{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "cb7731e2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 178\n",
      "1 182\n",
      "2 177\n",
      "3 183\n",
      "4 181\n",
      "5 182\n",
      "6 181\n",
      "7 179\n",
      "8 174\n",
      "9 180\n",
      "[178 182 177 183 181 182 181 179 174 180]\n"
     ]
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.datasets import load_digits\n",
    "\n",
    "dataset = load_digits()\n",
    "X, y = dataset.data, dataset.target\n",
    "\n",
    "for class_name, class_count in zip(dataset.target_names, np.bincount(dataset.target)):\n",
    "    print(class_name,class_count)\n",
    "    \n",
    "print(np.bincount(dataset.target))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8631b0a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1797"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dataset.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3207328b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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