{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "65dbae75",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8ca1b1aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "fruits = pd.read_table('fruits.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3c9837a3",
   "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>fruit_label</th>\n",
       "      <th>fruit_name</th>\n",
       "      <th>fruit_subtype</th>\n",
       "      <th>mass</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>color_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>apple</td>\n",
       "      <td>granny_smith</td>\n",
       "      <td>192</td>\n",
       "      <td>8.4</td>\n",
       "      <td>7.3</td>\n",
       "      <td>0.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>apple</td>\n",
       "      <td>granny_smith</td>\n",
       "      <td>180</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>0.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>apple</td>\n",
       "      <td>granny_smith</td>\n",
       "      <td>176</td>\n",
       "      <td>7.4</td>\n",
       "      <td>7.2</td>\n",
       "      <td>0.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>86</td>\n",
       "      <td>6.2</td>\n",
       "      <td>4.7</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>84</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>0.79</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fruit_label fruit_name fruit_subtype  mass  width  height  color_score\n",
       "0            1      apple  granny_smith   192    8.4     7.3         0.55\n",
       "1            1      apple  granny_smith   180    8.0     6.8         0.59\n",
       "2            1      apple  granny_smith   176    7.4     7.2         0.60\n",
       "3            2   mandarin      mandarin    86    6.2     4.7         0.80\n",
       "4            2   mandarin      mandarin    84    6.0     4.6         0.79"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b1813198",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(59, 7)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "463d6dbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "fruit_name\n",
       "apple       19\n",
       "lemon       16\n",
       "mandarin     5\n",
       "orange      19\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits.groupby('fruit_name').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "55d208df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='fruit_name'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "counts = _\n",
    "counts.plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d17f7a69",
   "metadata": {},
   "outputs": [],
   "source": [
    "label_removed = fruits.drop('fruit_label', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5fb24329",
   "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>fruit_name</th>\n",
       "      <th>fruit_subtype</th>\n",
       "      <th>mass</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>color_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>apple</td>\n",
       "      <td>granny_smith</td>\n",
       "      <td>192</td>\n",
       "      <td>8.4</td>\n",
       "      <td>7.3</td>\n",
       "      <td>0.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>apple</td>\n",
       "      <td>granny_smith</td>\n",
       "      <td>180</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>0.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>apple</td>\n",
       "      <td>granny_smith</td>\n",
       "      <td>176</td>\n",
       "      <td>7.4</td>\n",
       "      <td>7.2</td>\n",
       "      <td>0.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>mandarin</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>86</td>\n",
       "      <td>6.2</td>\n",
       "      <td>4.7</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>mandarin</td>\n",
       "      <td>mandarin</td>\n",
       "      <td>84</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>0.79</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  fruit_name fruit_subtype  mass  width  height  color_score\n",
       "0      apple  granny_smith   192    8.4     7.3         0.55\n",
       "1      apple  granny_smith   180    8.0     6.8         0.59\n",
       "2      apple  granny_smith   176    7.4     7.2         0.60\n",
       "3   mandarin      mandarin    86    6.2     4.7         0.80\n",
       "4   mandarin      mandarin    84    6.0     4.6         0.79"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_removed.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "472432c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "mass              Axes(0.125,0.536818;0.352273x0.343182)\n",
       "width          Axes(0.547727,0.536818;0.352273x0.343182)\n",
       "height               Axes(0.125,0.125;0.352273x0.343182)\n",
       "color_score       Axes(0.547727,0.125;0.352273x0.343182)\n",
       "dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "label_removed.plot(kind='box', subplots=True, layout=(2,2), title='Variables', figsize=(12, 12))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5b75b573",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<Axes: title={'center': 'mass'}>,\n",
       "        <Axes: title={'center': 'width'}>],\n",
       "       [<Axes: title={'center': 'height'}>,\n",
       "        <Axes: title={'center': 'color_score'}>]], dtype=object)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "label_removed.hist(bins=30, figsize=(10, 10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "23494723",
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_names = ['mass', 'width', 'height', 'color_score']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "18fcdb3e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/b3/cjvms6c10k77tgv6k_rw3jbh0000gn/T/ipykernel_73793/3949518286.py:6: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed in 3.11. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap()`` or ``pyplot.get_cmap()`` instead.\n",
      "  cmap = cm.get_cmap('gnuplot')\n"
     ]
    }
   ],
   "source": [
    "X = fruits[feature_names]\n",
    "y = fruits['fruit_label']\n",
    "\n",
    "from matplotlib import cm\n",
    "\n",
    "cmap = cm.get_cmap('gnuplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "76640a7b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter = pd.plotting.scatter_matrix(X, c=y, marker='o', s=40, hist_kwds={'bins': 15}, cmap=cmap, figsize=(12,12))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "aaee746e",
   "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>mass</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>color_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>192</td>\n",
       "      <td>8.4</td>\n",
       "      <td>7.3</td>\n",
       "      <td>0.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>180</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>0.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>176</td>\n",
       "      <td>7.4</td>\n",
       "      <td>7.2</td>\n",
       "      <td>0.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86</td>\n",
       "      <td>6.2</td>\n",
       "      <td>4.7</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>84</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>0.79</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mass  width  height  color_score\n",
       "0   192    8.4     7.3         0.55\n",
       "1   180    8.0     6.8         0.59\n",
       "2   176    7.4     7.2         0.60\n",
       "3    86    6.2     4.7         0.80\n",
       "4    84    6.0     4.6         0.79"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "39d88398",
   "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>mass</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>color_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>59.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>59.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>163.118644</td>\n",
       "      <td>7.105085</td>\n",
       "      <td>7.693220</td>\n",
       "      <td>0.762881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>55.018832</td>\n",
       "      <td>0.816938</td>\n",
       "      <td>1.361017</td>\n",
       "      <td>0.076857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>76.000000</td>\n",
       "      <td>5.800000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>140.000000</td>\n",
       "      <td>6.600000</td>\n",
       "      <td>7.200000</td>\n",
       "      <td>0.720000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>158.000000</td>\n",
       "      <td>7.200000</td>\n",
       "      <td>7.600000</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>177.000000</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>8.200000</td>\n",
       "      <td>0.810000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>362.000000</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>10.500000</td>\n",
       "      <td>0.930000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             mass      width     height  color_score\n",
       "count   59.000000  59.000000  59.000000    59.000000\n",
       "mean   163.118644   7.105085   7.693220     0.762881\n",
       "std     55.018832   0.816938   1.361017     0.076857\n",
       "min     76.000000   5.800000   4.000000     0.550000\n",
       "25%    140.000000   6.600000   7.200000     0.720000\n",
       "50%    158.000000   7.200000   7.600000     0.750000\n",
       "75%    177.000000   7.500000   8.200000     0.810000\n",
       "max    362.000000   9.600000  10.500000     0.930000"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e0b2c0f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import MinMaxScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5687551d",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e9fd36e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = MinMaxScaler()\n",
    "X_train = scaler.fit_transform(X_train)\n",
    "X_test = scaler.transform(X_test)"
   ]
  }
 ],
 "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",
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