2장 퍼셉트론.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ad9e1d04",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "131ac878",
   "metadata": {},
   "source": [
    "### 퍼셉트론 구현"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "33053ea4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#AND\n",
    "def AND(x1 , x2):\n",
    "    w1, w2, theta = 0.5, 0.5, 0.7\n",
    "    tmp = x1*w1 + x2*w2\n",
    "    if tmp <=theta:\n",
    "        return 0\n",
    "    elif tmp > theta:\n",
    "        return 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c871b5b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "출력값은: 0\n",
      "출력값은: 0\n",
      "출력값은: 1\n",
      "출력값은: 0\n"
     ]
    }
   ],
   "source": [
    "and_list=np.array([0,1])\n",
    "for i in and_list:\n",
    "    a1 = AND(1, i) #1,0 1,1\n",
    "    a2 = AND(0, i) #0,0 0,1일때 값들\n",
    "    print('출력값은:', a1)\n",
    "    print('출력값은:', a2) #처음 내가 생각한 것"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7cf08708",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "array() takes from 1 to 2 positional arguments but 4 were given",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_15828\\3307210352.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m#강의 시 좋은 방법\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mand_list\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m#오류 수정 필요 2차원 어레이로 만들기\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mand_list\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mAND\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mi\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'->'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m#이렇게는 또 오류가 발생하네\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: array() takes from 1 to 2 positional arguments but 4 were given"
     ]
    }
   ],
   "source": [
    "#강의 시 좋은 방법\n",
    "and_list = np.array([0,0], [0,1], [1,0], [0,0]) #오류 수정 필요 2차원 어레이로 만들기\n",
    "for i in and_list:\n",
    "    y = AND(i[0], i[1])\n",
    "    print(str(i), '->', str(y)) #이렇게는 또 오류가 발생하네"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "98640317",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0, 0) -> 0\n",
      "(0, 1) -> 0\n",
      "(1, 0) -> 0\n",
      "(1, 1) -> 1\n"
     ]
    }
   ],
   "source": [
    "#강의 시 좋은 방법\n",
    "and_list = [(0,0), (0,1), (1,0), (1,1)]\n",
    "for i in and_list:\n",
    "    y = AND(i[0], i[1])\n",
    "    print(str(i), '->', str(y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "65f2b5e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 0, 0, 1]\n"
     ]
    }
   ],
   "source": [
    "and_list = np.array([[0,0], [0,1], [1,0], [1,1]])\n",
    "Y=[]\n",
    "for i in and_list:\n",
    "    y = AND(i[0], i[1])\n",
    "    Y.append(y)\n",
    "print(Y) #값들 리스트에 담기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0f134011",
   "metadata": {},
   "outputs": [],
   "source": [
    "x1 = [0,1] *2\n",
    "x2 = [0, 0, 1, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "da361990",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>y</th>\n",
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       "       y\n",
       "x1 x2   \n",
       "0  0   0\n",
       "1  0   0\n",
       "0  1   0\n",
       "1  1   1"
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     "execution_count": 8,
     "metadata": {},
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    }
   ],
   "source": [
    "#로직 데이터 프레임으로 구현\n",
    "AND_df=pd.DataFrame({\n",
    "    'x1' : x1,\n",
    "    'x2' : x2,\n",
    "    'y' : Y\n",
    "})\n",
    "AND_df = AND_df.set_index(['x1', 'x2'])\n",
    "AND_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a8e3d5fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#시각화 구현\n",
    "plt.figure(figsize=(8,6))\n",
    "plt.scatter(x=0, y=0, color = 'b', edgecolor='b', marker='o')\n",
    "plt.scatter(x=0, y=1, color = 'b', edgecolor='b', marker='o')\n",
    "plt.scatter(x=1, y=0, color='b', edgecolor='b')\n",
    "plt.scatter(x=1, y=1, color = 'r', edgecolors='r', marker = 's')\n",
    "plt.xticks(np.arange(0,3,1))\n",
    "plt.yticks(np.arange(0,3,1))\n",
    "plt.show()\n",
    "#위의 데이터 프레임을 봤을 때 1,1만 출력됨. 그렇게 만드는 직선은 어떻게 만들까? 여러가지 가능 #어떻게 4사분면 코드를 이렇게 작성함?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "fb7378fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w1 = 0.5\n",
    "w2 = 0.5\n",
    "b = -1*0.7\n",
    "#파라미터 처럼 모델을 보고 조정하는 값\n",
    "x1 = np.arange(0, 1.5 ,0.1) \n",
    "# b+w1*x1 + w2*x2 =0\n",
    "x2 = (-0.5*x1 + 0.7)/0.5 #이항\n",
    "#시각화 구현\n",
    "plt.figure(figsize=(8,6))\n",
    "plt.scatter(x=0, y=0, color = 'b', edgecolor='b', marker='o')\n",
    "plt.scatter(x=0, y=1, color = 'b', edgecolor='b', marker='o')\n",
    "plt.scatter(x=1, y=0, color='b', edgecolor='b')\n",
    "plt.scatter(x=1, y=1, color = 'r', edgecolors='r', marker = 's')\n",
    "x = np.arange(0, 10, 0.1)\n",
    "plt.fill_between(x1, x2, np.max(y),\n",
    "                 color=\"skyblue\", alpha=0.4)\n",
    "\n",
    "plt.plot(x1, x2, linestyle = '--', color = 'g')\n",
    "plt.xticks(np.arange(0,3,1))\n",
    "plt.yticks(np.arange(0,3,1))\n",
    "plt.grid()\n",
    "plt.show()\n",
    "#위의 데이터 프레임을 봤을 때 1,1만 출력됨. 그렇게 만드는 직선은 어떻게 만들까? 여러가지 가능 #어떻게 4사분면 코드를 이렇게 작성함?\n",
    "#부등호 영역 시각화 어케함 이것도 이상함."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9e2bcb0f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2560c2cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "#NAND\n",
    "#가중치와 편향 도입\n",
    "def NAND(x1, x2):\n",
    "    x = np.array([x1, x2])\n",
    "    w = np.array([-0.5, -0.5]) #이렇게 표현해도 가능\n",
    "    b = 0.7 #NAND는 가중치 편향에 -1곱한것과 같음\n",
    "    tmp = np.sum(x*w) + b #브로드 캐스트로 쉽게 가능\n",
    "    if tmp<=0:\n",
    "        return 0\n",
    "    else:\n",
    "        return 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b3e83cd7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#OR\n",
    "def OR(x1, x2):\n",
    "    x = np.array([x1, x2])\n",
    "    w = np.array([0.5, 0.5])\n",
    "    b = -0.2 #NAND는 가중치 편향에 -1곱한것과 같음\n",
    "    tmp = np.sum(x*w) + b #브로드 캐스트로 쉽게 가능\n",
    "    if tmp<=0:\n",
    "        return 0\n",
    "    else:\n",
    "        return 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e2d13b5f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "56a55960",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0, 0) -> 1\n",
      "(0, 1) -> 1\n",
      "(1, 0) -> 1\n",
      "(1, 1) -> 0\n"
     ]
    }
   ],
   "source": [
    "#NAND\n",
    "and_list = [(0,0), (0,1), (1,0), (1,1)]\n",
    "for i in and_list:\n",
    "    y = NAND(i[0], i[1])\n",
    "    print(str(i), '->', str(y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "abc5d45e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 1, 1, 0]\n"
     ]
    }
   ],
   "source": [
    "and_list = np.array([[0,0], [0,1], [1,0], [1,1]])\n",
    "Y=[]\n",
    "for i in and_list:\n",
    "    y = NAND(i[0], i[1])\n",
    "    Y.append(y)\n",
    "print(Y) #값들 리스트에 담기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "48027500",
   "metadata": {},
   "outputs": [],
   "source": [
    "x1 = [0,1] *2\n",
    "x2 = [0, 0, 1, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "253ccaba",
   "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></th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       y\n",
       "x1 x2   \n",
       "0  0   1\n",
       "1  0   1\n",
       "0  1   1\n",
       "1  1   0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NAND_df=pd.DataFrame({\n",
    "    'x1' : x1,\n",
    "    'x2' : x2,\n",
    "    'y' : Y\n",
    "})\n",
    "NAND_df = NAND_df.set_index(['x1', 'x2'])\n",
    "NAND_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "715afee2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w1 = -0.5\n",
    "w2 = -0.5\n",
    "b = 0.7\n",
    "#파라미터 처럼 모델을 보고 조정하는 값\n",
    "x1 = np.arange(0, 1.5 ,0.1) \n",
    "# b+w1*x1 + w2*x2 =0\n",
    "x2 = (0.5*x1 -0.7)/0.5*(-1) #이항 #역치기 때문에 -1곱하나 안곱하나 그래프는 똑같아\n",
    "#시각화 구현\n",
    "plt.figure(figsize=(8,6))\n",
    "plt.scatter(x=0, y=0, color = 'r', edgecolor='k', marker='s')\n",
    "plt.scatter(x=0, y=1, color = 'r', edgecolor='k', marker='s')\n",
    "plt.scatter(x=1, y=0, color='r', edgecolor='k', marker= 's')\n",
    "plt.scatter(x=1, y=1, color = 'b', edgecolors='b', marker = 'o')\n",
    "\n",
    "plt.fill_between(x1, x2,\n",
    "                 color=\"skyblue\", alpha=0.4)\n",
    "\n",
    "plt.plot(x1, x2, linestyle = '--', color = 'g')\n",
    "plt.xticks(np.arange(0,3,1))\n",
    "plt.yticks(np.arange(0,3,1))\n",
    "plt.grid()\n",
    "plt.show()\n",
    "#위의 데이터 프레임을 봤을 때 1,1만 출력됨. 그렇게 만드는 직선은 어떻게 만들까? 여러가지 가능 #어떻게 4사분면 코드를 이렇게 작성함?\n",
    "#부등호 영역 시각화 어케함 이것도 이상함."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a3854866",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "21b29f89",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0, 0) -> 0\n",
      "(0, 1) -> 1\n",
      "(1, 0) -> 1\n",
      "(1, 1) -> 1\n"
     ]
    }
   ],
   "source": [
    "#NAND\n",
    "and_list = [(0,0), (0,1), (1,0), (1,1)]\n",
    "for i in and_list:\n",
    "    y = OR(i[0], i[1])\n",
    "    print(str(i), '->', str(y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "41229401",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 1, 1]\n"
     ]
    }
   ],
   "source": [
    "and_list = np.array([[0,0], [0,1], [1,0], [1,1]])\n",
    "Y=[]\n",
    "for i in and_list:\n",
    "    y = OR(i[0], i[1])\n",
    "    Y.append(y)\n",
    "print(Y) #값들 리스트에 담기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "241acc98",
   "metadata": {},
   "outputs": [],
   "source": [
    "x1 = [0,1] *2\n",
    "x2 = [0, 0, 1, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "08decbfb",
   "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></th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       y\n",
       "x1 x2   \n",
       "0  0   0\n",
       "1  0   1\n",
       "0  1   1\n",
       "1  1   1"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "OR_df=NAND_df.drop('y', axis=1)\n",
    "OR_df['y'] = Y\n",
    "OR_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "df144b63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w1 = 0.5\n",
    "w2 = 0.5\n",
    "b = -0.2\n",
    "#파라미터 처럼 모델을 보고 조정하는 값\n",
    "x1 = np.arange(0, 2 ,0.1) \n",
    "# b+w1*x1 + w2*x2 =0\n",
    "x2 = (-0.5*x1 +0.2)/0.5 #이항 #역치기 때문에 -1곱하나 안곱하나 그래프는 똑같아\n",
    "#시각화 구현\n",
    "plt.figure(figsize=(8,6))\n",
    "plt.scatter(x=0, y=0, color = 'b', edgecolor='g', marker='o')\n",
    "plt.scatter(x=0, y=1, color = 'r', edgecolor='k', marker='s')\n",
    "plt.scatter(x=1, y=0, color='r', edgecolor='k', marker='s')\n",
    "plt.scatter(x=1, y=1, color = 'r', edgecolors='k', marker = 's')\n",
    "\n",
    "plt.fill_between(x1, x2,np.max(y),\n",
    "                 color=\"skyblue\", alpha=0.4)\n",
    "\n",
    "plt.plot(x1, x2, linestyle = '--', color = 'g')\n",
    "plt.xticks(np.arange(0,3,1))\n",
    "plt.yticks(np.arange(0,3,1))\n",
    "plt.grid()\n",
    "plt.show()\n",
    "#위의 데이터 프레임을 봤을 때 1,1만 출력됨. 그렇게 만드는 직선은 어떻게 만들까? 여러가지 가능 #어떻게 4사분면 코드를 이렇게 작성함?\n",
    "#부등호 영역 시각화 어케함 이것도 이상함."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e499e3d4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ce391515",
   "metadata": {},
   "outputs": [],
   "source": [
    "#XOR\n",
    "def XOR(x1, x2):\n",
    "    s1 = NAND(x1, x2)\n",
    "    s2 = OR(x1, x2)\n",
    "    y=AND(s1, s2)\n",
    "    return y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "08d64ea0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 0] -> 0\n",
      "[1 0] -> 1\n",
      "[0 1] -> 1\n",
      "[1 1] -> 0\n"
     ]
    }
   ],
   "source": [
    "for i in np.array([[0, 0], \n",
    "                    [1, 0], \n",
    "                    [0, 1], \n",
    "                    [1, 1]]):\n",
    "    y=XOR(i[0], i[1])\n",
    "    print(str(i), '->', str(y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "8594c349",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 1, 0]\n",
      "[1, 1, 1, 0]\n",
      "[0, 1, 1, 1]\n"
     ]
    }
   ],
   "source": [
    "#데이터 프레임으로 만들기\n",
    "and_list = np.array([[0,0], [0,1], [1,0], [1,1]])\n",
    "Y=[]\n",
    "S1= []\n",
    "S2 = []\n",
    "for i in and_list:\n",
    "    y = XOR(i[0], i[1])\n",
    "    s1 = NAND(i[0], i[1])\n",
    "    s2 = OR(i[0], i[1])\n",
    "    Y.append(y)\n",
    "    S1.append(s1)\n",
    "    S2.append(s2)\n",
    "print(Y) #값들 리스트에 담기\n",
    "print(S1)\n",
    "print(S2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "34a657fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "x1 = [0,1] *2\n",
    "x2 = [0, 0, 1, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "e9aab92c",
   "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></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
       "      <th>s1</th>\n",
       "      <th>s2</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             y\n",
       "x1 x2 s1 s2   \n",
       "0  0  1  0   0\n",
       "1  0  1  1   1\n",
       "0  1  1  1   1\n",
       "1  1  0  1   0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "XOR_df=pd.DataFrame({\n",
    "    'x1' : x1,\n",
    "    'x2' : x2,\n",
    "    's1' : S1,\n",
    "    's2' : S2,\n",
    "    'y' : Y\n",
    "})\n",
    "XOR_df = XOR_df.set_index(['x1', 'x2', 's1', 's2'])\n",
    "XOR_df #데이터 프레임 사이즈는 어떻게 조정하는가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "3049ea75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#시각화 구현\n",
    "plt.figure(figsize=(8,6))\n",
    "plt.scatter(x=0, y=0, color = 'b', edgecolor='b', marker='o')\n",
    "plt.scatter(x=0, y=1, color = 'r', edgecolor='r', marker='s')\n",
    "plt.scatter(x=1, y=0, color='r', edgecolor='r', marker = 's')\n",
    "plt.scatter(x=1, y=1, color = 'b', edgecolors='b', marker = 'o')\n",
    "plt.xticks(np.arange(0,3,1))\n",
    "plt.yticks(np.arange(0,3,1))\n",
    "plt.show()\n",
    "#직선으로는 포함될 수 없다. 빨간 점이 포함되려면 비선형 직선을 그릴수 있어야함"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "e78c2dc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "# 산점도 그리기\n",
    "fig = plt.figure(figsize=(8, 6))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "ax.scatter(0, 0, 0, color='b', marker='o')\n",
    "ax.scatter(0, 1, 0, color='r', marker='s')\n",
    "ax.scatter(1, 0, 0, color='r', marker='s')\n",
    "ax.scatter(1, 1, 0, color='b', marker='o')\n",
    "\n",
    "# 비선형 그래프 그리기\n",
    "x = np.linspace(-0.5, 1.5, 100)\n",
    "y = np.linspace(-0.5, 1.5, 100)\n",
    "x, y = np.meshgrid(x, y)\n",
    "z = -2 * (x - 0.5) ** 2 + 1.5 * (y - 0.5) ** 3\n",
    "\n",
    "ax.plot_surface(x, y, z, color='b')\n",
    "\n",
    "ax.set_xticks(np.arange(0, 3, 1))\n",
    "ax.set_yticks(np.arange(0, 3, 1))\n",
    "ax.set_zticks(np.arange(0, 3, 1))\n",
    "ax.set_xlabel('X')\n",
    "ax.set_ylabel('Y')\n",
    "ax.set_zlabel('Z')\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "b0f27430",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7zA5bnzXLNrIAXlO/vjRtWvC61X//W/L7XacCEC0oqkAe8/vtxX7yZClfPisBl1/uOhVwcs2aSW+9Jfl80htvSM884zoRgGhBUQXy2FNPScOG2Yv+xIl2XiXgde3bS0OH2viZZ6QhQ9zmARAdKKpAHnr9dem552z8xhvSrbe6zQNkRffuwdnU3r2lSZPc5gEQ+SiqQB6ZPt1e3CXp2Wel++5zmwfIjieflHr1snGXLtKcOS7TAIh0FFUgDyxaJN12m61Pvfde6YknXCcCssfnk1591U6sOHpUuvFGafVq16kARCqKKpDLfv1VatlSOnTIzkwdOtRe7IFwFRNj66vr1rULK1q0kLZscZ0KQCSiqAK5aMcOuy99xw677WfyZDvmBwh3BQtKH35ot6j9/rt0/fXSvn2uUwGINBRVIJccPGhXT65bJ1WsKH3yid3yA0SKEiXsIoASJaSlS6V27aS0NNepAEQSiiqQC/x+6c47pYULpaJF7UD/f/3LdSog9CpXlj76SCpQwN6M9e3rOhGASEJRBXLBCy9I771nj/mnT5fOP991IiD3XH659M47Nn79dWnkSLd5AEQOiioQYh98YEf4SHaw/1VXOY0D5Ik2baTnn7dxz57S11+7zQMgMlBUgRBatkzq1MnGvXtLd9/tNg+Ql/7v/+wGq7Q06aabpF9+cZ0IQLijqAIhsnWrbZ46cEBq0kR65RXXiYC85fNJY8dKdepIu3ZJN9wgpaS4TgUgnFFUgRA4dMgOPt+4UTrvPI6hQvQqWFCaMUM680xpzRqbYU1Pd50KQLiiqAI55PfbmrxFi6QzzrAd0EWLuk4FuFO2rJ2xWrCgHV/FTWwAsouiCuTQ6NH2uDMmxmZSzz3XdSLAvdq1pXHjbPzii7bJEACyiqIK5MCiRTabKkn9+knXXus2D+Al7doFz1Xt0kVavdppHABhiKIKZNOff0pt20pHj9rnhx92nQjwnpdesiPa9u2zddxsrgKQFRRVIBuOHpVuvlnavFmqVk0aP952PAM4VlycLYkpV076+Wepc2cpI8N1KgDhgqIKZMNDD0nz50sJCXbzVEKC60SAd5UqJU2bJuXPb5us+vVznQhAuKCoAlk0ebL02ms2njjRjqMCcGp16thNbZL0n/9IX3zhNg+A8EBRBbLg55+Dt0099pgd8A8gc7p2le66y45069DBls4AwKlQVIFMOnjQ1qXu3Ss1aCA9+6zrRED4GTJEqllT2rYteN0qAJwMRRXIpN69pRUrpJIlpXff5eYpIDsKFpTef18qUkSaN0966inXiQB4GUUVyIS337aD/X0+adIku3kHQPZUqSKNGWPjfv3s9ioAOBGKKnAaa9ZI995r4//8R2rc2G0eIBLceqvUvbuNO3aUNm50mweAN1FUgVMIrEs9cEC65hrpySddJwIix6BBUq1a0s6drFcFcGIUVeAUHnhAWrVKKl1aeucdKTbWdSIgcsTH23rVxETpm2+k555znQiA11BUgZP48ENp+HAbv/WWlVUAoXX22dKIETZ+/nm7SAMAAiiqwAn88Yd05502fvBBqUkTt3mASNa+ffBq1Q4dpN27XScC4BUUVeAf0tNtc8euXbZ+7oUXXCcCIt/rr0vnnGObqu65xy4FAACKKvAPAwZIX38tFS5s56Xmz+86ERD5EhLs6Le4OGnqVGnsWNeJAHgBRRX4m+++C+7sf/11O+8RQN6oUyf4BKN3b+mnn9zmAeAeRRX4//btk26/3R7933qr1KWL60RA9HnwQTur+MABW6965IjrRABcoqgC/9+DD0q//CKVL2+7kH0+14mA6BMTI735plSsmLR0KUdWAdGOogpImjVLGjnSxhMmSEWLukwDRLeyZYNHVvXrJy1a5DYPAHcoqoh6O3YEj6Lq00dq1MhpHACyG+E6dLAjqzp2lPbvd50IgAtxrgMAeWbdOmnv3mO+5PdL3R6ppD//PEPVKh9Wv37xjsIB+KehQ6W5c21JzkMP2QbH+fOlLVukMmWk+vW5LQ6IdD6/P3xPq0tNTVVSUpJSUlKUmJjoOg68bN26E27hn6jb1UkTFaej+k6XqdbPk6Vzz3UQEMCJfPmlba6SpOLFpZ07g79Xrpz02mtSmzZusgHInJz0NaeP/ufNm6eWLVuqbNmy8vl8mjFjhss4iGT/mEmVpGSVV08NlSQ9pWdUS8tO+H0A3LnmGqlFCxv/vaRKdoPcTTdJ06blfS4AecNpUd2/f78uvPBCDR061GUMRCG/pDs1TqlK0uX6Vo/qRdeRAJxAerq0fPmJfy/wPLBPH/s+AJHH6RrV5s2bq3nz5pn+/sOHD+vw4cN//To1NTU3YiEKjNbd+lKNVUAH9aY6K068ygFeNH++zZyejN9v167Ony9ddVWexQKQR8Jq13///v2VlJT010f58uVdR0IY+l0V9IAGSpL66f9URescJwJwMlu2hPb7AISXsCqqjz32mFJSUv762Lhxo+tICDN+SXdrtPYpQXX1jf6tIa4jATiFMmVC+30AwktYHU8VHx+v+HiOD0L2jVVXzVYTFdBBjdcdilWG60gATqF+fdvd/8cfwTWpf+fz2e/Xr5/32QDkvrCaUQVyIlnl1VeDJEkv6HEe+QNhIDbWjqCSTnytsd8vvfoq56kCkYqiiqjgL5KgezRKe5WoK7RQvfXaib8xISFvgwE4rTZtpKlTpTPPPP73GjbkHFUgkjl99L9v3z798ssvf/16/fr1+uGHH1SsWDFVqFDBYTJEmgnfnKvPdK7i82do/LtJij1r8fHflJDAYf+AR7VpI7VqFbyZavduqVcvu7nq44+l6693nRBAbnB6M9WcOXN09dVXH/f1zp07a8KECaf989xMhcz480+pWjV7YXvpJenhh10nAhAKDz0kvfKKrVFdvZoHIoBX5aSvcYUqIl67dtLkydLFF0vffy/FhdUWQgAnc+CAdMEF0m+/2ezqEA7xADwpbK9QBXLbxx9bSY2NlcaMoaQCkaRQIWnkSBsPHSp9+63bPABCj6KKiLV3r3TffTbu21eqVcttHgCh17ix1Lmz7f6/+27pyBHXiQCEEkUVEevxx6VNm6Szz5aeftp1GgC5ZeBAqWRJadUqW4cOIHJQVBGRvv3WHgVK9miwUCG3eQDknuLFg2etPv+8tGaN2zwAQoeiiohz5Ig9AvT77ZFg48auEwHIbe3aSS1a2L//e+6RMrh0DogIFFVEnIED7RFgyZI2BhD5fD5p+HCpcGFpwQJp3DjXiQCEAkUVEWX9eum552w8aJA9EgQQHSpUCP77f+QRaft2t3kA5BxFFRHD77ezFA8elK6+WurQwXUiAHmtVy/pwgulXbu43AOIBBRVRIwZM6RPPpHy5ZOGDbNHgQCiS1ycNGKE/fufMEGaN891IgA5QVFFRNi3T/r3v2388MNS1apu8wBw5/LLbUOlZGcpc7YqEL4oqogITz8dPDP18cddpwHgWv/+tqFy9Wpp8GDXaQBkF0UVYW/FCunVV208dKhUsKDTOAA8oFgx6ZVXbPzMM9KGDU7jAMgmiirCWkaG1K2blJ4u3XST1Ly560QAvKJjR6lhQ9tgGVgaBCC8UFQR1t56y26hKlIkOKsKAFLwbNV8+aSPPpI+/th1IgBZRVFF2Nqzx85KlKSnnpLOPNNpHAAeVK2adP/9Nu7TRzp0yGkcAFlEUUXYevppads22+HPYz0AJ/PEE1LZstKvv3JbHRBuKKoISz/+aBunJGnIECl/frd5AHhXQoL08ss2fuEFKTnZbR4AmUdRRdgJ3ECVni61bStde63rRAC8rn17qX5921j1wAOu0wDILIoqws6UKdLcuXYMFY/xAGSGz2dPYWJipKlTpS+/dJ0IQGZQVBFW9u0LzoY89phUsaLbPADCR82aUo8eNu7VSzp61G0eAKdHUUVYeeEF6Y8/7Aaqhx5ynQZAuHn2Wbuxas0aW98OwNsoqggbv/4qDRpk48GDpQIF3OYBEH6KFrXrVSUrrdu2OY0D4DQoqggbDz4oHTkiNW0qtWzpOg2AcHXHHVLt2lJqqvTkk67TADgViirCwldfSTNmSLGxNqvq87lOBCBcxcQEb7IbM0ZavtxpHACnQFGF56WnB2+Wue8+6fzz3eYBEP6uvFK65RYpI8NurPL7XScCcCIUVXje2LHSihXSGWfYbVQAEAoDBtha9zlz7IkNAO+hqMLTUlLs+kPJSmrx4k7jAIggFSva2nfJPh8+7DYPgONRVOFpzz0nbd8uVa1qj/0BIJQeeUQqU0b67TfptddcpwHwTxRVeNa6dcFzDgcNkvLlc5sHQOQpUkR68UUbP/+89OefbvMAOBZFFZ718MN2c0zz5vYBALnh9tulOnWkvXs5rgrwGooqPGnevOBxVAMHuk4DIJL9/biqsWOlVaucxgHwNxRVeE5GRnCDw913S9Wquc0DIPLVrSu1bWs/fx5+2HUaAAEUVXjO5MnS4sW2dozjqADklRdflOLipFmzpC+/dJ0GgERRhcccOiQ99piNH3lEKl3abR4A0eOcc6Tu3W384IM2uwrALYoqPGXoUOn336WyZaW+fV2nARBtnnxSSkqSfvhBevtt12kAUFThGTt32vEwkvTCC1KhQm7zAIg+JUpIjz9u48cflw4ccJsHiHYUVXjGc8/ZTVQ1a0odO7pOAyBa9eplt1Zt2hQ8DQCAGxRVeMIvv0jDhtn4lVfsWCoAcKFAAalfPxu/+KK0bZvbPEA0o6jCEx5/3A73b9pUuvZa12kARLt27aRLLrFLAJ57znUaIHpRVOHckiXSlCmSzycNGOA6DQDYJQCBn0cjR0q//eY2DxCtKKpw7tFH7XOHDrY+FQC84Oqr7SnP0aNcrQq4QlGFU7NnS198IeXLJz37rOs0AHCs/v3t86RJ0rJlbrMA0SjTRXXTpk25mQNRKCMjOJt6331SpUpu8wDAP118sdS+vY0Dl5EAyDuZLqo1atTQxIkTczMLosz770tLl0oJCdITT7hOAwAn9vzz9tTns8+kr792nQaILpkuqv369VOPHj3Utm1b7dy5MzczIQocPRospw8+KJUs6TYPAJzM2WdL995r40cflfx+t3mAaJLpotq9e3ctX75cu3fvVvXq1TVz5szczIUIN2aMnZ1aqhRXpQLwvieekAoXlr7/Xpo2zXUaIHr4/P6svzccOnSo7r//flWrVk1xcXHH/N7SpUtDFu50UlNTlZSUpJSUFCUmJubZfy5yZv9+6ZxzpK1bpddfl3r2dJ0IAE7vqads02eVKtKqVdI/Xv4AnERO+lqW/5n9/vvv+uCDD1SsWDG1atXquKIKnM6QIVZSK1WS7rnHdRoAyJwHHpCGD5d+/ll6802pa1fXiYDIl6WWOXr0aD3wwANq3LixVq5cqZIsLEQW7dkTPET72Wel/PmdxgGATEtMtJ3/ffvaz6/bb5fi412nAiJbpteoNmvWTI888oiGDh2qadOmUVKRLQMHWlk9//zgkS8AEC7uu08680wpOVkaNcp1GiDyZbqopqena8WKFerUqVNu5kEE275devVVGz/3nBQb6zQOAGRZgQLBW6peeMHW3APIPZkuqrNnz1a5cuVyMwsi3EsvSfv2SbVqSTfe6DoNAGTPnXfakVV//ikNHeo6DRDZuEIVeWLzZumNN2z8/POSz+c2DwBkV758dgKAZG/AU1Lc5gEiGUUVeeL556VDh6R69aRmzVynAYCc6dBBqlZN2r1bGjTIdRogclFUkevWr5dGj7bxCy8wmwog/MXG2s5/yYrqjh1u8wCRiqKKXPfMM1JamnTttVLDhq7TAEBotGkjXXyxrb1/6SXXaYDIRFFFrlq7Vpo40cbPP+82CwCEUkxM8Ofa0KHSli1u8wCRiKKKXPXcc1JGhtSypXTppa7TAEBoNW8uXX65rcEPXGYCIHQoqsg1P/0kvfuujZ9+2mkUAMgVPp8tb5KkESOYVQVCjaKKXPPsszab2qqVnZ0KAJHo2mulunVtVvXFF12nASILRRW5YvVq6b33bMxsKoBI9vdZ1ZEjpT/+cJsHiCQUVeSKZ5+V/H67geqii1ynAYDcdc010pVXSocPM6sKhBJFFSG3apU0ZYqNA7e3AEAk8/mCT49GjZI2bXIaB4gYFFWEXGA2tU0b6cILXacBgLzRqJFUv7505AizqkCoUFQRUitXSu+/b2NmUwFEk7+vVR09Wtq40W0eIBJQVBFSzzxjs6k33STVrOk6DQDkrauvthv4jhyR+vd3nQYIfxRVhMzKldLUqTZmNhVAtArMqo4dy1pVIKcoqgiZF16wz23bSjVquM0CAK40bCg1aGCzqtxWBeQMRRUhsXatNHmyjZ94wm0WAHDtySft8+jR0tatbrMA4YyiipDo18/WprZsybmpAHDNNdLll9ttVa+84joNEL4oqsix336T3nnHxoFZBACIZj5f8Ofh8OHS9u1u8wDhiqKKHOvfX0pPl5o2lerUcZ0GALyheXOpdm3pwAFp8GDXaYDwRFFFjiQnS2++aWNmUwEgyOcLrtkfOlTatcttHiAcUVSRIy+9JB09amcH1qvnOg0AeMsNN0gXXCDt3SsNGeI6DRB+KKrItj/+kMaMsTGzqQBwvJiY4Kzqa69Jqalu8wDhhqKKbHvlFTsnsF496aqrXKcBAG9q21aqWlXas8eWAADIPIoqsmX7dmnkSBs/+aStxQIAHC82Vnr8cRsPHmybqwBkDkUV2TJkiHTwoO1obdLEdRoA8LZ27aRKlaQdO+xqVQCZQ1FFlqWmSq+/buPHHmM2FQBOJy5OevhhG7/8si2bAnB6FFVk2YgRUkqKrbm68UbXaQAgPHTpIv3rX9LGjdKkSa7TAOGBooosOXRIGjTIxo88YjtaAQCnV6CA1LevjV980S5KAXBq1Axkyfjx0p9/ShUqSB06uE4DAOGlWzepaFFp7VppxgzXaQDvo6gi09LSpAEDbPzgg1K+fG7zAEC4SUiQevWycb9+kt/vNg/gdRRVZNp770kbNkglS0pdu7pOAwDh6d//lgoVkpYulWbPdp0G8DaKKjIlI8PWVElSnz72QxYAkHUlSkj33GPjfv3cZgG8jqKKTPnoI2nVKikxUere3XUaAAhvDzxgy6fmzpUWLnSdBvAuiipOy+8PzqZ2724bAQAA2VeunNSpk41fesltFsDLKKo4rW++kRYtkuLjpd69XacBgMjw0EN2YcrMmdKaNa7TAN5EUcVpBXb6d+5sh1UDAHLuvPOk1q1t/MorTqMAnkVRxSmtXm3rU30+W1MFAAidwLWqEydKmze7zQJ4EUUVpxR4l3/jjVKVKm6zAECkufxyqX596ehR6bXXXKcBvIeiipPatEl6+20bB971AwBCK/DzdcQIKSXFbRbAayiqOKnXXrN3+Q0aSJdd5joNAESmFi2k88+XUlOlUaNcpwG8haKKE9qzRxo50sbMpgJA7omJsRMAJOnVV6XDh53GATyFoooTGjlS2rtXql5dat7cdRoAiGy33SaVLWsbqiZNcp0G8A6KKo5z+LC9q5fsXX4M/y8BgFyVP790//02fvllu7YaAEUVJ/D229LWrdKZZ0rt27tOAwDR4Z577JrqNWukTz5xnQbwBooqjuH3S4MG2bhPH3uXDwDIfYmJUrduNh440G0WwCsoqjjGf/9rh/wnJEh33+06DQBEl169pLg4ae5cackS12kA9yiqOEbgXfxdd0lJSW6zAEC0KVdOatfOxsyqAhRV/M0PP0hffinFxkq9e7tOAwDRKXBd9ZQpUnKy2yyAaxRV/CWwNvWmm6SKFd1mAYBoddFFUqNGUnq6NGSI6zSAWxRVSJL++EN6910b9+3rNgsARLvArOro0XZjFRCtKKqQJA0dKqWlSVdeKV16qes0ABDdmjWTqla1kjpmjOs0gDsUVWjfPmnECBsH3sUDANyJiQk+3XrtNZtIAKIRRRUaP17as0c65xypZUvXaQAAktSxo1SypG2omjrVdRrADYpqlEtPD16Xev/9tuMfAOBegQJSjx42HjjQLmQBog1FNcrNnCn99ptUrJjUubPrNACAv+ve3Qrr//4nLVjgOg2Q9yiqUS4wm9qtm1S4sNMoAIB/KFnSlgBItlYViDYU1Si2dKk0b55d19e9u+s0AIAT+fe/7fP06dKGDU6jAHmOohrFAu/Ob7lFOvNMt1kAACdWo4bUuLGUkWFHCQLRhKIapbZuDR7wz3WpAOBtffrY5zFj7EhBIFpQVKPUiBHS0aPSFVdwwD8AeF3z5tK550opKdKbb7pOA+QdimoUOnRIGj7cxoF36QAA74qJCT79eu01WwYARAOKahR67z1p2zapfHmpTRvXaQAAmdG5s5SUJK1bJ336qes0QN6gqEYZvz94JFXPnrbjHwDgfUWKSHfdZePAz3Eg0lFUo8zcudLy5VKhQsEfeACA8NCzpy0D+OILaeVK12mA3EdRjTKBd+GdO9ttVACA8HHWWdKNN9qYCwAQDSiqUeS33+zKVCl4gDQAILwENsG+/ba0c6fTKECuo6hGkWHDbI1q06ZS1aqu0wAAsqNePenii+0ElzFjXKcBchdFNUrs3y+NHWvjXr3cZgEAZJ/PF/w5PmyYlJbmNg+QmyiqUeKdd6Q9e6TKle3gaABA+GrXTipeXEpOlj76yHUaIPdQVKOA3y+9/rqNe/SwHaMAgPBVsKB09902Dvx8ByIRlSUKzJ1rx5gUKiTdcYfrNACAULjvPpt4+PprjqpC5KKoRoHAu+1OnaSiRZ1GAQCESIUKUuvWNh461GkUINdQVCNccrI0Y4aNe/Z0GgUAEGKBTVUTJ0q7d7vNAuQGimqEGz5cysiQGjWSqld3nQYAEEoNG0o1akgHDkjjx7tOA4QeRTWCHTwojRplY46kAoDI4/MFL3B54w0pPd1tHiDUKKoR7N13pV27pIoVpZYtXacBAOSGDh2kM86w2wc//dR1GiC0KKoRyu8PLq7v3l2KjXWbBwCQOwoVkrp2tTFHVSHSUFQj1KJF0rJlUoECwR9gAIDI1L27LQP4/HNp3TrXaYDQoahGqGHD7HPg9hIAQOSqVElq0cLGI0a4zQKEEkU1Am3fLk2ZYuPu3d1mAQDkjcDP+/Hj7RQAIBJQVCPQuHHSkSPSJZdIdeq4TgMAyAtNm9rM6u7d0uTJrtMAoUFRjTDp6XZ2qsRsKgBEk9hYu1ZVsqOq/H63eYBQoKhGmE8/lX7/3Y4qadfOdRoAQF664w4pPl5askRavNh1GiDnKKoRJrCJ6s47pYIF3WYBAOStEiWkW2+1ceD1AAhnFNUI8uuv0n//a+Nu3dxmAQC4EVj29d570s6dbrMAOUVRjSAjRtiapGbNpHPOcZ0GAODCpZdKtWtLhw/b5lognFFUI8TBg8EfSGyiAoDo5fMFXweGD5cyMtzmAXKCohohpkyRdu2SKlQIHvoMAIhO7dpJRYtK69dLn33mOg2QfRTVCBE4kqpbNzuiBAAQvQoVshMAJDZVIbxRVCPAsmXSd99J+fLZbn8AAO691z7PmiUlJ7vNAmQXRTUCjBxpn9u0kUqXdpsFAOAN550nNWpka1THjHGdBsgeimqY27tXeucdGwfePQMAIAVfF8aMkY4edZsFyA6KapibNEnat0+qUkW66irXaQAAXtK6tVSqlLRli/TRR67TAFlHUQ1jfv+xm6h8Prd5AADekj9/cO9CYJkYEE4oqmHs+++l5cvtXufOnV2nAQB40d1320TG55/bDYZAOKGohrHAu+NbbpGKFXObBQDgTWefLTVtauNRo9xmAbKKohqmdu+2e5wle+wPAMDJBDZVjRtnV6sC4YKiGqYmTrRrUy+4QLriCtdpAABedv31Utmy0o4d0rRprtMAmUdRDUN+vzRihI3ZRAUAOJ24OFurKrGpCuGFohqGFiyQ1qyxK/I6dHCdBgAQDu66S4qJkebOtdcQIBxQVMNQ4N1w+/ZSUpLbLACA8FCunC0BkNhUhfBBUQ0zu3ZJU6famJuoAABZcc899vmtt6RDh9xmATKDohpm3n7bdmxeeKF0ySWu0wAAwkmzZjazumuXNH266zTA6VFUw4jfH3xcEzjAGQCAzIqNDd5UxeN/hAOKahhZtEhatUoqWJBNVACA7Ona1SY65syR1q1znQY4NYpqGBk92j7ffLNUtKjTKACAMFWhgi0BkKQxY9xmAU6HohomUlOlyZNtHFgMDwBAdgTOVJ0wQTpyxGkU4JQoqmFi0iTpwAGpWjWpbl3XaQAA4ez666V//Uvatk366CPXaYCTo6iGCTZRAQBCJV8+6Y47bMymKngZRTUMLFkiLVsm5c8vdezoOg0AIBJ07WqfZ8+WNmxwGgU4KYpqGAhsomrbVipRwm0WAEBkqFxZuuYaO/pw7FjXaYATo6h63L59tj5VCi5+BwAgFAKbc8eNk9LS3GYBTiTOdQCc2pQp0t690jnnSFdd5TpNZEhPl+bPl7ZskcqUkerXt0OwAXjUunX2g/BkEhKkc8/NuzwRpFUre1K3ebP06adSy5auEwHHcj6jOmzYMFWqVEkFChRQ7dq1NX/+fNeRPCXwOCZwQDNyZto06ayzpKuvlm67zT6fdZZ9HYAHrVsnVaki1a598o8qVTi5Ppvi46VOnWzM4394kdOiOnnyZPXp00ePP/64li1bpvr166t58+ZKTk52GcszfvpJWrjQZvs6d3adJvxNmybddJO0adOxX//jD/s6ZRXwoFPNpGbn+3CcwJWqH38sbd3qNgvwT06L6qBBg9S1a1fdddddqlatml599VWVL19ew4cPdxnLM8aNs88tWtgjamRferrUu7dtGvinwNf69LHvA4BoUr26dNll9vNv4kTXaYBjOSuqR44c0ZIlS9SkSZNjvt6kSRMtXLjwhH/m8OHDSk1NPeYjUh09Kr35po0DR4gg++bPP34m9e/8fmnjRvs+AIg2gdeZsWNP/IYecMVZUd2xY4fS09NVunTpY75eunRpbT3Js4f+/fsrKSnpr4/y5cvnRVQnPvnEbgwpXdpmVJEzW7aE9vsAIJLceqtUqJC0dq0tOQO8wvlmKt8/dgj5/f7jvhbw2GOPKSUl5a+PjRs35kVEJwKL2jt1shtEkDOZXTrBEgsA0SgxUbrlFhuzqQpe4qyolihRQrGxscfNnm7btu24WdaA+Ph4JSYmHvMRiTZvlmbNsnFgkTtypn59qVy5k5+c4PNJ5cvb9wFANAo8/g8ciwh4gbOimj9/ftWuXVuzZ88+5uuzZ89W3bp1HaXyhrfekjIypHr1pKpVXaeJDLGx0muv2fifZTXw61df5TxVANGrXj076Wv/fiurgBc4ffTft29fjRkzRuPGjdOaNWt0//33Kzk5Wd26dXMZyym/P7jbn01UodWmjTR1qnTmmcd+vVw5+3qbNm5yATiFhITQfh9OyucLPsXj8T+8wuf3u93fN2zYMA0YMEBbtmxRjRo1NHjwYDVo0CBTfzY1NVVJSUlKSUmJmGUA8+ZJDRtKRYrYxp4iRVwnijzcTAWEGW6myjNbt9qb9/R0afVqqVo114kQCXLS15wX1ZyIxKLaubM9+r/rLmn0aNdpAADRplUraeZM6YEHpFdecZ0GkSAnfc35rn8EpaZK779vYx77AwBcCLz+vPWWdOSI2ywARdVDJk+WDh60Ry2XXeY6DQAgGrVoYWd4b98ePIEGcIWi6iETJtjnO+44+TFKAADkprg4qWNHGwdelwBXKKoeEbgNJDZWuv1212kAANGsSxf7HLglEXCFouoRgXetzZpxOxIAwK3q1aU6daS0NOntt12nQTSjqHpAerotWpfssT8AAK4FXo/Gj7czvgEXKKoeMHu2XZtarJh0/fWu0wAAILVrJ8XHSytXSkuXuk6DaEVR9YDx4+1zhw72QwEAANfOOENq3drGgdcpIK9RVB3bvVuaMcPGPPYHAHhJ4HVp0iTp8GG3WRCdKKqOvfuuHahcs6Z00UWu0wAAENS4sXTmmTapMnOm6zSIRhRVxzg7FQDgVbGxUqdONuZMVbhAUXVo1Spp8WI7XLlDB9dpAAA4XuBM1f/+1zb+AnmJoupQYHH69ddLJUu6zQIAwIlUqSLVqydlZEgTJ7pOg2hDUXXk74cos4kKAOBlgVnVCRM4UxV5i6LqyGefSX/+aTOpzZu7TgMAwMndcotUsKD000+2ZA3IKxRVRwI3Ud12m5Qvn9ssAACcSmKidOONNg68fgF5gaLqwO7d0ocf2jiwmxIAAC8LvF69+y5nqiLvUFQdeP99+0deo4Z08cWu0wAAcHqNG0tlyki7dkmzZrlOg2hBUXXgzTftc6dOnJ0KAAgPsbHS7bfbOPA6BuQ2imoe++UXaeFCKSYm+A8eAIBw0Lmzff7kE2nHDrdZEB0oqnkssAi9SRN7hAIAQLioXl2qXduOWHz3XddpEA0oqnno74cls4kKABCOAq9f7P5HXqCo5qH586UNG+yYj9atXacBACDr2re3q7//9z9p9WrXaRDpKKp5KPDu8+ab7eBkAADCTcmSUosWNmZWFbmNoppHDhywY6mk4GJ0AADCUeB1bOJEKT3dbRZENopqHpkxQ9q7V6pUSapXz3UaAACy77rrpDPOkDZvlr76ynUaRDKKah4JPB7p1MmOpgIAIFzFx9taVYkzVZG7qEx5YMsWafZsG3N2KgAgEnTsaJ+nT5f27XObBZGLopoH3nvPjqa64grpnHNcpwEAIOcuu8xe0w4csOVtQG6gqOaBwNmpzKYCACKFzxd8XQu8zgGhRlHNZatWScuW2Zlzt97qOg0AAKETKKpffGHL3IBQo6jmsrffts8tWkjFi7vNAgBAKFWubMvaMjJsmRsQahTVXJSRIb3zjo157A8AiEQ8/kduoqjmovnzpY0b7crUli1dpwEAIPRuvdWWty1bZsvdgFCiqOaiwLvLm2+WChRwmwUAgNxQvHjwStXAU0QgVCiqueTQoeCVqTz2BwBEssDr3Dvv2LI3IFQoqrnko4+k1FSpfHmpQQPXaQAAyD0tW9oyt+RkW/YGhApFNZcEdvt36MCVqQCAyFaggC1zk4Kvf0AoUKFywY4d0qxZNuaxPwAgGgRe795/35a/AaFAUc0FU6ZIaWnSxRdL1au7TgMAQO5r0MCWu6Wk2PI3IBQoqrkgsOuxQwe3OQAAyCsxMcHXvUmT3GZB5KCohtj69dLChXYHcvv2rtMAAJB3AkV11ixp9263WRAZKKoh9u679vnqq6WyZd1mAQAgL9WoIV1wgXTkiPTBB67TIBJQVEPI7+exPwAgugVe/zj8H6FAUQ2hFSuk1aul/PmlNm1cpwEAIO+1a2ef586VNm1ymwXhj6IaQoHF49dfLxUt6jQKAABOVKwo1a9vTxknT3adBuGOohoiGRnB9am33eY2CwAALgVeB3n8j5yiqIbIggXSxo12hdx117lOAwCAOzffLMXFScuWSWvWuE6DcEZRDZHAY/+2be0qOQAAolXx4lKzZjbmTFXkBEU1BI4csSvjJHb7AwAgHXv4v9/vNgvCF0U1BD77TNq1SypTRrrqKtdpAABwr2VLqXBh6bffpO++c50G4YqiGgKBxxrt2kmxsW6zAADgBYULSzfeaGMe/yO7KKo5tHev9OGHNma3PwAAQYHXxcmTpbQ0t1kQniiqOfThh9LBg1KVKlLt2q7TAADgHY0bSyVLStu2SV9+6ToNwhFFNYcCZ6e2by/5fG6zAADgJfny2VFVUvD1EsgKimoO7Nwpff65jQNXxgEAgKD27e3z9OnSoUNusyD8UFRz4IMPbM3NRRdJVau6TgMAgPfUrSuVKyelpkqffuo6DcINRTUH/v7YHwAAHC8mJvjUkcf/yCqKajZt3izNnWvjW291mwUAAC8LFNWPP7bTcoDMoqhm05QpdtNG3bpSxYqu0wAA4F21aknnnmun5Myc6ToNwglFNZvee88+89gfAIBT8/mCs6qB108gMyiq2RC4Di4mJnjsBgAAOLlAUQ1cOw5kBkU1GwLvBhs1kkqXdpsFAIBwcP75Us2a0tGjdmoOkBkU1WzgsT8AAFkXeN3k8T8yi6KaRatWST/+aLdt3Hij6zQAAISPwOP/r7+WtmxxmwXhgaKaRYF3gc2bS2ec4TYLAADh5KyzpMsvt1Nz3n/fdRqEA4pqFvj9wcOKuTIVAICsCzz+5/B/ZAZFNQuWLJF+/VUqVEi64QbXaQAACD8332yn5ixaJG3Y4DoNvI6imgWTJ9vn66+XChd2mwUAgHBUpozUsKGNp0xxmwXeR1HNJL8/+A+KK1MBAMi+wOtoYAIIOBmKaiYtWiQlJ0tFithGKgAAkD1t2kixsdLSpdIvv7hOAy+jqGZSYDa1VSupYEG3WQAACGclS9qlORKP/3FqFNVMyMgIHqPBY38AAHKOx//IDIpqJnzzjfTHH1JSktSkies0AACEvxtvlOLipBUrpJ9+cp0GXkVRzYTAu73WraX4eKdRAACICMWKSddea2NmVXEyFNXTSE+Xpk61MY/9AQAIncDrKutUcTIU1dOYN0/680+7LvWaa1ynAQAgcrRuLeXPL61eLa1c6ToNvIiiehqBxxFt2tg/JgAAEBpJSVKzZjbm8T9OhKJ6Cmlp0gcf2JjH/gAAhN7fd//7/W6zwHsoqqfw9dfSjh1SiRLS1Ve7TgMAQORp2VIqUEBat05avtx1GngNRfUUAo8h2ra1IzQAAEBoJSRILVrYmMf/+CeK6kkcOSJNm2ZjHvsDAJB7ePyPk6GonsT69VKRIlLp0lKDBq7TAAAQua67TipUSIqJkbZudZ0GXsID7ZM47zxpwwYpOVmKjXWdBgCAyFW4sLRqlVSxouTzuU4DL6GonkJMjHTWWa5TAAAQ+Xi9xYnw6B8AAACeRFEFAACAJ1FUAQAA4EkUVQAAAHgSRRUAAACeRFEFAACAJ1FUAQAA4EkUVQAAAHgSRRUAAACeRFEFAACAJ1FUAQAA4EkUVQAAAHgSRRUAAACeRFEFAACAJ8W5DpATfr9fkpSamuo4CQAAAE4k0NMCvS0rwrqo7t27V5JUvnx5x0kAAABwKjt37lRSUlKW/ozPn5166xEZGRnavHmzEhIS5PP5XMdBGElNTVX58uW1ceNGJSYmuo4DIJP4twuEn5SUFFWoUEG7d+9W0aJFs/Rnw3pGNSYmRuXKlXMdA2EsMTGRFzsgDPFvFwg/MTFZ3xrFZioAAAB4EkUVAAAAnkRRRVSKj4/XU089pfj4eNdRAGQB/3aB8JOTf7dhvZkKAAAAkYsZVQAAAHgSRRUAAACeRFEFAACAJ1FUAQAA4EkUVUSlYcOGqVKlSipQoIBq166t+fPnu44E4BTmzZunli1bqmzZsvL5fJoxY4brSABOo3///qpTp44SEhJUqlQptW7dWmvXrs3S30FRRdSZPHmy+vTpo8cff1zLli1T/fr11bx5cyUnJ7uOBuAk9u/frwsvvFBDhw51HQVAJs2dO1c9evTQokWLNHv2bKWlpalJkybav39/pv8OjqdC1LnssstUq1YtDR8+/K+vVatWTa1bt1b//v0dJgOQGT6fT9OnT1fr1q1dRwGQBdu3b1epUqU0d+5cNWjQIFN/hhlVRJUjR45oyZIlatKkyTFfb9KkiRYuXOgoFQAAkS8lJUWSVKxYsUz/GYoqosqOHTuUnp6u0qVLH/P10qVLa+vWrY5SAQAQ2fx+v/r27asrr7xSNWrUyPSfi8vFTIBn+Xy+Y37t9/uP+xoAAAiNnj17asWKFVqwYEGW/hxFFVGlRIkSio2NPW72dNu2bcfNsgIAgJzr1auXZs6cqXnz5qlcuXJZ+rM8+kdUyZ8/v2rXrq3Zs2cf8/XZs2erbt26jlIBABB5/H6/evbsqWnTpumrr75SpUqVsvx3MKOKqNO3b1917NhRl1xyia644gqNGjVKycnJ6tatm+toAE5i3759+uWXX/769fr16/XDDz+oWLFiqlChgsNkAE6mR48emjRpkj788EMlJCT89TQzKSlJBQsWzNTfwfFUiErDhg3TgAEDtGXLFtWoUUODBw/O9FEZAPLenDlzdPXVVx/39c6dO2vChAl5HwjAaZ1s78f48ePVpUuXzP0dFFUAAAB4EWtUAQAA4EkUVQAAAHgSRRUAAACeRFEFAACAJ1FUAQAA4EkUVQAAAHgSRRUAAACeRFEFAACAJ1FUAQAA4EkUVQBwLD09XXXr1lXbtm2P+XpKSorKly+vJ554wlEyAHCLK1QBwAPWrVuniy66SKNGjVKHDh0kSZ06ddLy5cu1ePFi5c+f33FCAMh7FFUA8IghQ4bo6aef1sqVK7V48WLdfPPN+v7773XRRRe5jgYATlBUAcAj/H6/GjVqpNjYWP3444/q1asXj/0BRDWKKgB4yE8//aRq1arpggsu0NKlSxUXF+c6EgA4w2YqAPCQcePGqVChQlq/fr02bdrkOg4AOMWMKgB4xLfffqsGDRro008/1YABA5Senq4vvvhCPp/PdTQAcIIZVQDwgIMHD6pz586699571bhxY40ZM0aLFy/WyJEjXUcDAGcoqgDgAY8++qgyMjL00ksvSZIqVKiggQMH6qGHHtKGDRvchgMAR3j0DwCOzZ07V9dcc43mzJmjK6+88pjfa9q0qdLS0lgCACAqUVQBAADgSTz6BwAAgCdRVAEAAOBJFFUAAAB4EkUVAAAAnkRRBQAAgCdRVAEAAOBJFFUAAAB4EkUVAAAAnkRRBQAAgCdRVAEAAOBJFFUAAAB40v8D+j9OVHrEpb0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 산점도 그리기\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(x=0, y=0, color='b', edgecolor='b', marker='o')\n",
    "plt.scatter(x=0, y=1, color='r', edgecolor='r', marker='s')\n",
    "plt.scatter(x=1, y=0, color='r', edgecolor='r', marker='s')\n",
    "plt.scatter(x=1, y=1, color='b', edgecolor='b', marker='o')\n",
    "\n",
    "# 비선형 그래프 그리기\n",
    "x_curve = np.linspace(-0.5, 1.5, 100)  # x 좌표 범위\n",
    "y_curve = -2 * (x_curve - 0.5) ** 2 + 1.5  # y 좌표 (파란색 원이 있는 y 좌표)\n",
    "plt.plot(x_curve, y_curve, color='b')\n",
    "\n",
    "plt.xticks(np.arange(0, 3, 1))\n",
    "plt.yticks(np.arange(0, 3, 1))\n",
    "plt.xlabel('X')\n",
    "plt.ylabel('Y')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "c7d90e0e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x = np.linspace(-2, 2, 100)  # x 범위 설정\n",
    "y = 3 * x**4 - 10 * x**2 + 6  # 4차식 그래프 정의\n",
    "\n",
    "plt.plot(x, y)\n",
    "plt.scatter(0, 1.5, color='r', marker='o')\n",
    "plt.scatter(0, 0.5, color='r', marker='o')\n",
    "plt.scatter(0.5, 0, color='b', marker='o')\n",
    "plt.scatter(1.5, 0, color='b', marker='o')\n",
    "plt.xlabel('X')\n",
    "plt.ylabel('Y')\n",
    "plt.title('4차식 그래프')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "#개 열받는다 챗 지피티.. 말을 못알아듣네"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2b38e8e2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "254aab41",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "05a91af0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "77b31d6e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21040aff",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f2e6e55d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a85ed1ff",
   "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}