주식데이터_수집_전처리.ipynb

{
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  {
   "cell_type": "markdown",
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   "source": [
    "### 시가총액 데이터셋 marcap\n",
    "\n",
    "https://github.com/FinanceData/marcap\n",
    "\n",
    "컬럼 구성(18개)\n",
    "\n",
    "Date : 날짜 (DatetimeIndex)  \n",
    "Rank: 시가총액 순위 (당일)  \n",
    "Code : 종목코드  \n",
    "Name : 종명이름  \n",
    "Open : 시가  \n",
    "High : 고가  \n",
    "Low : 저가  \n",
    "Close : 종가  \n",
    "Volume : 거래량  \n",
    "Amount : 거래대금  \n",
    "Changes : 전일대비  \n",
    "ChangeCode: 등락 기호  \n",
    "ChagesRatio : 전일대비 등락률  \n",
    "Marcap : 시가총액(백만원)  \n",
    "Stocks : 상장주식수  \n",
    "MarketId : 시장기호  \n",
    "Market : 시장  \n",
    "Dept : 부서(한국거래소)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
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   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Code</th>\n",
       "      <th>Name</th>\n",
       "      <th>Market</th>\n",
       "      <th>Dept</th>\n",
       "      <th>Close</th>\n",
       "      <th>ChangeCode</th>\n",
       "      <th>Changes</th>\n",
       "      <th>ChagesRatio</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Amount</th>\n",
       "      <th>Marcap</th>\n",
       "      <th>Stocks</th>\n",
       "      <th>MarketId</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>005930</td>\n",
       "      <td>삼성전자</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38750.0</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.13</td>\n",
       "      <td>39400.0</td>\n",
       "      <td>39400.0</td>\n",
       "      <td>38550.0</td>\n",
       "      <td>7847664.0</td>\n",
       "      <td>3.046826e+11</td>\n",
       "      <td>2.313291e+14</td>\n",
       "      <td>5969782550</td>\n",
       "      <td>STK</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-01-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>000660</td>\n",
       "      <td>SK하이닉스</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0.17</td>\n",
       "      <td>61300.0</td>\n",
       "      <td>61400.0</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>1934295.0</td>\n",
       "      <td>1.174588e+11</td>\n",
       "      <td>4.411694e+13</td>\n",
       "      <td>728002365</td>\n",
       "      <td>STK</td>\n",
       "      <td>2</td>\n",
       "      <td>2019-01-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>068270</td>\n",
       "      <td>셀트리온</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>214500.0</td>\n",
       "      <td>2</td>\n",
       "      <td>-8000.0</td>\n",
       "      <td>-3.60</td>\n",
       "      <td>224500.0</td>\n",
       "      <td>226000.0</td>\n",
       "      <td>213000.0</td>\n",
       "      <td>1045357.0</td>\n",
       "      <td>2.285731e+11</td>\n",
       "      <td>2.691034e+13</td>\n",
       "      <td>125456133</td>\n",
       "      <td>STK</td>\n",
       "      <td>3</td>\n",
       "      <td>2019-01-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>005935</td>\n",
       "      <td>삼성전자우</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31600.0</td>\n",
       "      <td>2</td>\n",
       "      <td>-150.0</td>\n",
       "      <td>-0.47</td>\n",
       "      <td>32700.0</td>\n",
       "      <td>32800.0</td>\n",
       "      <td>31300.0</td>\n",
       "      <td>944879.0</td>\n",
       "      <td>3.020400e+10</td>\n",
       "      <td>2.600322e+13</td>\n",
       "      <td>822886700</td>\n",
       "      <td>STK</td>\n",
       "      <td>4</td>\n",
       "      <td>2019-01-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>207940</td>\n",
       "      <td>삼성바이오로직스</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>374000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>-12500.0</td>\n",
       "      <td>-3.23</td>\n",
       "      <td>389500.0</td>\n",
       "      <td>392000.0</td>\n",
       "      <td>372000.0</td>\n",
       "      <td>148344.0</td>\n",
       "      <td>5.654277e+10</td>\n",
       "      <td>2.474571e+13</td>\n",
       "      <td>66165000</td>\n",
       "      <td>STK</td>\n",
       "      <td>5</td>\n",
       "      <td>2019-01-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566722</th>\n",
       "      <td>001527</td>\n",
       "      <td>동양2우B</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9360.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>9360.0</td>\n",
       "      <td>9360.0</td>\n",
       "      <td>9250.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>1.702630e+06</td>\n",
       "      <td>2.888206e+09</td>\n",
       "      <td>308569</td>\n",
       "      <td>STK</td>\n",
       "      <td>2469</td>\n",
       "      <td>2019-12-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566723</th>\n",
       "      <td>245450</td>\n",
       "      <td>씨앤에스링크</td>\n",
       "      <td>KONEX</td>\n",
       "      <td>일반기업부</td>\n",
       "      <td>1710.0</td>\n",
       "      <td>2</td>\n",
       "      <td>-285.0</td>\n",
       "      <td>-14.29</td>\n",
       "      <td>1710.0</td>\n",
       "      <td>1710.0</td>\n",
       "      <td>1710.0</td>\n",
       "      <td>585.0</td>\n",
       "      <td>1.000350e+06</td>\n",
       "      <td>2.701732e+09</td>\n",
       "      <td>1579960</td>\n",
       "      <td>KNX</td>\n",
       "      <td>2471</td>\n",
       "      <td>2019-12-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566724</th>\n",
       "      <td>276240</td>\n",
       "      <td>엘리비젼</td>\n",
       "      <td>KONEX</td>\n",
       "      <td>일반기업부</td>\n",
       "      <td>500.0</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>11.11</td>\n",
       "      <td>500.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>450.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.450000e+03</td>\n",
       "      <td>2.587200e+09</td>\n",
       "      <td>5174400</td>\n",
       "      <td>KNX</td>\n",
       "      <td>2472</td>\n",
       "      <td>2019-12-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566725</th>\n",
       "      <td>001529</td>\n",
       "      <td>동양3우B</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28450.0</td>\n",
       "      <td>1</td>\n",
       "      <td>200.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>28000.0</td>\n",
       "      <td>28850.0</td>\n",
       "      <td>28000.0</td>\n",
       "      <td>851.0</td>\n",
       "      <td>2.409010e+07</td>\n",
       "      <td>2.552591e+09</td>\n",
       "      <td>89722</td>\n",
       "      <td>STK</td>\n",
       "      <td>2473</td>\n",
       "      <td>2019-12-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566726</th>\n",
       "      <td>238500</td>\n",
       "      <td>로보쓰리</td>\n",
       "      <td>KONEX</td>\n",
       "      <td>일반기업부</td>\n",
       "      <td>475.0</td>\n",
       "      <td>2</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>-4.81</td>\n",
       "      <td>425.0</td>\n",
       "      <td>475.0</td>\n",
       "      <td>425.0</td>\n",
       "      <td>12267.0</td>\n",
       "      <td>5.235286e+06</td>\n",
       "      <td>2.224029e+09</td>\n",
       "      <td>4682166</td>\n",
       "      <td>KNX</td>\n",
       "      <td>2474</td>\n",
       "      <td>2019-12-30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>566727 rows × 18 columns</p>\n",
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      ],
      "text/plain": [
       "          Code      Name Market   Dept     Close  ChangeCode  Changes  \\\n",
       "0       005930      삼성전자  KOSPI    NaN   38750.0           1     50.0   \n",
       "1       000660    SK하이닉스  KOSPI    NaN   60600.0           1    100.0   \n",
       "2       068270      셀트리온  KOSPI    NaN  214500.0           2  -8000.0   \n",
       "3       005935     삼성전자우  KOSPI    NaN   31600.0           2   -150.0   \n",
       "4       207940  삼성바이오로직스  KOSPI    NaN  374000.0           2 -12500.0   \n",
       "...        ...       ...    ...    ...       ...         ...      ...   \n",
       "566722  001527     동양2우B  KOSPI    NaN    9360.0           3      0.0   \n",
       "566723  245450    씨앤에스링크  KONEX  일반기업부    1710.0           2   -285.0   \n",
       "566724  276240      엘리비젼  KONEX  일반기업부     500.0           1     50.0   \n",
       "566725  001529     동양3우B  KOSPI    NaN   28450.0           1    200.0   \n",
       "566726  238500      로보쓰리  KONEX  일반기업부     475.0           2    -24.0   \n",
       "\n",
       "        ChagesRatio      Open      High       Low     Volume        Amount  \\\n",
       "0              0.13   39400.0   39400.0   38550.0  7847664.0  3.046826e+11   \n",
       "1              0.17   61300.0   61400.0   60000.0  1934295.0  1.174588e+11   \n",
       "2             -3.60  224500.0  226000.0  213000.0  1045357.0  2.285731e+11   \n",
       "3             -0.47   32700.0   32800.0   31300.0   944879.0  3.020400e+10   \n",
       "4             -3.23  389500.0  392000.0  372000.0   148344.0  5.654277e+10   \n",
       "...             ...       ...       ...       ...        ...           ...   \n",
       "566722         0.00    9360.0    9360.0    9250.0      182.0  1.702630e+06   \n",
       "566723       -14.29    1710.0    1710.0    1710.0      585.0  1.000350e+06   \n",
       "566724        11.11     500.0     500.0     450.0        3.0  1.450000e+03   \n",
       "566725         0.71   28000.0   28850.0   28000.0      851.0  2.409010e+07   \n",
       "566726        -4.81     425.0     475.0     425.0    12267.0  5.235286e+06   \n",
       "\n",
       "              Marcap      Stocks MarketId  Rank        Date  \n",
       "0       2.313291e+14  5969782550      STK     1  2019-01-02  \n",
       "1       4.411694e+13   728002365      STK     2  2019-01-02  \n",
       "2       2.691034e+13   125456133      STK     3  2019-01-02  \n",
       "3       2.600322e+13   822886700      STK     4  2019-01-02  \n",
       "4       2.474571e+13    66165000      STK     5  2019-01-02  \n",
       "...              ...         ...      ...   ...         ...  \n",
       "566722  2.888206e+09      308569      STK  2469  2019-12-30  \n",
       "566723  2.701732e+09     1579960      KNX  2471  2019-12-30  \n",
       "566724  2.587200e+09     5174400      KNX  2472  2019-12-30  \n",
       "566725  2.552591e+09       89722      STK  2473  2019-12-30  \n",
       "566726  2.224029e+09     4682166      KNX  2474  2019-12-30  \n",
       "\n",
       "[566727 rows x 18 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "mcp = pd.read_csv('./raw/marcap-2019.csv')\n",
    "mcp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "efbda9a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 566727 entries, 0 to 566726\n",
      "Data columns (total 18 columns):\n",
      " #   Column       Non-Null Count   Dtype  \n",
      "---  ------       --------------   -----  \n",
      " 0   Code         566727 non-null  object \n",
      " 1   Name         566727 non-null  object \n",
      " 2   Market       566727 non-null  object \n",
      " 3   Dept         346336 non-null  object \n",
      " 4   Close        566727 non-null  float64\n",
      " 5   ChangeCode   566727 non-null  int64  \n",
      " 6   Changes      566727 non-null  float64\n",
      " 7   ChagesRatio  566727 non-null  float64\n",
      " 8   Open         566727 non-null  float64\n",
      " 9   High         566727 non-null  float64\n",
      " 10  Low          566727 non-null  float64\n",
      " 11  Volume       566727 non-null  float64\n",
      " 12  Amount       566727 non-null  float64\n",
      " 13  Marcap       566727 non-null  float64\n",
      " 14  Stocks       566727 non-null  int64  \n",
      " 15  MarketId     566727 non-null  object \n",
      " 16  Rank         566727 non-null  int64  \n",
      " 17  Date         566727 non-null  object \n",
      "dtypes: float64(9), int64(3), object(6)\n",
      "memory usage: 77.8+ MB\n"
     ]
    }
   ],
   "source": [
    "mcp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0919e873",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 19년 1월 2일 기준 KOSPI 시가총액 상위 100개\n",
    "mcp1 = mcp[\n",
    "    (mcp['Date'] == '2019-01-02') &\n",
    "    (mcp['Marcap'][(mcp['Date']=='2019-01-02') & (mcp['Market']=='KOSPI')].rank(ascending=False) <= 100)\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "58ec8f86",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Code</th>\n",
       "      <th>Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>005930</td>\n",
       "      <td>삼성전자</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>000660</td>\n",
       "      <td>SK하이닉스</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>068270</td>\n",
       "      <td>셀트리온</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>005935</td>\n",
       "      <td>삼성전자우</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>207940</td>\n",
       "      <td>삼성바이오로직스</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>000060</td>\n",
       "      <td>메리츠화재</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>028670</td>\n",
       "      <td>팬오션</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>010620</td>\n",
       "      <td>현대미포조선</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>000880</td>\n",
       "      <td>한화</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>138930</td>\n",
       "      <td>BNK금융지주</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Code      Name\n",
       "0    005930      삼성전자\n",
       "1    000660    SK하이닉스\n",
       "2    068270      셀트리온\n",
       "3    005935     삼성전자우\n",
       "4    207940  삼성바이오로직스\n",
       "..      ...       ...\n",
       "105  000060     메리츠화재\n",
       "106  028670       팬오션\n",
       "107  010620    현대미포조선\n",
       "108  000880        한화\n",
       "109  138930   BNK금융지주\n",
       "\n",
       "[100 rows x 2 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mcp1[['Code', 'Name']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "af96cc43",
   "metadata": {},
   "outputs": [],
   "source": [
    "codes = mcp1['Code'].values\n",
    "df = mcp[mcp['Code'].isin(list(codes))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "822abdfb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_stock = df.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32f27648",
   "metadata": {},
   "source": [
    "ChangeCode : 기본 라벨값  \n",
    "1: 전일대비 상승  1 ->  1 유지\n",
    "2 : 전일대비 하락 2  -> 0으로 변경\n",
    "3 : 등락 변동 없음 3 -> 1로 변경 (손실이 없었다라고 판단)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1f94c500",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-16-ff6f12737a0f>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_stock['ChangeCode'][df_stock['ChangeCode']==2] = 0\n",
      "<ipython-input-16-ff6f12737a0f>:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_stock['ChangeCode'][df_stock['ChangeCode']==3] = 1\n"
     ]
    }
   ],
   "source": [
    "df_stock['ChangeCode'][df_stock['ChangeCode']==2] = 0\n",
    "df_stock['ChangeCode'][df_stock['ChangeCode']==3] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "adc90c24",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_stock1 = df_stock[['Code','Name','ChangeCode','Date']]\n",
    "df_stock1 = df_stock1.sort_values(by=['Code','Date'])\n",
    "df_stock1.to_csv('./전처리/df_stock.csv', encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "31df120e",
   "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>Code</th>\n",
       "      <th>Name</th>\n",
       "      <th>ChangeCode</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>000030</td>\n",
       "      <td>우리은행</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-01-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>000030</td>\n",
       "      <td>우리은행</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>000030</td>\n",
       "      <td>우리은행</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-01-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>331</th>\n",
       "      <td>000030</td>\n",
       "      <td>우리은행</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-01-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>000030</td>\n",
       "      <td>우리은행</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-01-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23943</th>\n",
       "      <td>282330</td>\n",
       "      <td>BGF리테일</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24042</th>\n",
       "      <td>282330</td>\n",
       "      <td>BGF리테일</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24141</th>\n",
       "      <td>282330</td>\n",
       "      <td>BGF리테일</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24239</th>\n",
       "      <td>282330</td>\n",
       "      <td>BGF리테일</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24336</th>\n",
       "      <td>282330</td>\n",
       "      <td>BGF리테일</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-12-30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24357 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Code    Name  ChangeCode        Date\n",
       "27     000030    우리은행           0  2019-01-02\n",
       "127    000030    우리은행           1  2019-01-03\n",
       "228    000030    우리은행           0  2019-01-04\n",
       "331    000030    우리은행           0  2019-01-07\n",
       "430    000030    우리은행           1  2019-01-08\n",
       "...       ...     ...         ...         ...\n",
       "23943  282330  BGF리테일           1  2019-12-23\n",
       "24042  282330  BGF리테일           1  2019-12-24\n",
       "24141  282330  BGF리테일           1  2019-12-26\n",
       "24239  282330  BGF리테일           1  2019-12-27\n",
       "24336  282330  BGF리테일           1  2019-12-30\n",
       "\n",
       "[24357 rows x 4 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_stock1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "47ba0574",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib as mp\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "mp.rcParams['axes.unicode_minus'] = False          # 폰트 깨짐 방지\n",
    "plt.rcParams[\"font.family\"] = 'Malgun Gothic'      # 그래프 폰트"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e3b9163f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    24357.000000\n",
       "mean        -0.006764\n",
       "std          1.791314\n",
       "min        -27.700000\n",
       "25%         -0.980000\n",
       "50%          0.000000\n",
       "75%          0.910000\n",
       "max         17.850000\n",
       "Name: ChagesRatio, dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_stock['ChagesRatio'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f9b324e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df_stock['ChagesRatio'],range=(-30,30), bins=60, density=True)\n",
    "\n",
    "plt.xlabel('전일 종가 대비 변화율', size=12)\n",
    "plt.ylabel('density', size=12)\n",
    "plt.title('코스피 시가총액 상위 100위 종목 변화율 분포도', size = 10)\n",
    "\n",
    "plt.show()          "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b77ec27",
   "metadata": {},
   "source": [
    "0을 기준으로 50%가 (-0.98%, +0.91%)에 몰려 있음\n",
    "\n",
    "추가 label 기준 : \n",
    "\n",
    "-30% 부터 - 0.5% : 0  감소 \n",
    "+0.5% 부터 +30%  : 1  증가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "1751f565",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-19-a00856f79c9f>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['label'] = None\n",
      "<ipython-input-19-a00856f79c9f>:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['label'][df['ChagesRatio']<=0.5] = 0\n",
      "C:\\Users\\gimhu\\anaconda3\\lib\\site-packages\\pandas\\core\\series.py:992: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._where(~key, value, inplace=True)\n",
      "<ipython-input-19-a00856f79c9f>:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['label'][df['ChagesRatio']>0.5] = 1\n",
      "C:\\Users\\gimhu\\anaconda3\\lib\\site-packages\\pandas\\core\\series.py:992: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._where(~key, value, inplace=True)\n"
     ]
    }
   ],
   "source": [
    "df['label'] = None\n",
    "df['label'][df['ChagesRatio']<=0.5] = 0\n",
    "df['label'][df['ChagesRatio']>0.5] = 1\n",
    "\n",
    "df_stock2 = df[['Code','Name','label','Date']]\n",
    "df_stock2 = df_stock2.sort_values(by=['Code','Date'])\n",
    "df_stock2.to_csv('./전처리/df_stock1.csv', encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "db042692",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-20-daf5688ea780>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['label'] = None\n",
      "<ipython-input-20-daf5688ea780>:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['label'][df['ChagesRatio']<=1] = 0\n",
      "C:\\Users\\gimhu\\anaconda3\\lib\\site-packages\\pandas\\core\\series.py:992: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._where(~key, value, inplace=True)\n",
      "<ipython-input-20-daf5688ea780>:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['label'][df['ChagesRatio']>1] = 1\n",
      "C:\\Users\\gimhu\\anaconda3\\lib\\site-packages\\pandas\\core\\series.py:992: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._where(~key, value, inplace=True)\n"
     ]
    }
   ],
   "source": [
    "df['label'] = None\n",
    "df['label'][df['ChagesRatio']<=1] = 0\n",
    "df['label'][df['ChagesRatio']>1] = 1\n",
    "\n",
    "df_stock2 = df[['Code','Name','label','Date']]\n",
    "df_stock2 = df_stock2.sort_values(by=['Code','Date'])\n",
    "df_stock2.to_csv('./전처리/df_stock2.csv', encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "465c5d44",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "file_extension": ".py",
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