2day_samsung_finance.ipynb

{
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   "id": "df7c7ff6-936c-4f33-8cfe-5f81163776cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting package metadata (current_repodata.json): ...working... done\n",
      "Solving environment: ...working... done\n",
      "\n",
      "## Package Plan ##\n",
      "\n",
      "  environment location: C:\\Users\\user\\anaconda3\n",
      "\n",
      "  added / updated specs:\n",
      "    - pandas-datareader\n",
      "\n",
      "\n",
      "The following packages will be downloaded:\n",
      "\n",
      "    package                    |            build\n",
      "    ---------------------------|-----------------\n",
      "    conda-4.13.0               |   py39haa95532_0         923 KB\n",
      "    pandas-datareader-0.10.0   |     pyhd3eb1b0_0          71 KB\n",
      "    ------------------------------------------------------------\n",
      "                                           Total:         995 KB\n",
      "\n",
      "The following NEW packages will be INSTALLED:\n",
      "\n",
      "  pandas-datareader  pkgs/main/noarch::pandas-datareader-0.10.0-pyhd3eb1b0_0\n",
      "\n",
      "The following packages will be UPDATED:\n",
      "\n",
      "  conda                               4.12.0-py39haa95532_0 --> 4.13.0-py39haa95532_0\n",
      "\n",
      "\n",
      "\n",
      "Downloading and Extracting Packages\n",
      "\n",
      "conda-4.13.0         | 923 KB    |            |   0% \n",
      "conda-4.13.0         | 923 KB    | #7         |  17% \n",
      "conda-4.13.0         | 923 KB    | ########## | 100% \n",
      "conda-4.13.0         | 923 KB    | ########## | 100% \n",
      "\n",
      "pandas-datareader-0. | 71 KB     |            |   0% \n",
      "pandas-datareader-0. | 71 KB     | ########## | 100% \n",
      "Preparing transaction: ...working... done\n",
      "Verifying transaction: ...working... done\n",
      "Executing transaction: ...working... done\n",
      "\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "conda install pandas-datareader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5bcd2bff-07c4-4474-a795-a21b667b528c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting yfinance\n",
      "  Downloading yfinance-0.1.72-py2.py3-none-any.whl (27 kB)\n",
      "Collecting multitasking>=0.0.7\n",
      "  Downloading multitasking-0.0.10.tar.gz (8.2 kB)\n",
      "Requirement already satisfied: lxml>=4.5.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from yfinance) (4.8.0)\n",
      "Requirement already satisfied: requests>=2.26 in c:\\users\\user\\anaconda3\\lib\\site-packages (from yfinance) (2.27.1)\n",
      "Requirement already satisfied: pandas>=0.24.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from yfinance) (1.4.2)\n",
      "Requirement already satisfied: numpy>=1.15 in c:\\users\\user\\anaconda3\\lib\\site-packages (from yfinance) (1.21.5)\n",
      "Requirement already satisfied: python-dateutil>=2.8.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from pandas>=0.24.0->yfinance) (2.8.2)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from pandas>=0.24.0->yfinance) (2021.3)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\user\\anaconda3\\lib\\site-packages (from python-dateutil>=2.8.1->pandas>=0.24.0->yfinance) (1.16.0)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests>=2.26->yfinance) (2021.10.8)\n",
      "Requirement already satisfied: charset-normalizer~=2.0.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests>=2.26->yfinance) (2.0.4)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests>=2.26->yfinance) (1.26.9)\n",
      "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests>=2.26->yfinance) (3.3)\n",
      "Building wheels for collected packages: multitasking\n",
      "  Building wheel for multitasking (setup.py): started\n",
      "  Building wheel for multitasking (setup.py): finished with status 'done'\n",
      "  Created wheel for multitasking: filename=multitasking-0.0.10-py3-none-any.whl size=8500 sha256=e0531ec085a98cbbb45b6659d6b72453972c28647cbf4eb46d3a8f43e228b8b0\n",
      "  Stored in directory: c:\\users\\user\\appdata\\local\\pip\\cache\\wheels\\f2\\b5\\2c\\59ba95dcf854e542944c75fe3da584e4e3833b319735a0546c\n",
      "Successfully built multitasking\n",
      "Installing collected packages: multitasking, yfinance\n",
      "Successfully installed multitasking-0.0.10 yfinance-0.1.72\n"
     ]
    }
   ],
   "source": [
    "!pip install yfinance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "93b3d881-c52c-4724-8371-92c107f6a5ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://finance.yahoo.com/\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from pandas_datareader import data\n",
    "import yfinance as yfin\n",
    "yfin.pdr_override()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "3ed5e57e-10bd-4149-a4ea-18eb0cf5a6cc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    }
   ],
   "source": [
    "# samsung electronics\n",
    "df = data.get_data_yahoo('005930.KS', start='2020-01-01', end='2021-02-11')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "6ea6bef7-a1db-47c2-b826-648b1676f614",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 276 entries, 2020-01-02 to 2021-02-10\n",
      "Data columns (total 6 columns):\n",
      " #   Column     Non-Null Count  Dtype  \n",
      "---  ------     --------------  -----  \n",
      " 0   Open       276 non-null    float64\n",
      " 1   High       276 non-null    float64\n",
      " 2   Low        276 non-null    float64\n",
      " 3   Close      276 non-null    float64\n",
      " 4   Adj Close  276 non-null    float64\n",
      " 5   Volume     276 non-null    int64  \n",
      "dtypes: float64(5), int64(1)\n",
      "memory usage: 15.1 KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "f087a98e-cc1d-4150-9a58-51c5e5180947",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Open</th>\n",
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       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-02</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-03</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>2020-01-06</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-07</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-08</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2021-02-04</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>2021-02-05</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <th>2021-02-08</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-09</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-10</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>276 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Open   High    Low  Close  Adj Close  Volume\n",
       "Date                                                     \n",
       "2020-01-02  False  False  False  False      False   False\n",
       "2020-01-03  False  False  False  False      False   False\n",
       "2020-01-06  False  False  False  False      False   False\n",
       "2020-01-07  False  False  False  False      False   False\n",
       "2020-01-08  False  False  False  False      False   False\n",
       "...           ...    ...    ...    ...        ...     ...\n",
       "2021-02-04  False  False  False  False      False   False\n",
       "2021-02-05  False  False  False  False      False   False\n",
       "2021-02-08  False  False  False  False      False   False\n",
       "2021-02-09  False  False  False  False      False   False\n",
       "2021-02-10  False  False  False  False      False   False\n",
       "\n",
       "[276 rows x 6 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "cf134421-511b-4a6f-ad3a-73df94a03966",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
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       "      <th>Volume</th>\n",
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       "  </thead>\n",
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       "      <th>count</th>\n",
       "      <td>276.000000</td>\n",
       "      <td>276.000000</td>\n",
       "      <td>276.000000</td>\n",
       "      <td>276.000000</td>\n",
       "      <td>276.000000</td>\n",
       "      <td>2.760000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>60024.637681</td>\n",
       "      <td>60812.318841</td>\n",
       "      <td>59331.340580</td>\n",
       "      <td>60051.449275</td>\n",
       "      <td>57009.725076</td>\n",
       "      <td>2.295921e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>10835.925511</td>\n",
       "      <td>11160.551977</td>\n",
       "      <td>10751.116881</td>\n",
       "      <td>10930.302237</td>\n",
       "      <td>11159.429431</td>\n",
       "      <td>1.047140e+07</td>\n",
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       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>42600.000000</td>\n",
       "      <td>43550.000000</td>\n",
       "      <td>42300.000000</td>\n",
       "      <td>42500.000000</td>\n",
       "      <td>39695.613281</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>52950.000000</td>\n",
       "      <td>53600.000000</td>\n",
       "      <td>52175.000000</td>\n",
       "      <td>52875.000000</td>\n",
       "      <td>49988.554688</td>\n",
       "      <td>1.607145e+07</td>\n",
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       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>57800.000000</td>\n",
       "      <td>58550.000000</td>\n",
       "      <td>57300.000000</td>\n",
       "      <td>57900.000000</td>\n",
       "      <td>54795.605469</td>\n",
       "      <td>2.042467e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>61100.000000</td>\n",
       "      <td>61525.000000</td>\n",
       "      <td>60525.000000</td>\n",
       "      <td>61025.000000</td>\n",
       "      <td>57844.319336</td>\n",
       "      <td>2.692489e+07</td>\n",
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       "      <th>max</th>\n",
       "      <td>90300.000000</td>\n",
       "      <td>96800.000000</td>\n",
       "      <td>89500.000000</td>\n",
       "      <td>91000.000000</td>\n",
       "      <td>88908.179688</td>\n",
       "      <td>9.030618e+07</td>\n",
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      ],
      "text/plain": [
       "               Open          High           Low         Close     Adj Close  \\\n",
       "count    276.000000    276.000000    276.000000    276.000000    276.000000   \n",
       "mean   60024.637681  60812.318841  59331.340580  60051.449275  57009.725076   \n",
       "std    10835.925511  11160.551977  10751.116881  10930.302237  11159.429431   \n",
       "min    42600.000000  43550.000000  42300.000000  42500.000000  39695.613281   \n",
       "25%    52950.000000  53600.000000  52175.000000  52875.000000  49988.554688   \n",
       "50%    57800.000000  58550.000000  57300.000000  57900.000000  54795.605469   \n",
       "75%    61100.000000  61525.000000  60525.000000  61025.000000  57844.319336   \n",
       "max    90300.000000  96800.000000  89500.000000  91000.000000  88908.179688   \n",
       "\n",
       "             Volume  \n",
       "count  2.760000e+02  \n",
       "mean   2.295921e+07  \n",
       "std    1.047140e+07  \n",
       "min    0.000000e+00  \n",
       "25%    1.607145e+07  \n",
       "50%    2.042467e+07  \n",
       "75%    2.692489e+07  \n",
       "max    9.030618e+07  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "cb797a81-7273-49a5-8989-cc200328714c",
   "metadata": {},
   "outputs": [
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     "data": {
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     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.max(df['Close'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "11215320-3de2-481a-9f29-164e99657e57",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "42500.0"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.min(df['Close'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "51eee39b-f8dc-4e68-b61e-a925fea12dff",
   "metadata": {},
   "outputs": [
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       "60051.44927536232"
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     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(df['Close'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "88340523-fc53-476c-8966-14638c9137cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(276, 6)"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "ffe1326f-5c3d-4fc9-8a97-d44ab2453c00",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "276"
      ]
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     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "4bf22818-9fc6-4926-b528-67261330a81d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2020-01-02    55200.0\n",
       "2020-01-03    55500.0\n",
       "2020-01-06    55500.0\n",
       "2020-01-07    55800.0\n",
       "2020-01-08    56800.0\n",
       "               ...   \n",
       "2021-02-04    82500.0\n",
       "2021-02-05    83500.0\n",
       "2021-02-08    83000.0\n",
       "2021-02-09    82700.0\n",
       "2021-02-10    81600.0\n",
       "Name: Close, Length: 276, dtype: float64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
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   "source": [
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  {
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   "execution_count": 67,
   "id": "17496b7f-5df7-46a8-9c9f-9933a9368813",
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       "    <tr>\n",
       "      <th>2020-01-06</th>\n",
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       "      <th>2020-01-07</th>\n",
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       "      <th>2020-01-08</th>\n",
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       "      <th>2021-02-04</th>\n",
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       "      <th>2021-02-10</th>\n",
       "      <td>82600.0</td>\n",
       "      <td>81600.0</td>\n",
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       "               High      Low\n",
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   "execution_count": 69,
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       "      <td>85600.0</td>\n",
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       "      <td>81000.0</td>\n",
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       "      <td>84400.0</td>\n",
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       "      <td>81580.578125</td>\n",
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       "               Open     High      Low    Close     Adj Close    Volume\n",
       "Date                                                                  \n",
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       "2020-01-10  58800.0  59700.0  58300.0  59500.0  55573.859375  16000170\n",
       "...             ...      ...      ...      ...           ...       ...\n",
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       "\n",
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   "execution_count": 70,
   "id": "cef2a88c-9bfc-45aa-8f59-e8bea6773c24",
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       "               Open     High      Low    Close     Adj Close    Volume\n",
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   "execution_count": 72,
   "id": "d8468f6a-0cd0-4ebd-bc72-c47066ae29e2",
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "Open         8.980000e+04\n",
       "High         9.180000e+04\n",
       "Low          8.800000e+04\n",
       "Close        8.800000e+04\n",
       "Adj Close    8.597713e+04\n",
       "Volume       3.343181e+07\n",
       "Name: 2021-01-15 00:00:00, dtype: float64"
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     "execution_count": 72,
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       "High    91800.0\n",
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     "execution_count": 73,
     "metadata": {},
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   "source": [
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   "execution_count": 74,
   "id": "944b7545-25d4-49fc-8680-d0e0d53ce5a4",
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   "outputs": [
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       "Open         5.000000e+04\n",
       "High         5.070000e+04\n",
       "Low          4.970000e+04\n",
       "Close        5.070000e+04\n",
       "Adj Close    4.770416e+04\n",
       "Volume       2.759696e+07\n",
       "Name: 2020-05-29 00:00:00, dtype: float64"
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     },
     "execution_count": 74,
     "metadata": {},
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   "execution_count": 75,
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       "      <th>2021-02-10</th>\n",
       "      <td>82600.0</td>\n",
       "      <td>82600.0</td>\n",
       "      <td>81600.0</td>\n",
       "      <td>81600.0</td>\n",
       "      <td>79724.242188</td>\n",
       "      <td>23025766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-09</th>\n",
       "      <td>84000.0</td>\n",
       "      <td>84800.0</td>\n",
       "      <td>82700.0</td>\n",
       "      <td>82700.0</td>\n",
       "      <td>80798.960938</td>\n",
       "      <td>20898332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-08</th>\n",
       "      <td>83800.0</td>\n",
       "      <td>84200.0</td>\n",
       "      <td>83000.0</td>\n",
       "      <td>83000.0</td>\n",
       "      <td>81092.070312</td>\n",
       "      <td>15338765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-05</th>\n",
       "      <td>83100.0</td>\n",
       "      <td>84000.0</td>\n",
       "      <td>82500.0</td>\n",
       "      <td>83500.0</td>\n",
       "      <td>81580.578125</td>\n",
       "      <td>18036835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-04</th>\n",
       "      <td>83500.0</td>\n",
       "      <td>83800.0</td>\n",
       "      <td>82100.0</td>\n",
       "      <td>82500.0</td>\n",
       "      <td>80603.562500</td>\n",
       "      <td>24171688</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-08</th>\n",
       "      <td>56200.0</td>\n",
       "      <td>57400.0</td>\n",
       "      <td>55900.0</td>\n",
       "      <td>56800.0</td>\n",
       "      <td>53052.015625</td>\n",
       "      <td>23501171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-07</th>\n",
       "      <td>55700.0</td>\n",
       "      <td>56400.0</td>\n",
       "      <td>55600.0</td>\n",
       "      <td>55800.0</td>\n",
       "      <td>52118.000000</td>\n",
       "      <td>10009778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-06</th>\n",
       "      <td>54900.0</td>\n",
       "      <td>55600.0</td>\n",
       "      <td>54600.0</td>\n",
       "      <td>55500.0</td>\n",
       "      <td>51837.800781</td>\n",
       "      <td>10278951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-03</th>\n",
       "      <td>56000.0</td>\n",
       "      <td>56600.0</td>\n",
       "      <td>54900.0</td>\n",
       "      <td>55500.0</td>\n",
       "      <td>51837.800781</td>\n",
       "      <td>15422255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-02</th>\n",
       "      <td>55500.0</td>\n",
       "      <td>56000.0</td>\n",
       "      <td>55000.0</td>\n",
       "      <td>55200.0</td>\n",
       "      <td>51557.601562</td>\n",
       "      <td>12993228</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>276 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Open     High      Low    Close     Adj Close    Volume\n",
       "Date                                                                  \n",
       "2021-02-10  82600.0  82600.0  81600.0  81600.0  79724.242188  23025766\n",
       "2021-02-09  84000.0  84800.0  82700.0  82700.0  80798.960938  20898332\n",
       "2021-02-08  83800.0  84200.0  83000.0  83000.0  81092.070312  15338765\n",
       "2021-02-05  83100.0  84000.0  82500.0  83500.0  81580.578125  18036835\n",
       "2021-02-04  83500.0  83800.0  82100.0  82500.0  80603.562500  24171688\n",
       "...             ...      ...      ...      ...           ...       ...\n",
       "2020-01-08  56200.0  57400.0  55900.0  56800.0  53052.015625  23501171\n",
       "2020-01-07  55700.0  56400.0  55600.0  55800.0  52118.000000  10009778\n",
       "2020-01-06  54900.0  55600.0  54600.0  55500.0  51837.800781  10278951\n",
       "2020-01-03  56000.0  56600.0  54900.0  55500.0  51837.800781  15422255\n",
       "2020-01-02  55500.0  56000.0  55000.0  55200.0  51557.601562  12993228\n",
       "\n",
       "[276 rows x 6 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_index(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "823c758f-5256-49d7-8d65-d24ef22440a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2021-01-11    91000.0\n",
       "2021-01-12    90600.0\n",
       "2021-01-14    89700.0\n",
       "2021-01-13    89700.0\n",
       "2021-01-25    89400.0\n",
       "               ...   \n",
       "2020-04-01    45800.0\n",
       "2020-03-18    45600.0\n",
       "2020-03-20    45400.0\n",
       "2020-03-19    42950.0\n",
       "2020-03-23    42500.0\n",
       "Name: Close, Length: 276, dtype: float64"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Close'].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "a923e9f4-31bf-434c-956e-9ac174302bc9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>55500.0</td>\n",
       "      <td>56000.0</td>\n",
       "      <td>55000.0</td>\n",
       "      <td>55200.0</td>\n",
       "      <td>51557.593750</td>\n",
       "      <td>12993228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>56000.0</td>\n",
       "      <td>56600.0</td>\n",
       "      <td>54900.0</td>\n",
       "      <td>55500.0</td>\n",
       "      <td>51837.804688</td>\n",
       "      <td>15422255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-06</td>\n",
       "      <td>54900.0</td>\n",
       "      <td>55600.0</td>\n",
       "      <td>54600.0</td>\n",
       "      <td>55500.0</td>\n",
       "      <td>51837.804688</td>\n",
       "      <td>10278951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-07</td>\n",
       "      <td>55700.0</td>\n",
       "      <td>56400.0</td>\n",
       "      <td>55600.0</td>\n",
       "      <td>55800.0</td>\n",
       "      <td>52118.007812</td>\n",
       "      <td>10009778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-08</td>\n",
       "      <td>56200.0</td>\n",
       "      <td>57400.0</td>\n",
       "      <td>55900.0</td>\n",
       "      <td>56800.0</td>\n",
       "      <td>53052.023438</td>\n",
       "      <td>23501171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>271</th>\n",
       "      <td>2021-02-04</td>\n",
       "      <td>83500.0</td>\n",
       "      <td>83800.0</td>\n",
       "      <td>82100.0</td>\n",
       "      <td>82500.0</td>\n",
       "      <td>80603.562500</td>\n",
       "      <td>24171688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>2021-02-05</td>\n",
       "      <td>83100.0</td>\n",
       "      <td>84000.0</td>\n",
       "      <td>82500.0</td>\n",
       "      <td>83500.0</td>\n",
       "      <td>81580.570312</td>\n",
       "      <td>18036835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>2021-02-08</td>\n",
       "      <td>83800.0</td>\n",
       "      <td>84200.0</td>\n",
       "      <td>83000.0</td>\n",
       "      <td>83000.0</td>\n",
       "      <td>81092.078125</td>\n",
       "      <td>15338765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274</th>\n",
       "      <td>2021-02-09</td>\n",
       "      <td>84000.0</td>\n",
       "      <td>84800.0</td>\n",
       "      <td>82700.0</td>\n",
       "      <td>82700.0</td>\n",
       "      <td>80798.968750</td>\n",
       "      <td>20898332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>2021-02-10</td>\n",
       "      <td>82600.0</td>\n",
       "      <td>82600.0</td>\n",
       "      <td>81600.0</td>\n",
       "      <td>81600.0</td>\n",
       "      <td>79724.257812</td>\n",
       "      <td>23025766</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>276 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date     Open     High      Low    Close     Adj Close    Volume\n",
       "0   2020-01-02  55500.0  56000.0  55000.0  55200.0  51557.593750  12993228\n",
       "1   2020-01-03  56000.0  56600.0  54900.0  55500.0  51837.804688  15422255\n",
       "2   2020-01-06  54900.0  55600.0  54600.0  55500.0  51837.804688  10278951\n",
       "3   2020-01-07  55700.0  56400.0  55600.0  55800.0  52118.007812  10009778\n",
       "4   2020-01-08  56200.0  57400.0  55900.0  56800.0  53052.023438  23501171\n",
       "..         ...      ...      ...      ...      ...           ...       ...\n",
       "271 2021-02-04  83500.0  83800.0  82100.0  82500.0  80603.562500  24171688\n",
       "272 2021-02-05  83100.0  84000.0  82500.0  83500.0  81580.570312  18036835\n",
       "273 2021-02-08  83800.0  84200.0  83000.0  83000.0  81092.078125  15338765\n",
       "274 2021-02-09  84000.0  84800.0  82700.0  82700.0  80798.968750  20898332\n",
       "275 2021-02-10  82600.0  82600.0  81600.0  81600.0  79724.257812  23025766\n",
       "\n",
       "[276 rows x 7 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 인덱스 컬럼을 0부터 순차적으로 증가하는 정수로 변경하세요.\n",
    "# 새로운 인덱스를 추가하는 방법\n",
    "df.reset_index(inplace=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "7a1d1417-312a-457f-9a6f-4690cda30c98",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename(columns = {'Date':'날짜', 'High':'고가', 'Low':'저가'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "9d311763-d399-4b17-81c0-5715579990a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>56000.0</td>\n",
       "      <td>56600.0</td>\n",
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       "      <th>2</th>\n",
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       "      <td>55700.0</td>\n",
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       "      <td>55900.0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <th>271</th>\n",
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       "      <td>82500.0</td>\n",
       "      <td>80603.562500</td>\n",
       "      <td>24171688</td>\n",
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       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>83100.0</td>\n",
       "      <td>84000.0</td>\n",
       "      <td>82500.0</td>\n",
       "      <td>83500.0</td>\n",
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       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>83800.0</td>\n",
       "      <td>84200.0</td>\n",
       "      <td>83000.0</td>\n",
       "      <td>83000.0</td>\n",
       "      <td>81092.078125</td>\n",
       "      <td>15338765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274</th>\n",
       "      <td>84000.0</td>\n",
       "      <td>84800.0</td>\n",
       "      <td>82700.0</td>\n",
       "      <td>82700.0</td>\n",
       "      <td>80798.968750</td>\n",
       "      <td>20898332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>82600.0</td>\n",
       "      <td>82600.0</td>\n",
       "      <td>81600.0</td>\n",
       "      <td>81600.0</td>\n",
       "      <td>79724.257812</td>\n",
       "      <td>23025766</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>276 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Open       고가       저가    Close     Adj Close    Volume\n",
       "0    55500.0  56000.0  55000.0  55200.0  51557.593750  12993228\n",
       "1    56000.0  56600.0  54900.0  55500.0  51837.804688  15422255\n",
       "2    54900.0  55600.0  54600.0  55500.0  51837.804688  10278951\n",
       "3    55700.0  56400.0  55600.0  55800.0  52118.007812  10009778\n",
       "4    56200.0  57400.0  55900.0  56800.0  53052.023438  23501171\n",
       "..       ...      ...      ...      ...           ...       ...\n",
       "271  83500.0  83800.0  82100.0  82500.0  80603.562500  24171688\n",
       "272  83100.0  84000.0  82500.0  83500.0  81580.570312  18036835\n",
       "273  83800.0  84200.0  83000.0  83000.0  81092.078125  15338765\n",
       "274  84000.0  84800.0  82700.0  82700.0  80798.968750  20898332\n",
       "275  82600.0  82600.0  81600.0  81600.0  79724.257812  23025766\n",
       "\n",
       "[276 rows x 6 columns]"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop(['날짜'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "741683da-d203-4530-a243-b6d89a8be2fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>날짜</th>\n",
       "      <th>Open</th>\n",
       "      <th>고가</th>\n",
       "      <th>저가</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>55500.0</td>\n",
       "      <td>56000.0</td>\n",
       "      <td>55000.0</td>\n",
       "      <td>55200.0</td>\n",
       "      <td>51557.593750</td>\n",
       "      <td>12993228</td>\n",
       "      <td>-300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>56000.0</td>\n",
       "      <td>56600.0</td>\n",
       "      <td>54900.0</td>\n",
       "      <td>55500.0</td>\n",
       "      <td>51837.804688</td>\n",
       "      <td>15422255</td>\n",
       "      <td>-500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-06</td>\n",
       "      <td>54900.0</td>\n",
       "      <td>55600.0</td>\n",
       "      <td>54600.0</td>\n",
       "      <td>55500.0</td>\n",
       "      <td>51837.804688</td>\n",
       "      <td>10278951</td>\n",
       "      <td>600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-07</td>\n",
       "      <td>55700.0</td>\n",
       "      <td>56400.0</td>\n",
       "      <td>55600.0</td>\n",
       "      <td>55800.0</td>\n",
       "      <td>52118.007812</td>\n",
       "      <td>10009778</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-08</td>\n",
       "      <td>56200.0</td>\n",
       "      <td>57400.0</td>\n",
       "      <td>55900.0</td>\n",
       "      <td>56800.0</td>\n",
       "      <td>53052.023438</td>\n",
       "      <td>23501171</td>\n",
       "      <td>600.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271</th>\n",
       "      <td>2021-02-04</td>\n",
       "      <td>83500.0</td>\n",
       "      <td>83800.0</td>\n",
       "      <td>82100.0</td>\n",
       "      <td>82500.0</td>\n",
       "      <td>80603.562500</td>\n",
       "      <td>24171688</td>\n",
       "      <td>-1000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>2021-02-05</td>\n",
       "      <td>83100.0</td>\n",
       "      <td>84000.0</td>\n",
       "      <td>82500.0</td>\n",
       "      <td>83500.0</td>\n",
       "      <td>81580.570312</td>\n",
       "      <td>18036835</td>\n",
       "      <td>400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>2021-02-08</td>\n",
       "      <td>83800.0</td>\n",
       "      <td>84200.0</td>\n",
       "      <td>83000.0</td>\n",
       "      <td>83000.0</td>\n",
       "      <td>81092.078125</td>\n",
       "      <td>15338765</td>\n",
       "      <td>-800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274</th>\n",
       "      <td>2021-02-09</td>\n",
       "      <td>84000.0</td>\n",
       "      <td>84800.0</td>\n",
       "      <td>82700.0</td>\n",
       "      <td>82700.0</td>\n",
       "      <td>80798.968750</td>\n",
       "      <td>20898332</td>\n",
       "      <td>-1300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>2021-02-10</td>\n",
       "      <td>82600.0</td>\n",
       "      <td>82600.0</td>\n",
       "      <td>81600.0</td>\n",
       "      <td>81600.0</td>\n",
       "      <td>79724.257812</td>\n",
       "      <td>23025766</td>\n",
       "      <td>-1000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>276 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            날짜     Open       고가       저가    Close     Adj Close    Volume  \\\n",
       "0   2020-01-02  55500.0  56000.0  55000.0  55200.0  51557.593750  12993228   \n",
       "1   2020-01-03  56000.0  56600.0  54900.0  55500.0  51837.804688  15422255   \n",
       "2   2020-01-06  54900.0  55600.0  54600.0  55500.0  51837.804688  10278951   \n",
       "3   2020-01-07  55700.0  56400.0  55600.0  55800.0  52118.007812  10009778   \n",
       "4   2020-01-08  56200.0  57400.0  55900.0  56800.0  53052.023438  23501171   \n",
       "..         ...      ...      ...      ...      ...           ...       ...   \n",
       "271 2021-02-04  83500.0  83800.0  82100.0  82500.0  80603.562500  24171688   \n",
       "272 2021-02-05  83100.0  84000.0  82500.0  83500.0  81580.570312  18036835   \n",
       "273 2021-02-08  83800.0  84200.0  83000.0  83000.0  81092.078125  15338765   \n",
       "274 2021-02-09  84000.0  84800.0  82700.0  82700.0  80798.968750  20898332   \n",
       "275 2021-02-10  82600.0  82600.0  81600.0  81600.0  79724.257812  23025766   \n",
       "\n",
       "       diff  \n",
       "0    -300.0  \n",
       "1    -500.0  \n",
       "2     600.0  \n",
       "3     100.0  \n",
       "4     600.0  \n",
       "..      ...  \n",
       "271 -1000.0  \n",
       "272   400.0  \n",
       "273  -800.0  \n",
       "274 -1300.0  \n",
       "275 -1000.0  \n",
       "\n",
       "[276 rows x 8 columns]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['diff'] = df['Close'] - df['Open']\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "9ce594c9-fb36-49bc-90e0-e38798c94630",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "      <td>2020-01-07</td>\n",
       "      <td>55700.0</td>\n",
       "      <td>56400.0</td>\n",
       "      <td>55600.0</td>\n",
       "      <td>55800.0</td>\n",
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       "      <th>271</th>\n",
       "      <td>2021-02-04</td>\n",
       "      <td>83500.0</td>\n",
       "      <td>83800.0</td>\n",
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       "      <td>82500.0</td>\n",
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       "      <th>272</th>\n",
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       "      <td>82500.0</td>\n",
       "      <td>83500.0</td>\n",
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       "      <td>18036835</td>\n",
       "      <td>400.0</td>\n",
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       "      <td>2021-02-08</td>\n",
       "      <td>83800.0</td>\n",
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       "      <td>83000.0</td>\n",
       "      <td>83000.0</td>\n",
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       "      <td>15338765</td>\n",
       "      <td>-800.0</td>\n",
       "      <td>2021</td>\n",
       "      <td>2</td>\n",
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       "      <td>2021-02-09</td>\n",
       "      <td>84000.0</td>\n",
       "      <td>84800.0</td>\n",
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       "      <td>-1000.0</td>\n",
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       "      <td>2</td>\n",
       "      <td>10</td>\n",
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      "text/plain": [
       "            날짜     Open       고가       저가    Close     Adj Close    Volume  \\\n",
       "0   2020-01-02  55500.0  56000.0  55000.0  55200.0  51557.593750  12993228   \n",
       "1   2020-01-03  56000.0  56600.0  54900.0  55500.0  51837.804688  15422255   \n",
       "2   2020-01-06  54900.0  55600.0  54600.0  55500.0  51837.804688  10278951   \n",
       "3   2020-01-07  55700.0  56400.0  55600.0  55800.0  52118.007812  10009778   \n",
       "4   2020-01-08  56200.0  57400.0  55900.0  56800.0  53052.023438  23501171   \n",
       "..         ...      ...      ...      ...      ...           ...       ...   \n",
       "271 2021-02-04  83500.0  83800.0  82100.0  82500.0  80603.562500  24171688   \n",
       "272 2021-02-05  83100.0  84000.0  82500.0  83500.0  81580.570312  18036835   \n",
       "273 2021-02-08  83800.0  84200.0  83000.0  83000.0  81092.078125  15338765   \n",
       "274 2021-02-09  84000.0  84800.0  82700.0  82700.0  80798.968750  20898332   \n",
       "275 2021-02-10  82600.0  82600.0  81600.0  81600.0  79724.257812  23025766   \n",
       "\n",
       "       diff  Year  Month  Day  \n",
       "0    -300.0  2020      1    2  \n",
       "1    -500.0  2020      1    3  \n",
       "2     600.0  2020      1    6  \n",
       "3     100.0  2020      1    7  \n",
       "4     600.0  2020      1    8  \n",
       "..      ...   ...    ...  ...  \n",
       "271 -1000.0  2021      2    4  \n",
       "272   400.0  2021      2    5  \n",
       "273  -800.0  2021      2    8  \n",
       "274 -1300.0  2021      2    9  \n",
       "275 -1000.0  2021      2   10  \n",
       "\n",
       "[276 rows x 11 columns]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# datetime split 1\n",
    "df['Year'] = [d.year for d in df['날짜']]\n",
    "df['Month'] = [d.month for d in df['날짜']]\n",
    "df['Day'] = [d.day for d in df['날짜']]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3fabbb8e-1745-4c3f-83e9-69aae8a8754d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# datetime split 2\n",
    "import datetime\n",
    "df['Year'] = df['Date'].dt.year\n",
    "df['Month'] = df['Date'].dt.month\n",
    "df['Day'] = df['Date'].dt.day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "5aaa43c3-62e5-4a8f-857c-9245b98f4d65",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271</th>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274</th>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>276 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       날짜  Open    고가    저가 Close Adj Close Volume  diff  Year Month   Day\n",
       "0    2.00  2.00  2.00  2.00  2.00      2.00   2.00  2.00  2.00  2.00  2.00\n",
       "1    2.00  2.00  2.00  2.00  2.00      2.00   2.00  2.00  2.00  2.00  2.00\n",
       "2    2.00  2.00  2.00  2.00  2.00      2.00   2.00  2.00  2.00  2.00  2.00\n",
       "3    2.00  2.00  2.00  2.00  2.00      2.00   2.00  2.00  2.00  2.00  2.00\n",
       "4    2.00  2.00  2.00  2.00  2.00      2.00   2.00  2.00  2.00  2.00  2.00\n",
       "..    ...   ...   ...   ...   ...       ...    ...   ...   ...   ...   ...\n",
       "271  2.00  2.00  2.00  2.00  2.00      2.00   2.00  2.00  2.00  2.00  2.00\n",
       "272  2.00  2.00  2.00  2.00  2.00      2.00   2.00  2.00  2.00  2.00  2.00\n",
       "273  2.00  2.00  2.00  2.00  2.00      2.00   2.00  2.00  2.00  2.00  2.00\n",
       "274  2.00  2.00  2.00  2.00  2.00      2.00   2.00  2.00  2.00  2.00  2.00\n",
       "275  2.00  2.00  2.00  2.00  2.00      2.00   2.00  2.00  2.00  2.00  2.00\n",
       "\n",
       "[276 rows x 11 columns]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "format = lambda x: '%.2f' % 2\n",
    "df.applymap(format)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "e4b637ee-73de-450b-801d-f4f622538676",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "df['거래량'] = df['Volume'].apply(lambda x: \"{:,}\".format(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "857a8053-807a-49e0-831b-8c78b0d1370d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Month\n",
       "1     2.713407e+07\n",
       "2     1.921213e+07\n",
       "3     3.537865e+07\n",
       "4     2.120510e+07\n",
       "5     1.969814e+07\n",
       "6     2.351997e+07\n",
       "7     1.901368e+07\n",
       "8     2.008490e+07\n",
       "9     2.030011e+07\n",
       "10    1.723988e+07\n",
       "11    2.363959e+07\n",
       "12    2.523804e+07\n",
       "Name: Volume, dtype: float64"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "volume_mean = df['Volume'].groupby(df['Month']).mean()\n",
    "volume_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "088645d8-f414-4866-a594-406b39c71cd2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "날짜           0\n",
       "Open         0\n",
       "고가           0\n",
       "저가           0\n",
       "Close        0\n",
       "Adj Close    0\n",
       "Volume       0\n",
       "diff         0\n",
       "Year         0\n",
       "Month        0\n",
       "Day          0\n",
       "거래량          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "82bcf870-d1d6-4512-a8f2-f2be2f6b116c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.dropna()   # 결측치가 있을 경우 예시\n",
    "df.fillna({'High':90000, 'Low':50000})  # 결측치가 있을 경우 예시"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "f5fb4649-ce6c-4194-868c-8e2ae1b76256",
   "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",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>날짜</th>\n",
       "      <th>Open</th>\n",
       "      <th>고가</th>\n",
       "      <th>저가</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>diff</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>거래량</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>2020-11-02</td>\n",
       "      <td>56400.0</td>\n",
       "      <td>57500.0</td>\n",
       "      <td>56000.0</td>\n",
       "      <td>57400.0</td>\n",
       "      <td>54703.820312</td>\n",
       "      <td>20489076</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>20,489,076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>2020-11-03</td>\n",
       "      <td>57900.0</td>\n",
       "      <td>58900.0</td>\n",
       "      <td>57600.0</td>\n",
       "      <td>58800.0</td>\n",
       "      <td>56038.066406</td>\n",
       "      <td>14950919</td>\n",
       "      <td>900.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>14,950,919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>2020-11-04</td>\n",
       "      <td>58900.0</td>\n",
       "      <td>59000.0</td>\n",
       "      <td>57800.0</td>\n",
       "      <td>58500.0</td>\n",
       "      <td>55752.152344</td>\n",
       "      <td>21718561</td>\n",
       "      <td>-400.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>21,718,561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>2020-11-05</td>\n",
       "      <td>59000.0</td>\n",
       "      <td>60300.0</td>\n",
       "      <td>58800.0</td>\n",
       "      <td>60300.0</td>\n",
       "      <td>57467.605469</td>\n",
       "      <td>20639475</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>20,639,475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>2020-11-06</td>\n",
       "      <td>60700.0</td>\n",
       "      <td>60800.0</td>\n",
       "      <td>59600.0</td>\n",
       "      <td>60100.0</td>\n",
       "      <td>57277.007812</td>\n",
       "      <td>16910230</td>\n",
       "      <td>-600.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>16,910,230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>2020-11-09</td>\n",
       "      <td>60700.0</td>\n",
       "      <td>60900.0</td>\n",
       "      <td>60100.0</td>\n",
       "      <td>60200.0</td>\n",
       "      <td>57372.300781</td>\n",
       "      <td>15892961</td>\n",
       "      <td>-500.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>15,892,961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>2020-11-10</td>\n",
       "      <td>60500.0</td>\n",
       "      <td>60500.0</td>\n",
       "      <td>59500.0</td>\n",
       "      <td>60200.0</td>\n",
       "      <td>57372.300781</td>\n",
       "      <td>19073552</td>\n",
       "      <td>-300.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>19,073,552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>2020-11-11</td>\n",
       "      <td>60700.0</td>\n",
       "      <td>61400.0</td>\n",
       "      <td>60400.0</td>\n",
       "      <td>61300.0</td>\n",
       "      <td>58420.628906</td>\n",
       "      <td>25628510</td>\n",
       "      <td>600.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>25,628,510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>2020-11-12</td>\n",
       "      <td>61000.0</td>\n",
       "      <td>61400.0</td>\n",
       "      <td>60700.0</td>\n",
       "      <td>61000.0</td>\n",
       "      <td>58134.726562</td>\n",
       "      <td>19800573</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>19,800,573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>2020-11-13</td>\n",
       "      <td>61300.0</td>\n",
       "      <td>63200.0</td>\n",
       "      <td>61000.0</td>\n",
       "      <td>63200.0</td>\n",
       "      <td>60231.390625</td>\n",
       "      <td>31508829</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>13</td>\n",
       "      <td>31,508,829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>2020-11-16</td>\n",
       "      <td>64000.0</td>\n",
       "      <td>66700.0</td>\n",
       "      <td>63900.0</td>\n",
       "      <td>66300.0</td>\n",
       "      <td>63185.777344</td>\n",
       "      <td>36354334</td>\n",
       "      <td>2300.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>16</td>\n",
       "      <td>36,354,334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>2020-11-17</td>\n",
       "      <td>67000.0</td>\n",
       "      <td>67000.0</td>\n",
       "      <td>65600.0</td>\n",
       "      <td>65700.0</td>\n",
       "      <td>62613.960938</td>\n",
       "      <td>30204089</td>\n",
       "      <td>-1300.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>17</td>\n",
       "      <td>30,204,089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>2020-11-18</td>\n",
       "      <td>65700.0</td>\n",
       "      <td>66200.0</td>\n",
       "      <td>64700.0</td>\n",
       "      <td>64800.0</td>\n",
       "      <td>61756.230469</td>\n",
       "      <td>22963790</td>\n",
       "      <td>-900.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>18</td>\n",
       "      <td>22,963,790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>2020-11-19</td>\n",
       "      <td>64100.0</td>\n",
       "      <td>64800.0</td>\n",
       "      <td>63900.0</td>\n",
       "      <td>64600.0</td>\n",
       "      <td>61565.621094</td>\n",
       "      <td>16590290</td>\n",
       "      <td>500.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>19</td>\n",
       "      <td>16,590,290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>2020-11-20</td>\n",
       "      <td>63900.0</td>\n",
       "      <td>65200.0</td>\n",
       "      <td>63900.0</td>\n",
       "      <td>64700.0</td>\n",
       "      <td>61660.929688</td>\n",
       "      <td>15068682</td>\n",
       "      <td>800.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>20</td>\n",
       "      <td>15,068,682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>2020-11-23</td>\n",
       "      <td>64800.0</td>\n",
       "      <td>67800.0</td>\n",
       "      <td>64700.0</td>\n",
       "      <td>67500.0</td>\n",
       "      <td>64329.410156</td>\n",
       "      <td>27134398</td>\n",
       "      <td>2700.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>23</td>\n",
       "      <td>27,134,398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>2020-11-24</td>\n",
       "      <td>67900.0</td>\n",
       "      <td>69500.0</td>\n",
       "      <td>67000.0</td>\n",
       "      <td>67700.0</td>\n",
       "      <td>64520.015625</td>\n",
       "      <td>32158235</td>\n",
       "      <td>-200.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>24</td>\n",
       "      <td>32,158,235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>2020-11-25</td>\n",
       "      <td>67900.0</td>\n",
       "      <td>68300.0</td>\n",
       "      <td>66500.0</td>\n",
       "      <td>66600.0</td>\n",
       "      <td>63471.683594</td>\n",
       "      <td>32447065</td>\n",
       "      <td>-1300.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>25</td>\n",
       "      <td>32,447,065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>2020-11-26</td>\n",
       "      <td>66100.0</td>\n",
       "      <td>68000.0</td>\n",
       "      <td>66000.0</td>\n",
       "      <td>68000.0</td>\n",
       "      <td>64805.917969</td>\n",
       "      <td>19023323</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>26</td>\n",
       "      <td>19,023,323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>2020-11-27</td>\n",
       "      <td>68000.0</td>\n",
       "      <td>68400.0</td>\n",
       "      <td>67600.0</td>\n",
       "      <td>68200.0</td>\n",
       "      <td>64996.531250</td>\n",
       "      <td>14063434</td>\n",
       "      <td>200.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>27</td>\n",
       "      <td>14,063,434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>2020-11-30</td>\n",
       "      <td>68400.0</td>\n",
       "      <td>68600.0</td>\n",
       "      <td>66700.0</td>\n",
       "      <td>66700.0</td>\n",
       "      <td>63566.988281</td>\n",
       "      <td>43811016</td>\n",
       "      <td>-1700.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>30</td>\n",
       "      <td>43,811,016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>2020-12-01</td>\n",
       "      <td>67100.0</td>\n",
       "      <td>68300.0</td>\n",
       "      <td>67100.0</td>\n",
       "      <td>67800.0</td>\n",
       "      <td>64615.312500</td>\n",
       "      <td>22327173</td>\n",
       "      <td>700.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>22,327,173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>2020-12-02</td>\n",
       "      <td>68400.0</td>\n",
       "      <td>69900.0</td>\n",
       "      <td>68300.0</td>\n",
       "      <td>69500.0</td>\n",
       "      <td>66235.468750</td>\n",
       "      <td>29703942</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>29,703,942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>2020-12-03</td>\n",
       "      <td>70100.0</td>\n",
       "      <td>70500.0</td>\n",
       "      <td>69300.0</td>\n",
       "      <td>69700.0</td>\n",
       "      <td>66426.070312</td>\n",
       "      <td>23677989</td>\n",
       "      <td>-400.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>23,677,989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>70400.0</td>\n",
       "      <td>72100.0</td>\n",
       "      <td>70100.0</td>\n",
       "      <td>71500.0</td>\n",
       "      <td>68141.523438</td>\n",
       "      <td>28130533</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>28,130,533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>2020-12-07</td>\n",
       "      <td>72400.0</td>\n",
       "      <td>73500.0</td>\n",
       "      <td>71900.0</td>\n",
       "      <td>72900.0</td>\n",
       "      <td>69475.757812</td>\n",
       "      <td>28490496</td>\n",
       "      <td>500.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>7</td>\n",
       "      <td>28,490,496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>2020-12-08</td>\n",
       "      <td>72200.0</td>\n",
       "      <td>72900.0</td>\n",
       "      <td>71600.0</td>\n",
       "      <td>71700.0</td>\n",
       "      <td>68332.132812</td>\n",
       "      <td>25000338</td>\n",
       "      <td>-500.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>25,000,338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>2020-12-09</td>\n",
       "      <td>72100.0</td>\n",
       "      <td>73900.0</td>\n",
       "      <td>72000.0</td>\n",
       "      <td>73900.0</td>\n",
       "      <td>70428.781250</td>\n",
       "      <td>24077996</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>24,077,996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>2020-12-10</td>\n",
       "      <td>72700.0</td>\n",
       "      <td>73800.0</td>\n",
       "      <td>72500.0</td>\n",
       "      <td>72900.0</td>\n",
       "      <td>69475.757812</td>\n",
       "      <td>39882928</td>\n",
       "      <td>200.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>39,882,928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>2020-12-11</td>\n",
       "      <td>73500.0</td>\n",
       "      <td>73800.0</td>\n",
       "      <td>73100.0</td>\n",
       "      <td>73400.0</td>\n",
       "      <td>69952.281250</td>\n",
       "      <td>18486672</td>\n",
       "      <td>-100.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>11</td>\n",
       "      <td>18,486,672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>73600.0</td>\n",
       "      <td>74500.0</td>\n",
       "      <td>73200.0</td>\n",
       "      <td>73800.0</td>\n",
       "      <td>70333.492188</td>\n",
       "      <td>21510415</td>\n",
       "      <td>200.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>14</td>\n",
       "      <td>21,510,415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>73800.0</td>\n",
       "      <td>74100.0</td>\n",
       "      <td>73300.0</td>\n",
       "      <td>73800.0</td>\n",
       "      <td>70333.492188</td>\n",
       "      <td>20863671</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>20,863,671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>2020-12-16</td>\n",
       "      <td>74100.0</td>\n",
       "      <td>74500.0</td>\n",
       "      <td>73400.0</td>\n",
       "      <td>73800.0</td>\n",
       "      <td>70333.492188</td>\n",
       "      <td>17512081</td>\n",
       "      <td>-300.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>17,512,081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>2020-12-17</td>\n",
       "      <td>73400.0</td>\n",
       "      <td>73700.0</td>\n",
       "      <td>72600.0</td>\n",
       "      <td>73300.0</td>\n",
       "      <td>69856.968750</td>\n",
       "      <td>24293214</td>\n",
       "      <td>-100.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>17</td>\n",
       "      <td>24,293,214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>2020-12-18</td>\n",
       "      <td>73300.0</td>\n",
       "      <td>73700.0</td>\n",
       "      <td>73000.0</td>\n",
       "      <td>73000.0</td>\n",
       "      <td>69571.062500</td>\n",
       "      <td>17613029</td>\n",
       "      <td>-300.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>18</td>\n",
       "      <td>17,613,029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>73100.0</td>\n",
       "      <td>73400.0</td>\n",
       "      <td>72000.0</td>\n",
       "      <td>73000.0</td>\n",
       "      <td>69571.062500</td>\n",
       "      <td>20367355</td>\n",
       "      <td>-100.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>21</td>\n",
       "      <td>20,367,355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>2020-12-22</td>\n",
       "      <td>72500.0</td>\n",
       "      <td>73200.0</td>\n",
       "      <td>72100.0</td>\n",
       "      <td>72300.0</td>\n",
       "      <td>68903.945312</td>\n",
       "      <td>16304910</td>\n",
       "      <td>-200.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>22</td>\n",
       "      <td>16,304,910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>2020-12-23</td>\n",
       "      <td>72400.0</td>\n",
       "      <td>74000.0</td>\n",
       "      <td>72300.0</td>\n",
       "      <td>73900.0</td>\n",
       "      <td>70428.781250</td>\n",
       "      <td>19411326</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>23</td>\n",
       "      <td>19,411,326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>2020-12-24</td>\n",
       "      <td>74100.0</td>\n",
       "      <td>78800.0</td>\n",
       "      <td>74000.0</td>\n",
       "      <td>77800.0</td>\n",
       "      <td>74145.601562</td>\n",
       "      <td>32502870</td>\n",
       "      <td>3700.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>24</td>\n",
       "      <td>32,502,870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>2020-12-28</td>\n",
       "      <td>79000.0</td>\n",
       "      <td>80100.0</td>\n",
       "      <td>78200.0</td>\n",
       "      <td>78700.0</td>\n",
       "      <td>75003.328125</td>\n",
       "      <td>40085044</td>\n",
       "      <td>-300.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>28</td>\n",
       "      <td>40,085,044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>2020-12-29</td>\n",
       "      <td>78800.0</td>\n",
       "      <td>78900.0</td>\n",
       "      <td>77300.0</td>\n",
       "      <td>78300.0</td>\n",
       "      <td>76500.109375</td>\n",
       "      <td>30339449</td>\n",
       "      <td>-500.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>29</td>\n",
       "      <td>30,339,449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>77400.0</td>\n",
       "      <td>81300.0</td>\n",
       "      <td>77300.0</td>\n",
       "      <td>81000.0</td>\n",
       "      <td>79138.054688</td>\n",
       "      <td>29417421</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>30</td>\n",
       "      <td>29,417,421</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            날짜     Open       고가       저가    Close     Adj Close    Volume  \\\n",
       "206 2020-11-02  56400.0  57500.0  56000.0  57400.0  54703.820312  20489076   \n",
       "207 2020-11-03  57900.0  58900.0  57600.0  58800.0  56038.066406  14950919   \n",
       "208 2020-11-04  58900.0  59000.0  57800.0  58500.0  55752.152344  21718561   \n",
       "209 2020-11-05  59000.0  60300.0  58800.0  60300.0  57467.605469  20639475   \n",
       "210 2020-11-06  60700.0  60800.0  59600.0  60100.0  57277.007812  16910230   \n",
       "211 2020-11-09  60700.0  60900.0  60100.0  60200.0  57372.300781  15892961   \n",
       "212 2020-11-10  60500.0  60500.0  59500.0  60200.0  57372.300781  19073552   \n",
       "213 2020-11-11  60700.0  61400.0  60400.0  61300.0  58420.628906  25628510   \n",
       "214 2020-11-12  61000.0  61400.0  60700.0  61000.0  58134.726562  19800573   \n",
       "215 2020-11-13  61300.0  63200.0  61000.0  63200.0  60231.390625  31508829   \n",
       "216 2020-11-16  64000.0  66700.0  63900.0  66300.0  63185.777344  36354334   \n",
       "217 2020-11-17  67000.0  67000.0  65600.0  65700.0  62613.960938  30204089   \n",
       "218 2020-11-18  65700.0  66200.0  64700.0  64800.0  61756.230469  22963790   \n",
       "219 2020-11-19  64100.0  64800.0  63900.0  64600.0  61565.621094  16590290   \n",
       "220 2020-11-20  63900.0  65200.0  63900.0  64700.0  61660.929688  15068682   \n",
       "221 2020-11-23  64800.0  67800.0  64700.0  67500.0  64329.410156  27134398   \n",
       "222 2020-11-24  67900.0  69500.0  67000.0  67700.0  64520.015625  32158235   \n",
       "223 2020-11-25  67900.0  68300.0  66500.0  66600.0  63471.683594  32447065   \n",
       "224 2020-11-26  66100.0  68000.0  66000.0  68000.0  64805.917969  19023323   \n",
       "225 2020-11-27  68000.0  68400.0  67600.0  68200.0  64996.531250  14063434   \n",
       "226 2020-11-30  68400.0  68600.0  66700.0  66700.0  63566.988281  43811016   \n",
       "227 2020-12-01  67100.0  68300.0  67100.0  67800.0  64615.312500  22327173   \n",
       "228 2020-12-02  68400.0  69900.0  68300.0  69500.0  66235.468750  29703942   \n",
       "229 2020-12-03  70100.0  70500.0  69300.0  69700.0  66426.070312  23677989   \n",
       "230 2020-12-04  70400.0  72100.0  70100.0  71500.0  68141.523438  28130533   \n",
       "231 2020-12-07  72400.0  73500.0  71900.0  72900.0  69475.757812  28490496   \n",
       "232 2020-12-08  72200.0  72900.0  71600.0  71700.0  68332.132812  25000338   \n",
       "233 2020-12-09  72100.0  73900.0  72000.0  73900.0  70428.781250  24077996   \n",
       "234 2020-12-10  72700.0  73800.0  72500.0  72900.0  69475.757812  39882928   \n",
       "235 2020-12-11  73500.0  73800.0  73100.0  73400.0  69952.281250  18486672   \n",
       "236 2020-12-14  73600.0  74500.0  73200.0  73800.0  70333.492188  21510415   \n",
       "237 2020-12-15  73800.0  74100.0  73300.0  73800.0  70333.492188  20863671   \n",
       "238 2020-12-16  74100.0  74500.0  73400.0  73800.0  70333.492188  17512081   \n",
       "239 2020-12-17  73400.0  73700.0  72600.0  73300.0  69856.968750  24293214   \n",
       "240 2020-12-18  73300.0  73700.0  73000.0  73000.0  69571.062500  17613029   \n",
       "241 2020-12-21  73100.0  73400.0  72000.0  73000.0  69571.062500  20367355   \n",
       "242 2020-12-22  72500.0  73200.0  72100.0  72300.0  68903.945312  16304910   \n",
       "243 2020-12-23  72400.0  74000.0  72300.0  73900.0  70428.781250  19411326   \n",
       "244 2020-12-24  74100.0  78800.0  74000.0  77800.0  74145.601562  32502870   \n",
       "245 2020-12-28  79000.0  80100.0  78200.0  78700.0  75003.328125  40085044   \n",
       "246 2020-12-29  78800.0  78900.0  77300.0  78300.0  76500.109375  30339449   \n",
       "247 2020-12-30  77400.0  81300.0  77300.0  81000.0  79138.054688  29417421   \n",
       "\n",
       "       diff  Year  Month  Day         거래량  \n",
       "206  1000.0  2020     11    2  20,489,076  \n",
       "207   900.0  2020     11    3  14,950,919  \n",
       "208  -400.0  2020     11    4  21,718,561  \n",
       "209  1300.0  2020     11    5  20,639,475  \n",
       "210  -600.0  2020     11    6  16,910,230  \n",
       "211  -500.0  2020     11    9  15,892,961  \n",
       "212  -300.0  2020     11   10  19,073,552  \n",
       "213   600.0  2020     11   11  25,628,510  \n",
       "214     0.0  2020     11   12  19,800,573  \n",
       "215  1900.0  2020     11   13  31,508,829  \n",
       "216  2300.0  2020     11   16  36,354,334  \n",
       "217 -1300.0  2020     11   17  30,204,089  \n",
       "218  -900.0  2020     11   18  22,963,790  \n",
       "219   500.0  2020     11   19  16,590,290  \n",
       "220   800.0  2020     11   20  15,068,682  \n",
       "221  2700.0  2020     11   23  27,134,398  \n",
       "222  -200.0  2020     11   24  32,158,235  \n",
       "223 -1300.0  2020     11   25  32,447,065  \n",
       "224  1900.0  2020     11   26  19,023,323  \n",
       "225   200.0  2020     11   27  14,063,434  \n",
       "226 -1700.0  2020     11   30  43,811,016  \n",
       "227   700.0  2020     12    1  22,327,173  \n",
       "228  1100.0  2020     12    2  29,703,942  \n",
       "229  -400.0  2020     12    3  23,677,989  \n",
       "230  1100.0  2020     12    4  28,130,533  \n",
       "231   500.0  2020     12    7  28,490,496  \n",
       "232  -500.0  2020     12    8  25,000,338  \n",
       "233  1800.0  2020     12    9  24,077,996  \n",
       "234   200.0  2020     12   10  39,882,928  \n",
       "235  -100.0  2020     12   11  18,486,672  \n",
       "236   200.0  2020     12   14  21,510,415  \n",
       "237     0.0  2020     12   15  20,863,671  \n",
       "238  -300.0  2020     12   16  17,512,081  \n",
       "239  -100.0  2020     12   17  24,293,214  \n",
       "240  -300.0  2020     12   18  17,613,029  \n",
       "241  -100.0  2020     12   21  20,367,355  \n",
       "242  -200.0  2020     12   22  16,304,910  \n",
       "243  1500.0  2020     12   23  19,411,326  \n",
       "244  3700.0  2020     12   24  32,502,870  \n",
       "245  -300.0  2020     12   28  40,085,044  \n",
       "246  -500.0  2020     12   29  30,339,449  \n",
       "247  3600.0  2020     12   30  29,417,421  "
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dec_df = df[df['Month'] == 12]\n",
    "nov_df = df[df['Month'] == 11]\n",
    "\n",
    "nov_dec_df = pd.concat([nov_df, dec_df])\n",
    "nov_dec_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6a80be52-826a-4568-ba1c-231bd000f6e0",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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