Day2/Chapter4.ipynb

{
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   "cell_type": "markdown",
   "id": "2f75c7a0-cfa3-4c5b-a01b-fd0445ce13c3",
   "metadata": {},
   "source": [
    "# Chapter4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cae257fa-fd6e-4bd5-85f1-f92609c9f00b",
   "metadata": {},
   "outputs": [],
   "source": [
    "a = 3; b = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "49051256-71a9-49d9-b56c-fd4a5c42803d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9e9121c5-a16f-44d7-ab3e-022559d5af8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-2"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a - b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "76ce2177-0373-408c-bd44-83abca5156e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a / b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b58286e2-87ef-4ef0-80bf-b61abe1bf540",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
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    }
   ],
   "source": [
    "a // b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "500bad1c-ebd8-48ea-a79e-c21be6d50832",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a % b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "36cede69-750b-43a7-8e57-33def97c84eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "243"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a**b"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5b097fc-4a6a-4cba-9dea-7c62d8d018e3",
   "metadata": {},
   "source": [
    "우선순위"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9829452e-cf80-4998-abeb-ce117f4be044",
   "metadata": {},
   "outputs": [],
   "source": [
    "a, b, c = 2, 3, 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d00731e3-f40e-450b-a308-345995503380",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a + b - c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "58d4c7c0-942b-4abf-97e4-157b72348f4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a + (b - c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ab9106f3-cf59-4459-9ded-5b06cf6f6b76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(a+b)*c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "47383dce-7375-45ff-a31e-bc557c5eab0b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a+(b*c)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d514bac5-1461-461e-baed-2f49dfbd6be1",
   "metadata": {},
   "source": [
    "### 내장 자료형 함수\n",
    " - int()\n",
    " - bin()\n",
    " - oct()\n",
    " - hex()\n",
    " - float()\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cfb0b38-a5b9-4423-8397-780bda4232c0",
   "metadata": {},
   "source": [
    "문자형 자료형 함수\n",
    " - str()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "759bb5fc-7fef-4a9c-88be-a01f27be6972",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "can only concatenate str (not \"int\") to str",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Input \u001b[1;32mIn [15]\u001b[0m, in \u001b[0;36m<cell line: 2>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m a \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m100\u001b[39m\n\u001b[1;32m----> 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m안녕 난 \u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43ma\u001b[49m \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m야!\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
      "\u001b[1;31mTypeError\u001b[0m: can only concatenate str (not \"int\") to str"
     ]
    }
   ],
   "source": [
    "a = 100\n",
    "print(\"안녕 난 \" + a + \"야!\")  # 안녕 난 100 야!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e52e1ff1-f68d-434c-8665-04c01e4ce285",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "안녕 난 100야!\n"
     ]
    }
   ],
   "source": [
    "print(\"안녕 난 \" + str(a) + \"야!\")  # 안녕 난 100 야!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "508d51b0-4d55-4858-9b97-60ecd4af8d27",
   "metadata": {},
   "source": [
    "## 복합대입연산자"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3ea96589-e715-4fba-a2fd-335beda98e9e",
   "metadata": {},
   "outputs": [],
   "source": [
    "a = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f2eafe4e-f089-49a3-ab49-62aaae9a557c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "13"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = a + 3\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d3a27b25-34d7-4942-87ba-db7bb61800e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "a += 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "82f1a8f8-1b17-465c-b94c-165ab108f954",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "38649aed-ec7d-40ef-8662-0f0a600d604d",
   "metadata": {},
   "outputs": [],
   "source": [
    "a **= 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "763648a8-a658-48db-b6ec-330be9a4674d",
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "cannot assign to literal (632958915.py, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  Input \u001b[1;32mIn [24]\u001b[1;36m\u001b[0m\n\u001b[1;33m    10 **= 3\u001b[0m\n\u001b[1;37m    ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m cannot assign to literal\n"
     ]
    }
   ],
   "source": [
    "10 **= 3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f40db02c-1bbf-41ad-a73c-06bf76546718",
   "metadata": {},
   "source": [
    "### p100 동전교환\n",
    "\n",
    "500, 100, 50, 10원짜리 동전으로 교환하는 방법!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "bde7472c-6657-45f2-bd2c-117727b8a174",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "교환할 돈은 얼마 ?  7200\n"
     ]
    }
   ],
   "source": [
    "## 변수 선언 부분 ##\n",
    "money, c500, c100, c50, c10 = 0, 0, 0, 0, 0\n",
    "\n",
    "## 메인 코드 부분 ##\n",
    "money=int(input(\"교환할 돈은 얼마 ? \"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "08f505e3-eeb9-4211-8b28-684e7efddcaf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "money // 500"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a1a8cb07-355f-4c65-ba09-a7124bd31197",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "money %= 500"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3d336d1-1940-48a9-bad3-e907825cc9cb",
   "metadata": {},
   "source": [
    "## 관계연산자"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "32b326fa-a899-465f-8b48-5828793cf3c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "10 == 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ed2bd6d1-c082-43da-8ab7-63ce88bf9c4a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "10 == 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "4f87b4ff-4e54-4e58-a176-3ce98fae5bca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "10 > 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "99f4307b-47ca-4856-a7cc-33ea6e848c31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "10 < 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "4de22e64-a7ff-451e-87b6-4fb7646e4261",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5보다 크다\n"
     ]
    }
   ],
   "source": [
    "if 10 > 5:\n",
    "    print(\"5보다 크다\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "df419bfb-7169-4f88-81b9-ecac366bba7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "10 != 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "e2e255f1-4db5-4a56-be0b-94d64ecd9be7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "10 != 10"
   ]
  },
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"
    }
   },
   "cell_type": "markdown",
   "id": "b77a676d-0571-4329-b0db-6d58c1dfe0b1",
   "metadata": {},
   "source": [
    "## 논리연산자\n",
    "\n",
    "![image.png](attachment:0359871a-1f62-4722-a52d-bc50f558b9f5.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "0de92f71-5a4f-4bd9-b616-6e0e5abee326",
   "metadata": {},
   "outputs": [],
   "source": [
    "a = 99"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "13adf044-1fd4-4552-b963-b9aa1c529840",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 논리곱\n",
    "a > 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "bfa6b668-8665-4391-a91a-6925140d6244",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# a가 100보다 크고 200보다 작은거!!!\n",
    "(a > 100) and (a < 200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "f7f2f0a9-43b3-43a6-bf1a-84092720db66",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# a가 100보다 크거나 200보다 작은거!!!\n",
    "(a > 100) or (a < 200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "0279668c-881a-4858-9552-3c80be98b652",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 반대!\n",
    "not True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "78b0a4b7-ff88-4ec0-95de-dcf4897a9648",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "not     (a > 100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36175012-d7a6-4010-918a-28707762652a",
   "metadata": {},
   "source": [
    "## 비트 연산자"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "b671bd5b-bc4a-429b-9932-77069857d24d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 비트 논리연산"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "8561c084-d033-4a34-b1dc-311838a9dca0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "10 & 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "bca62cb3-2aab-4b4f-95e4-2d3ead96bbe0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('0b1010', '0b111')"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bin(10), bin(7)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8400e86f-76d5-4313-b964-698d90a746aa",
   "metadata": {},
   "source": [
    "```\n",
    "  0b1010\n",
    "&  0b111\n",
    "--------\n",
    "    0010\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "25957ca0-c9d8-4e62-b474-977332e3c512",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0b10'"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bin(10 & 7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "c5cc2bf7-8e78-4a2e-8018-6fd037b88094",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2 & 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "6beb3150-4296-48f7-a4fe-afb62b778dc6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0b0'"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bin(2& 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "0ed38af7-9cba-4a26-b24b-c8b7ec8222e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('0b1111011', '0b111001000')"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bin(123), bin(456)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a25fa05-862e-47bb-bffd-2f1550a4be90",
   "metadata": {},
   "source": [
    "```\n",
    "  '0b1111011'\n",
    "'0b111001000'\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "849ad3c3-387e-4fd9-abd0-b7eeb5a2068d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0b1001000'"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bin(123 & 456)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "8487f21a-7e8c-4b07-a0c9-5808828141a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0b10'"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bin(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "c04f825f-bf76-4fb5-856b-c2ac1b292526",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-3"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "~2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "f6d3916d-c04c-444c-af2f-afc2ed91ad21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'-0b11'"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bin(~2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70f6fa02-edf6-43c3-84a2-8e9b1c186cb0",
   "metadata": {},
   "source": [
    "논리합"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "92ebbd7f-d3ea-46f1-8be6-d53eece96b57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('0b1010', '0b111')"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bin(10), bin(7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "a6eecc5b-7edd-47af-b86b-f4b5a201a296",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "10 | 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "e1baec6c-0401-4f1b-b016-ef5497b6ddd4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0b1111'"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bin(10 | 7 )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "073fec6a-3431-4e6e-8f8e-83b1e7c9b201",
   "metadata": {},
   "source": [
    "배타적 논리합"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "310d5774-6322-4526-8f2d-7767f9c7b4b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('0b1010', '0b111')"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bin(10), bin(7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "77609c99-dccd-4a05-97ef-d5a2b163dc5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0b1101'"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bin( 10 ^ 7)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "730efb31-9e54-4602-a23b-e6cdbd10f3e6",
   "metadata": {},
   "source": [
    "Masking 기법 : 비트 기반 연산!!!\n",
    "\n",
    "```\n",
    "00010 & 11000\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90f08fe7-ae17-4b35-91af-1565684d438a",
   "metadata": {},
   "source": [
    "## 쉬프트 연산자\n",
    "\n",
    "```\n",
    ">>\n",
    "<<\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "1f366126-852d-4383-8469-664e49ef701b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0b1010'"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = 10; bin(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "a4c24404-1e82-4eba-b81b-ae31488a1c12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a << 1    # 1칸"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "7c9ea170-c371-4698-9f8a-953fb125c6e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0b10100'"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bin( a << 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "9d77bbeb-4785-4552-97bb-4c588f98a1f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0b101'"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# >>\n",
    "bin( a >> 1)"
   ]
  }
 ],
 "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": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}