sort_memo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "74f5fb9d-b94b-4ecb-ba95-12d23b04cc1f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_sql_until(until:int):\n",
    "    with open('postgreSQL_remind.sql') as f:\n",
    "        for _ in range(until):\n",
    "            print(f.readline(), sep='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "e7772f0b-40d6-4509-986d-3513d9a990af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "select count(*) \"전체건수\",\n",
      "\n",
      "\t   count(position) \"직책건수\",\n",
      "\n",
      "\t   count(distinct position) \"직책종류\",\n",
      "\n",
      "\t   min(salary) \"최소\",\n",
      "\n",
      "\t   max(salary) \"최대\",\n",
      "\n",
      "\t   avg(salary) \"평균\"\n",
      "\n",
      "from cslee.tb_emp;\n",
      "\n"
     ]
    }
   ],
   "source": [
    "read_sql_until(7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "d4c768dd-6df0-4e40-b01a-1192b5ffb9f3",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "select count(*) \"전체건수\",\n",
      "\n",
      "\t   count(position) \"직책건수\",\n",
      "\n",
      "\t   count(distinct position) \"직책종류\",\n",
      "\n",
      "\t   min(salary) \"최소\",\n",
      "\n",
      "\t   max(salary) \"최대\",\n",
      "\n",
      "\t   avg(salary) \"평균\"\n",
      "\n",
      "from cslee.tb_emp;\n",
      "\n"
     ]
    }
   ],
   "source": [
    "a = str(read_sql_until(7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "94e25e4f-87a7-4623-9d0b-ce62d2c94399",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlalchemy\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "60eb55e3-fb91-4460-b668-6c86bd289d65",
   "metadata": {},
   "outputs": [],
   "source": [
    "engine = sqlalchemy.create_engine(\"postgresql://postgres:qwer1234@localhost:5432/postgres\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "26ad1ce1-62fb-4ba4-92e1-e5b0828d0c7e",
   "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>전체건수</th>\n",
       "      <th>직책건수</th>\n",
       "      <th>직책종류</th>\n",
       "      <th>최소</th>\n",
       "      <th>최대</th>\n",
       "      <th>평균</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>6</td>\n",
       "      <td>32300000</td>\n",
       "      <td>225996000</td>\n",
       "      <td>8.324772e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   전체건수  직책건수  직책종류        최소         최대            평균\n",
       "0    29    29     6  32300000  225996000  8.324772e+07"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_sql('select count(*) \"전체건수\",\\\n",
    "\t   count(position) \"직책건수\",\\\n",
    "\t   count(distinct position) \"직책종류\",\\\n",
    "\t   min(salary) \"최소\",\\\n",
    "\t   max(salary) \"최대\",\\\n",
    "\t   avg(salary) \"평균\"\\\n",
    "from cslee.tb_emp;', engine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "035ebba1-687d-4da2-9a26-84be62a459e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import warnings\n",
    "warnings.simplefilter(action='ignore', category=FutureWarning)   # FutureWarning 제거\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from sklearn.preprocessing import MinMaxScaler  #min-max 스케일링\n",
    "from sklearn.preprocessing import StandardScaler   # 표준화\n",
    "from scipy import stats\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "\n",
    "import os\n",
    "if os.name == 'nt':\n",
    "    font_family = 'Malgun Gothic'\n",
    "\n",
    "sns.set(font=font_family, rc={'axes.unicode_minus' : False})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "70023d68-17f3-4b64-8dc0-26c07d160e87",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.arange(1, 10001)\n",
    "y = np.arange(10001, 20001)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "37ef20d8-abf6-4cc5-b864-c7b2e282b87d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: total: 0 ns\n",
      "Wall time: 5.18 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "z = np.zeros_like(x)\n",
    "for i in range(10000):\n",
    "    z[i] = x[i] + y[i]\n",
    "    \n",
    "# 셀 코드 실행 시간 측정하는 Ipython 매직 명령어"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "95be1a47-0bbd-4148-9267-a0da72d0c89e",
   "metadata": {},
   "outputs": [],
   "source": [
    "a = np.array([[1, 2, 3, 4],\n",
    "              [46, 99, 100, 71],\n",
    "              [81, 59, 90, 100]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "d1ad4136-b388-4aac-bb5a-e92b8d940df1",
   "metadata": {},
   "outputs": [],
   "source": [
    "a.sort(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "e6188032-863f-4012-844a-2554856f0b22",
   "metadata": {},
   "outputs": [],
   "source": [
    "a.sort(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "c195f7df-a4cb-4537-8fcd-ac2b63e80cae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  1,   2,   3,   4],\n",
       "       [ 46,  71,  90, 100],\n",
       "       [ 59,  81,  99, 100]])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "e0b6966c-24d6-4214-a2c8-984a32bcecf0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:3, :][0][3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "1307a696-f38e-4347-a050-a37f2a2c4233",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0][3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "e9ddbb4f-341f-49f5-b6f8-a46d2c6daba5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "81"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[2, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "81c4b789-418d-412e-a0d1-25bf7d50edeb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "81"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[2][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "b2d0cef0-67a6-4dd1-ab50-255040fbcbe8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0, 3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "563e64f9-9b5b-4b05-b33b-61783ee9e255",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([90, 99])"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[1:, 2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "3527f873-8efd-43b8-829e-f2ddb8b8039f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 0, 0, 0],\n",
       "       [1, 1, 1, 1],\n",
       "       [2, 2, 2, 2]], dtype=int64)"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.argsort(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "c09a63bc-89c9-484c-b634-523d37722f18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 1, 2, 3],\n",
       "       [0, 1, 2, 3],\n",
       "       [0, 1, 2, 3]], dtype=int64)"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.argsort(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "af0af9bb-1747-4c7e-994a-eaaf3a828588",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf050150-ceff-4471-b6da-149ca7544bd0",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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