print(f\"Original number of observations: {pokemon.shape[0]} or pokemon type df observations {pkm_types.shape[0]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47198aaa-1b3d-428f-8d6c-77918cca486b",
   "metadata": {},
   "source": [
    "**Wow we created more observations am not quite sure why seems we have double enteies** "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5e872e54-65dc-46c4-953a-466cf70be813",
   "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>id</th>\n",
       "      <th>species</th>\n",
       "      <th>type_levels</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>807</th>\n",
       "      <td>1</td>\n",
       "      <td>bulbasaur</td>\n",
       "      <td>type_2</td>\n",
       "      <td>poison</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     id    species type_levels    type\n",
       "0     1  bulbasaur      type_1   grass\n",
       "807   1  bulbasaur      type_2  poison"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pkm_types[pkm_types[\"id\"] == 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "21fb0c06-bc94-47d0-933c-ff488a0c7172",
   "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>id</th>\n",
       "      <th>species</th>\n",
       "      <th>type_levels</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\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>808</th>\n",
       "      <td>2</td>\n",
       "      <td>ivysaur</td>\n",
       "      <td>type_2</td>\n",
       "      <td>poison</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     id  species type_levels    type\n",
       "1     2  ivysaur      type_1   grass\n",
       "808   2  ivysaur      type_2  poison"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pkm_types[pkm_types[\"id\"] == 2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d93a5fe-83d1-47a0-8a7a-2a8bc5436a43",
   "metadata": {},
   "source": [
    "**Now I see it's because of our two columns which are now one new columns they now act like new Identifiers I guess I was new to the melt function**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a31d658a-d651-4edc-b2b9-9850be21df2e",
   "metadata": {},
   "source": [
    "## More info about melt function on a dataframe\n",
    "\n",
    "![Cat](To_use.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56a16cfe-de26-4944-8af3-e670447848b7",
   "metadata": {},
   "source": [
    "**A little sanity check** "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "08434de3-a140-49d6-8305-a8609647bde5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type_1\n",
       "water       114\n",
       "normal      105\n",
       "grass        78\n",
       "bug          72\n",
       "fire         53\n",
       "psychic      53\n",
       "rock         46\n",
       "electric     40\n",
       "poison       34\n",
       "ground       32\n",
       "dark         29\n",
       "fighting     29\n",
       "ghost        27\n",
       "dragon       27\n",
       "steel        24\n",
       "ice          23\n",
       "fairy        18\n",
       "flying        3\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pokemon.type_1.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7dc2671b-116f-4c9d-bc72-da4af672b939",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type_2\n",
       "flying      95\n",
       "poison      32\n",
       "ground      32\n",
       "fairy       29\n",
       "psychic     29\n",
       "fighting    25\n",
       "steel       23\n",
       "grass       19\n",
       "dragon      18\n",
       "water       17\n",
       "dark        17\n",
       "ghost       16\n",
       "rock        14\n",
       "fire        11\n",
       "ice         11\n",
       "electric     8\n",
       "bug          5\n",
       "normal       4\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pokemon.type_2.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbecfd8b-8b5c-4e68-8c09-3aa71ee1db68",
   "metadata": {},
   "source": [
    "**Visuals**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "88939921-7051-48d8-af34-b27eabda32d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "Order_type = pkm_types.type.value_counts().index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "27956f2b-0f81-4b0e-b054-f67955a1e9f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(data = pkm_types, y = \"type\", color = base_color, order = Order_type);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b53325e-f39a-43bf-9520-ab0b8b3ccd1e",
   "metadata": {},
   "source": [
    "**Seems like flying just got flying!, significant boost**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0bdeeb23-5e5d-4f68-9fba-9fd2e0aed397",
   "metadata": {},
   "source": [
    "# Checking proportions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "ed9c73d9-cb26-4022-9bbd-7678bca611da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1623296158612144"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type_counts = pkm_types.type.value_counts()\n",
    "Order_type = type_counts.index\n",
    "\n",
    "max_type = type_counts.iloc[0]\n",
    "n_Poke = pokemon.shape[0]\n",
    "max_prop = max_type / n_Poke\n",
    "max_prop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "16a8ef7e-e84c-4925-b10b-62bdd23c00c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.   0.02 0.04 0.06 0.08 0.1  0.12 0.14 0.16] >> ['0.00', '0.02', '0.04', '0.06', '0.08', '0.10', '0.12', '0.14', '0.16']\n"
     ]
    }
   ],
   "source": [
    "tick_prop = np.arange(0, max_prop, 0.02)\n",
    "\n",
    "tick_labes = [\"{:.2f}\".format(v) for v in tick_prop]\n",
    "\n",
    "print(tick_prop,\">>\",tick_labes) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "dd6d8db6-cddb-444a-936e-65e827f5b465",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(data = pkm_types, y = \"type\", color = base_color, order = Order_type)\n",
    "plt.xticks(tick_prop * n_Poke, tick_labes)\n",
    "plt.xlabel(\"Proportions\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c30f4b57-e171-4c31-b8d1-eeea1635aada",
   "metadata": {},
   "source": [
    "**Let's see matplotlib shine with it's felxibility using plt.text()**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "320b8970-50bb-4586-9cc3-7d49d69e8a15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import rcParams\n",
    "\n",
    "rcParams[\"figure.figsize\"] = 17,4\n",
    "\n",
    "sb.countplot(data = pkm_types, y = \"type\", color = base_color, order = Order_type)\n",
    "\n",
    "for i in range(type_counts.shape[0]):\n",
    "    counts = type_counts.iloc[i]\n",
    "    perc_str = \"{:.1f}%\".format(100*counts / n_Poke)\n",
    "    plt.text(counts + 2, i, perc_str, va = \"center\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fe069be-6502-40e8-982e-fbe10303677b",
   "metadata": {},
   "source": [
    "**Horizontal Bars**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "6fbacb8c-bff4-4355-bfb4-66cac471fad5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rcParams[\"figure.figsize\"] = 15, 5\n",
    "\n",
    "sb.countplot(data = pkm_types, x = \"type\", color = base_color, order = Order_type)\n",
    "\n",
    "locs, labels = plt.xticks(rotation = 90)\n",
    "type_counts = pkm_types.type.value_counts()\n",
    "\n",
    "for loc, label in zip(locs, labels):\n",
    "    counts = type_counts[label.get_text()]\n",
    "    perc_str = \"{:.1f} %\".format(100 * counts/n_Poke)\n",
    "    plt.text(loc, counts + 2,perc_str, ha = \"center\", color = \"black\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7aaa4bb1-347f-4233-9674-984f9708c872",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}