{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 19. 함수가 여러 값을 반환하는 경우 절대로 네 값 이상을 언패킹하지 말라"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_stats(numbers):\n",
    "    minimum = min(numbers)\n",
    "    maximum = max(numbers)\n",
    "    return minimum, maximum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "length = [63, 73, 72, 60, 67, 66, 71, 61, 72, 70]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "minimum, maximum = get_stats(length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "60"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "minimum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "73"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "maximum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_avg_ratio(numbers):\n",
    "    avg = sum(numbers) / len(numbers)\n",
    "    scaled = [x / avg for x in numbers]\n",
    "    scaled.sort(reverse=True)\n",
    "    return scaled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "longest, *middle, shortest = get_avg_ratio(length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0814814814814815"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "longest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1.0666666666666667,\n",
       " 1.0666666666666667,\n",
       " 1.0518518518518518,\n",
       " 1.037037037037037,\n",
       " 0.9925925925925926,\n",
       " 0.9777777777777777,\n",
       " 0.9333333333333333,\n",
       " 0.9037037037037037]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "middle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8888888888888888"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shortest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_stats(numbers):\n",
    "    minimum = min(numbers)\n",
    "    maximum = max(numbers)\n",
    "    count = len(numbers)\n",
    "    average = sum(numbers) / count\n",
    "    sorted_numbers = sorted(numbers)\n",
    "    middle = count // 2\n",
    "    if count % 2 == 0:\n",
    "        lower = sorted_numbers[middle - 1]\n",
    "        upper = sorted_numbers[middle]\n",
    "        median = (lower + upper) / 2\n",
    "    else:\n",
    "        median = sorted_numbers[middle]\n",
    "\n",
    "    return minimum, maximum, average, median, count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "minimum, maximum, average, median, count = get_stats(length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "60"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "minimum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "73"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "maximum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "67.5"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "average"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "68.5"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "median"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 기억해야 할 내용\n",
    "- 함수가 여러 값을 반환하기 위해 값들을 튜플에 넣어서 반환하고, 호출하는 쪽에서는 파이썬 언패킹 구문을 쓸 수 있다.\n",
    "- 함수가 반환한 여러 값을, 모든 값을 처리하는 별표 식을 사용해 언패킹할 수도 있다.\n",
    "- 언패킹 구문에 변수가 네개 이상 나오면 실수하기 쉬우므로 변수를 네 개 이상 사용하면 안 된다. 대식 작은 클래스를 반환하거나 namedtuple 인스턴스를 반환하라"
   ]
  }
 ],
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