j_02_Pandas.ipynb

{"cells":[{"cell_type":"markdown","id":"b0fe0fe6","metadata":{"collapsed":true,"id":"b0fe0fe6","jupyter":{"outputs_hidden":true}},"source":["# pandas\n","- 데이터프레임(DataFrame)을 사용하기 위한 패키지\n","- 데이터프레임은 2차원 테이블 구조로 \"액셀\"과 같은 용도로 사용된다\n","- (참고) 1차원의 데이터를 다루기 위해서는 리스트가 사용된다\n","- copy()"]},{"cell_type":"markdown","id":"d570f2db","metadata":{"id":"d570f2db"},"source":["## 데이터 프레임 생성 방법\n","- 딕셔너리로부터 만드는 방법\n","- 배열, 리스트, 튜플로부터 만드는 방법\n","- csv 파일을 읽어 만드는 방법\n","- 액셀 파일을 읽어 만드는 방법"]},{"cell_type":"markdown","id":"4bea25ce","metadata":{"id":"4bea25ce"},"source":["## import"]},{"cell_type":"code","execution_count":1,"id":"d58c49b8","metadata":{"id":"d58c49b8","executionInfo":{"status":"ok","timestamp":1727050808235,"user_tz":-540,"elapsed":1161,"user":{"displayName":"전석환","userId":"07131861431613450544"}}},"outputs":[],"source":["import pandas as pd\n","\n","# 레티나 디스플레이를 사용하는 경우 설정\n","%config InlineBackend.figure_format = 'retina'"]},{"cell_type":"code","execution_count":2,"id":"cb0b3e0e","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"cb0b3e0e","executionInfo":{"status":"ok","timestamp":1727050808236,"user_tz":-540,"elapsed":14,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"8cbfba4e-8f04-4ba1-9e29-41647df1777f"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["  city  population  temp\n","0   서울         990    17\n","1   부산         350    18\n","2   대구         250    18\n","3   대전         154    19\n","4   광주         150    20"],"text/html":["\n","  <div id=\"df-2471a361-a732-494d-ac67-32533b3651e5\" class=\"colab-df-container\">\n","    <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>city</th>\n","      <th>population</th>\n","      <th>temp</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>서울</td>\n","      <td>990</td>\n","      <td>17</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>부산</td>\n","      <td>350</td>\n","      <td>18</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>대구</td>\n","      <td>250</td>\n","      <td>18</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>대전</td>\n","      <td>154</td>\n","      <td>19</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>광주</td>\n","      <td>150</td>\n","      <td>20</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2471a361-a732-494d-ac67-32533b3651e5')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-2471a361-a732-494d-ac67-32533b3651e5 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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pd.DataFrame(x)\n","df"]},{"cell_type":"code","execution_count":3,"id":"1e5672f4-f1d5-4559-97f3-ef1cf11ac83e","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"1e5672f4-f1d5-4559-97f3-ef1cf11ac83e","executionInfo":{"status":"ok","timestamp":1727050808236,"user_tz":-540,"elapsed":10,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"53204ae7-b957-4b5a-d083-2b9529e57a49"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["  city  population  temp\n","0   서울         990    17\n","1   부산         350    18\n","2   대구         250    18\n","3   대전         154    19\n","4   광주         150    20"],"text/html":["\n","  <div id=\"df-be29c78b-e730-4e94-8ef8-c7b13dc94803\" class=\"colab-df-container\">\n","    <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 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],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"temp\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 17,\n        \"max\": 20,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          18,\n          20,\n          17\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":3}],"source":["# 리스트로 DataFrame 생성\n","data = [\n","    ['서울', 990, 17],\n","    ['부산', 350, 18],\n","    ['대구', 250, 18],\n","    ['대전', 154, 19],\n","    ['광주', 150, 20]\n","]\n","\n","# 열 이름을 지정하여 DataFrame 생성\n","df = pd.DataFrame(data, columns=['city', 'population', 'temp'])\n","df"]},{"cell_type":"code","execution_count":4,"id":"23469570-bdd7-4351-a2dc-a652e6e6c021","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"23469570-bdd7-4351-a2dc-a652e6e6c021","executionInfo":{"status":"ok","timestamp":1727050808236,"user_tz":-540,"elapsed":9,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"7ad9760a-ad04-497b-848a-e688c82ecff0"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["  city  population  temp\n","0   서울         990    17\n","1   부산         350    18\n","2   대구         250    18\n","3   대전         154    19\n","4   광주         150    20"],"text/html":["\n","  <div id=\"df-a9caf9cc-ce46-4f21-adce-1b8c8fc9cc82\" class=\"colab-df-container\">\n","    <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 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'data.csv'는 파일 경로\n","df"]},{"cell_type":"code","execution_count":5,"id":"36fc6f01-f797-4008-8d48-152b1896ce42","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"36fc6f01-f797-4008-8d48-152b1896ce42","executionInfo":{"status":"ok","timestamp":1727050809275,"user_tz":-540,"elapsed":1047,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"53796294-570b-46e5-d75e-c7732587df1d"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["  city  population  temp\n","0   서울         990    17\n","1   부산         350    18\n","2   대구         250    18\n","3   대전         154    19\n","4   광주         150    20"],"text/html":["\n","  <div id=\"df-80a1fbf2-4e84-40ad-ab87-2a75893de6d3\" class=\"colab-df-container\">\n","    <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>city</th>\n","      <th>population</th>\n","      <th>temp</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>서울</td>\n","      <td>990</td>\n","      <td>17</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>부산</td>\n","      <td>350</td>\n","      <td>18</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>대구</td>\n","      <td>250</td>\n","      <td>18</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>대전</td>\n","      <td>154</td>\n","      <td>19</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>광주</td>\n","      <td>150</td>\n","      <td>20</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-80a1fbf2-4e84-40ad-ab87-2a75893de6d3')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-80a1fbf2-4e84-40ad-ab87-2a75893de6d3 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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'data.xlsx'는 파일 경로\n","df"]},{"cell_type":"code","execution_count":6,"id":"a4923892","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"a4923892","executionInfo":{"status":"ok","timestamp":1727050809276,"user_tz":-540,"elapsed":15,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"09e58933-fca8-4c22-c164-7e69d86df3c1"},"outputs":[{"output_type":"stream","name":"stdout","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 5 entries, 0 to 4\n","Data columns (total 3 columns):\n"," #   Column      Non-Null Count  Dtype \n","---  ------      --------------  ----- \n"," 0   city        5 non-null      object\n"," 1   population  5 non-null      int64 \n"," 2   temp        5 non-null      int64 \n","dtypes: int64(2), object(1)\n","memory usage: 248.0+ bytes\n","None\n"]}],"source":["print(df.info())"]},{"cell_type":"markdown","id":"b9ef3f92","metadata":{"id":"b9ef3f92"},"source":["- 딕셔너리의 키를 컬럼명으로, 값을 데이터로 사용한다\n","- 인덱스(행 번호)가 자동으로 만들어진다"]},{"cell_type":"code","execution_count":7,"id":"5bd607ec","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"5bd607ec","executionInfo":{"status":"ok","timestamp":1727050809276,"user_tz":-540,"elapsed":11,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"849cb27e-2501-47ae-fee6-6f63c60e9f22"},"outputs":[{"output_type":"stream","name":"stdout","text":["(5, 3)\n","5\n","3\n"]}],"source":["## 데이터프레임의 구조(shape)와 행과 열의 수 확인하기\n","\n","print(df.shape)    # 데이터프레임 구조\n","print(df.shape[0]) # 행의 수\n","print(df.shape[1]) # 열의 수"]},{"cell_type":"markdown","id":"bafe6521","metadata":{"id":"bafe6521"},"source":["# 데이터프레임 다루기"]},{"cell_type":"code","execution_count":8,"id":"cf292199","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"cf292199","executionInfo":{"status":"ok","timestamp":1727050809276,"user_tz":-540,"elapsed":10,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"930af78a-7a7e-4579-8488-a0438104bd24"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["  city  temp\n","0   서울    17\n","1   부산    18\n","2   대구    18\n","3   대전    19\n","4   광주    20"],"text/html":["\n","  <div id=\"df-04a59f5f-f378-4df1-9838-d21ea20d261f\" class=\"colab-df-container\">\n","    <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>city</th>\n","      <th>temp</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>서울</td>\n","      <td>17</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>부산</td>\n","      <td>18</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>대구</td>\n","      <td>18</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>대전</td>\n","      <td>19</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>광주</td>\n","      <td>20</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-04a59f5f-f378-4df1-9838-d21ea20d261f')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-04a59f5f-f378-4df1-9838-d21ea20d261f button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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사용"]},{"cell_type":"code","execution_count":10,"id":"cfc25e8d","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"cfc25e8d","outputId":"56ae9abb-c2de-4309-dec4-efeed7bd87d6","executionInfo":{"status":"ok","timestamp":1727050809276,"user_tz":-540,"elapsed":9,"user":{"displayName":"전석환","userId":"07131861431613450544"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["   도시   인구  날씨\n","0  서울  990  17\n","1  부산  350  18\n","2  대구  250  18\n","3  대전  154  19\n","4  광주  150  20"],"text/html":["\n","  <div id=\"df-1dbf4d2c-d6af-4a6c-b503-28aba817b1e1\" class=\"colab-df-container\">\n","    <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 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250\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\ub0a0\\uc528\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 17,\n        \"max\": 20,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          18,\n          20,\n          17\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":10}],"source":["## 컬럼명 바꾸기\n","\n","df.columns = ['도시','인구','날씨']\n","df"]},{"cell_type":"markdown","id":"f76fabe7","metadata":{"id":"f76fabe7"},"source":["## copy()\n","- 물리적인 복사(백업)를 하려면 copy()를 사용한다\n","- 처리된 원본을 백업해둔다"]},{"cell_type":"code","execution_count":11,"id":"428293c9","metadata":{"id":"428293c9","executionInfo":{"status":"ok","timestamp":1727050809276,"user_tz":-540,"elapsed":8,"user":{"displayName":"전석환","userId":"07131861431613450544"}}},"outputs":[],"source":["df_backup = df.copy()             # df 백업하기"]},{"cell_type":"code","execution_count":12,"id":"640acbee","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"640acbee","executionInfo":{"status":"ok","timestamp":1727050809276,"user_tz":-540,"elapsed":8,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"903801b7-9602-4da0-e717-152a02bf1265"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["[1, 2, 3, 4]"]},"metadata":{},"execution_count":12}],"source":["# copy() 사용 예\n","\n","x = list((1,2,3,4))\n","x"]},{"cell_type":"code","execution_count":13,"id":"e441b3a7","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"e441b3a7","executionInfo":{"status":"ok","timestamp":1727050809276,"user_tz":-540,"elapsed":7,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"eff63d5c-fd54-42a3-92a1-7b7d839f392b"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["[1, 2, 3, 4, 100]"]},"metadata":{},"execution_count":13}],"source":["y = x\n","y.append(100)\n","y"]},{"cell_type":"code","execution_count":14,"id":"433e891a","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"433e891a","executionInfo":{"status":"ok","timestamp":1727050809742,"user_tz":-540,"elapsed":473,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"f1250741-c3df-4544-96dd-05014da35d08"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["[1, 2, 3, 4, 100]"]},"metadata":{},"execution_count":14}],"source":["# y를 변경하면 x도 같이 변경된다 (물리적인 복사를 하지 않았다)\n","# 같은 메모리를 가리키며 변수의 이름만 복사한 것임\n","x"]},{"cell_type":"code","execution_count":15,"id":"041f03a3","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"041f03a3","executionInfo":{"status":"ok","timestamp":1727050809742,"user_tz":-540,"elapsed":9,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"9ea1e6f4-49ff-43e8-9fbb-26d77964a590"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["[1, 2, 3, 4, 100]"]},"metadata":{},"execution_count":15}],"source":["# copy()를 사용하여 물리적인 복사를 하겠다\n","\n","x = list((1,2,3,4))\n","y = x.copy()\n","y.append(100)\n","y"]},{"cell_type":"code","execution_count":16,"id":"0c6d75dd","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"0c6d75dd","executionInfo":{"status":"ok","timestamp":1727050809742,"user_tz":-540,"elapsed":8,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"2c134188-77ee-4606-ad29-042f552ecb33"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["[1, 2, 3, 4]"]},"metadata":{},"execution_count":16}],"source":["# y를 바꾸어도 x는 변경되지 않는다\n","x"]},{"cell_type":"code","execution_count":17,"id":"860fd4a5-9e22-4489-aac3-7941b5528523","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"860fd4a5-9e22-4489-aac3-7941b5528523","executionInfo":{"status":"ok","timestamp":1727050809742,"user_tz":-540,"elapsed":8,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"26c37868-36fa-42ab-99e5-f3ea955c7983"},"outputs":[{"output_type":"stream","name":"stdout","text":["원본 데이터프레임:\n","    도시   인구  날씨\n","0  서울  990  17\n","1  부산  350  18\n","2  대구  250  18\n","3  대전  154  19\n","4  광주  150  20\n","\n","복사된 데이터프레임:\n","    도시    인구  날씨\n","0  서울  1000  17\n","1  부산   400  18\n","2  대구   300  18\n","3  대전   200  19\n","4  광주   300  20\n"]}],"source":["# 데이터프레임 복사\n","df_copy = df.copy()\n","\n","# 복사본 수정\n","df_copy['인구'] = [1000, 400, 300, 200, 300]\n","\n","# 출력\n","print(\"원본 데이터프레임:\\n\", df)\n","print(\"\\n복사된 데이터프레임:\\n\", df_copy)\n"]},{"cell_type":"markdown","id":"570cb194","metadata":{"id":"570cb194"},"source":["## 인덱스 바꾸기"]},{"cell_type":"code","execution_count":18,"id":"ce9ec521","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ce9ec521","executionInfo":{"status":"ok","timestamp":1727050809742,"user_tz":-540,"elapsed":7,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"e216bd03-b40a-4baa-e6d8-6a3a37f23471"},"outputs":[{"output_type":"stream","name":"stdout","text":["Index(['도시', '인구', '날씨'], dtype='object')\n","RangeIndex(start=0, stop=5, step=1)\n"]}],"source":["## 컬럼과 행의 인덱스 보기\n","\n","print(df.columns)\n","print(df.index)"]},{"cell_type":"code","execution_count":19,"id":"97c24503","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"id":"97c24503","outputId":"624bd7bb-bb57-4526-d128-20b8ed9f4181","executionInfo":{"status":"ok","timestamp":1727050809742,"user_tz":-540,"elapsed":7,"user":{"displayName":"전석환","userId":"07131861431613450544"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     인구  날씨\n","도시         \n","서울  990  17\n","부산  350  18\n","대구  250  18\n","대전  154  19\n","광주  150  20"],"text/html":["\n","  <div id=\"df-7cd1effe-bf97-4a0d-947a-d2200ee43332\" class=\"colab-df-container\">\n","    <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>인구</th>\n","      <th>날씨</th>\n","    </tr>\n","    <tr>\n","      <th>도시</th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>서울</th>\n","      <td>990</td>\n","      <td>17</td>\n","    </tr>\n","    <tr>\n","      <th>부산</th>\n","      <td>350</td>\n","      <td>18</td>\n","    </tr>\n","    <tr>\n","      <th>대구</th>\n","      <td>250</td>\n","      <td>18</td>\n","    </tr>\n","    <tr>\n","      <th>대전</th>\n","      <td>154</td>\n","      <td>19</td>\n","    </tr>\n","    <tr>\n","      <th>광주</th>\n","      <td>150</td>\n","      <td>20</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7cd1effe-bf97-4a0d-947a-d2200ee43332')\"\n","         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   250\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\ub0a0\\uc528\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 17,\n        \"max\": 20,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          18,\n          20,\n          17\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":19}],"source":["## 인덱스를 컬럼중에서 하나로 선택하기\n","\n","df2 = df.set_index('도시')\n","df2"]},{"cell_type":"markdown","id":"772f4b07","metadata":{"id":"772f4b07"},"source":["- 수행 결과를 원본 데이터에 바로 반영하려면 inplace=True를 사용한다"]},{"cell_type":"code","execution_count":20,"id":"dacba78a","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"id":"dacba78a","executionInfo":{"status":"ok","timestamp":1727050809742,"user_tz":-540,"elapsed":6,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"823300f2-494e-4f4b-f3ee-d9e2a5a8893a"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     인구  날씨\n","도시         \n","서울  990  17\n","부산  350  18\n","대구  250  18\n","대전  154  19\n","광주  150  20"],"text/html":["\n","  <div id=\"df-10390ab2-9d6d-4b58-a3a0-6bc6ca565c52\" class=\"colab-df-container\">\n","    <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 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생성된다"]},{"cell_type":"code","execution_count":21,"id":"4eb4b5a3","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"4eb4b5a3","executionInfo":{"status":"ok","timestamp":1727050809742,"user_tz":-540,"elapsed":6,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"7e6fdca9-76c7-4532-9726-e90c4780c7a6"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["   도시   인구  날씨\n","0  서울  990  17\n","1  부산  350  18\n","2  대구  250  18\n","3  대전  154  19\n","4  광주  150  20"],"text/html":["\n","  <div id=\"df-c5d3000b-09dc-4324-81a5-6c7cf84346dc\" class=\"colab-df-container\">\n","    <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 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사용"]},{"cell_type":"code","execution_count":22,"id":"5d2adbc5","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":269},"id":"5d2adbc5","executionInfo":{"status":"ok","timestamp":1727050809742,"user_tz":-540,"elapsed":5,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"d0a6a0e3-dd6b-4eba-95e3-a9a05c4103fd"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["   도시   인구    날씨\n","0  서울  990  17.0\n","1  부산  350  18.0\n","2  대구  250  18.0\n","3  대전  154  19.0\n","4  광주  150  20.0\n","0  인천  290  12.7\n","1  울산  120  15.5"],"text/html":["\n","  <div id=\"df-41f05ba6-c55e-434e-9951-ac20ec5c278f\" class=\"colab-df-container\">\n","    <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 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<td>120</td>\n","      <td>15.5</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-41f05ba6-c55e-434e-9951-ac20ec5c278f')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      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df2])\n","df3"]},{"cell_type":"code","execution_count":23,"id":"f4604a90","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":269},"id":"f4604a90","executionInfo":{"status":"ok","timestamp":1727050810286,"user_tz":-540,"elapsed":549,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"80983bbc-0c50-4f66-e685-46de3f19156e"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["   도시   인구    날씨\n","0  서울  990  17.0\n","1  부산  350  18.0\n","2  대구  250  18.0\n","3  대전  154  19.0\n","4  광주  150  20.0\n","5  인천  290  12.7\n","6  울산  120  15.5"],"text/html":["\n","  <div id=\"df-0cb073d7-c54a-46f1-9391-262beae5f3cf\" class=\"colab-df-container\">\n","    <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","    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<td>울산</td>\n","      <td>120</td>\n","      <td>15.5</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0cb073d7-c54a-46f1-9391-262beae5f3cf')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      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ignore_index=True)\n","df3"]},{"cell_type":"code","execution_count":24,"id":"10f3ac19-5eac-496d-a308-4d93bdbf238b","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"10f3ac19-5eac-496d-a308-4d93bdbf238b","executionInfo":{"status":"ok","timestamp":1727050810287,"user_tz":-540,"elapsed":6,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"1296519a-01d0-430d-ca70-37eaa3c1ff84"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["   도시   인구  날씨  습도\n","0  서울  990  17  55\n","1  부산  350  18  60\n","2  대구  250  18  65\n","3  대전  154  19  70\n","4  광주  150  20  75"],"text/html":["\n","  <div id=\"df-a8c0844e-491d-4268-9318-b7cbb65214c4\" class=\"colab-df-container\">\n","    <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: 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   250\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\ub0a0\\uc528\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 17,\n        \"max\": 20,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          18,\n          20,\n          17\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uc2b5\\ub3c4\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7,\n        \"min\": 55,\n        \"max\": 75,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          60,\n          75,\n          65\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":24}],"source":["# 새로운 열을 데이터프레임으로 생성\n","df2 = pd.DataFrame({'습도': [55, 60, 65, 70, 75]})\n","\n","# 열 방향으로 새로운 열을 추가\n","df3 = pd.concat([df, df2], axis=1)\n","df3"]},{"cell_type":"markdown","id":"8c080bdd","metadata":{"id":"8c080bdd"},"source":["## loc, iloc()\n","- loc(): 특정 인덱스에 해당하는 샘플을 얻는다\n","- iloc(): 정수형 순서 번호로 샘플을 얻는다"]},{"cell_type":"code","execution_count":25,"id":"cc94399b","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":175},"id":"cc94399b","executionInfo":{"status":"ok","timestamp":1727050810287,"user_tz":-540,"elapsed":6,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"6e28ec39-af6d-46d0-e0ab-4ff18f6a6e3a"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     인구  날씨  습도\n","도시             \n","대전  154  19  70\n","부산  350  18  60\n","광주  150  20  75"],"text/html":["\n","  <div id=\"df-74c35ed4-f62f-4cf8-8483-3afe288738ce\" class=\"colab-df-container\">\n","    <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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\"\\ub0a0\\uc528\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 18,\n        \"max\": 20,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          19,\n          18,\n          20\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uc2b5\\ub3c4\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7,\n        \"min\": 60,\n        \"max\": 75,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          70,\n          60,\n          75\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":25}],"source":["# 인덱스를 '도시'컬럼으로 설정한 후 특정 인덱스에 해당하는 샘플 얻기\n","\n","df = df3.copy()\n","\n","df.set_index('도시', inplace=True)\n","df.loc[['대전','부산','광주']]"]},{"cell_type":"code","execution_count":26,"id":"0d6ec196","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":143},"id":"0d6ec196","executionInfo":{"status":"ok","timestamp":1727050810287,"user_tz":-540,"elapsed":6,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"5ccbb1a4-97d8-4434-9182-7edfb732e897"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     인구  날씨  습도\n","도시             \n","대전  154  19  70\n","광주  150  20  75"],"text/html":["\n","  <div id=\"df-86dcf740-dc3b-4a0f-8fda-c2497f2f3bc8\" class=\"colab-df-container\">\n","    <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>인구</th>\n","      <th>날씨</th>\n","      <th>습도</th>\n","    </tr>\n","    <tr>\n","      <th>도시</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>대전</th>\n","      <td>154</td>\n","      <td>19</td>\n","      <td>70</td>\n","    </tr>\n","    <tr>\n","      <th>광주</th>\n","      <td>150</td>\n","      <td>20</td>\n","      <td>75</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-86dcf740-dc3b-4a0f-8fda-c2497f2f3bc8')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path 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'block' : 'none';\n","\n","      async function convertToInteractive(key) {\n","        const element = document.querySelector('#df-86dcf740-dc3b-4a0f-8fda-c2497f2f3bc8');\n","        const dataTable =\n","          await google.colab.kernel.invokeFunction('convertToInteractive',\n","                                                    [key], {});\n","        if (!dataTable) return;\n","\n","        const docLinkHtml = 'Like what you see? Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-dfa5edac-d30a-4fe9-b2de-e776a6f94c93\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-dfa5edac-d30a-4fe9-b2de-e776a6f94c93')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-dfa5edac-d30a-4fe9-b2de-e776a6f94c93 button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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3~5 행 추출"]},{"cell_type":"markdown","id":"b3f8f7de","metadata":{"id":"b3f8f7de"},"source":["## 컬럼 추가\n","- 기존에 없던 컬럼(열) 이름을 지정하면서 값을 주면 새로운 열이 만들어진다"]},{"cell_type":"code","execution_count":27,"id":"4099cc4a","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"id":"4099cc4a","outputId":"536b831a-a8de-43d4-9e07-9aae408bdc02","executionInfo":{"status":"ok","timestamp":1727050810287,"user_tz":-540,"elapsed":5,"user":{"displayName":"전석환","userId":"07131861431613450544"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     인구  날씨  습도  자동차  대도시\n","도시                       \n","서울  990  17  55  300    1\n","부산  350  18  60  140    1\n","대구  250  18  65  120    1\n","대전  154  19  70   70    1\n","광주  150  20  75   50    1"],"text/html":["\n","  <div id=\"df-76c5fef5-a1ca-42c0-8e81-0050a9e96c3d\" class=\"colab-df-container\">\n","    <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>인구</th>\n","      <th>날씨</th>\n","      <th>습도</th>\n","      <th>자동차</th>\n","      <th>대도시</th>\n","    </tr>\n","    <tr>\n","      <th>도시</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>서울</th>\n","      <td>990</td>\n","      <td>17</td>\n","      <td>55</td>\n","      <td>300</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>부산</th>\n","      <td>350</td>\n","      <td>18</td>\n","      <td>60</td>\n","      <td>140</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>대구</th>\n","      <td>250</td>\n","      <td>18</td>\n","      <td>65</td>\n","      <td>120</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>대전</th>\n","      <td>154</td>\n","      <td>19</td>\n","      <td>70</td>\n","      <td>70</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>광주</th>\n","      <td>150</td>\n","      <td>20</td>\n","      <td>75</td>\n","      <td>50</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-76c5fef5-a1ca-42c0-8e81-0050a9e96c3d')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-76c5fef5-a1ca-42c0-8e81-0050a9e96c3d button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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동일한 값을 컬럼에 추가\n","df"]},{"cell_type":"code","execution_count":28,"id":"261e6410","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"id":"261e6410","executionInfo":{"status":"ok","timestamp":1727050810686,"user_tz":-540,"elapsed":404,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"dc53d018-7860-4f1a-b43c-87ef482903fa"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     인구  날씨  습도  자동차  대도시\n","도시                       \n","서울  990  17  55  400    1\n","부산  350  18  60  150    1\n","대구  250  18  65  130    1\n","대전  154  19  70   80    1\n","광주  150  20  75   60    1"],"text/html":["\n","  <div id=\"df-1b1f6198-4b73-462a-a784-9374c6e67bad\" class=\"colab-df-container\">\n","    <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>인구</th>\n","      <th>날씨</th>\n","      <th>습도</th>\n","      <th>자동차</th>\n","      <th>대도시</th>\n","    </tr>\n","    <tr>\n","      <th>도시</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>서울</th>\n","      <td>990</td>\n","      <td>17</td>\n","      <td>55</td>\n","      <td>400</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>부산</th>\n","      <td>350</td>\n","      <td>18</td>\n","      <td>60</td>\n","      <td>150</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>대구</th>\n","      <td>250</td>\n","      <td>18</td>\n","      <td>65</td>\n","      <td>130</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>대전</th>\n","      <td>154</td>\n","      <td>19</td>\n","      <td>70</td>\n","      <td>80</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>광주</th>\n","      <td>150</td>\n","      <td>20</td>\n","      <td>75</td>\n","      <td>60</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1b1f6198-4b73-462a-a784-9374c6e67bad')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-1b1f6198-4b73-462a-a784-9374c6e67bad button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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400,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          150,\n          60,\n          130\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\ub300\\ub3c4\\uc2dc\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":28}],"source":["## 기존 컬럼을 값을 갱신하는 방법\n","\n","new_cars = [400, 150, 130, 80, 60]\n","df['자동차'] = new_cars\n","df"]},{"cell_type":"code","execution_count":29,"id":"2d26d21d","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"id":"2d26d21d","executionInfo":{"status":"ok","timestamp":1727050810686,"user_tz":-540,"elapsed":10,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"9622d223-73fd-4bbd-877c-e7fb9d44c3c0"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     인구  날씨  습도  자동차  대도시    big\n","도시                              \n","서울  990  17  55  400    1   True\n","부산  350  18  60  150    1   True\n","대구  250  18  65  130    1   True\n","대전  154  19  70   80    1  False\n","광주  150  20  75   60    1  False"],"text/html":["\n","  <div id=\"df-702177fd-506c-4d19-b6dc-3fc9d416f871\" class=\"colab-df-container\">\n","    <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","    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400,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          150,\n          60,\n          130\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\ub300\\ub3c4\\uc2dc\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"big\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":29}],"source":["# 특정 조건을 만족하는 행들을 찾는 방법\n","\n","df['big'] = df[\"자동차\"] >= 100\n","df"]},{"cell_type":"code","execution_count":30,"id":"cbc64c0b","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":175},"id":"cbc64c0b","executionInfo":{"status":"ok","timestamp":1727050810686,"user_tz":-540,"elapsed":9,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"d66ca6c5-ca01-47d9-afe3-d414fd49773b"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     인구  날씨  습도  자동차  대도시   big\n","도시                             \n","서울  990  17  55  400    1  True\n","부산  350  18  60  150    1  True\n","대구  250  18  65  130    1  True"],"text/html":["\n","  <div id=\"df-ca80a877-c55a-4d42-9332-808f90993509\" class=\"colab-df-container\">\n","    <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","    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<td>1</td>\n","      <td>True</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ca80a877-c55a-4d42-9332-808f90993509')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      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Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-6b89465a-7a25-473d-b4ce-ebea3c6b25bc\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6b89465a-7a25-473d-b4ce-ebea3c6b25bc')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-6b89465a-7a25-473d-b4ce-ebea3c6b25bc button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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데이터프레임은 인덱스가 True인 항목만 리턴"]},{"cell_type":"markdown","id":"a31e6dea","metadata":{"id":"a31e6dea"},"source":["## 행(샘플) 삭제"]},{"cell_type":"code","execution_count":31,"id":"443439fe","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":175},"id":"443439fe","executionInfo":{"status":"ok","timestamp":1727050810686,"user_tz":-540,"elapsed":9,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"21f9ba5a-2e24-4101-ae17-949f5c8e1af1"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     인구  날씨  습도  자동차  대도시    big\n","도시                              \n","부산  350  18  60  150    1   True\n","대구  250  18  65  130    1   True\n","대전  154  19  70   80    1  False"],"text/html":["\n","  <div id=\"df-cf24708c-1f09-43de-b929-e5fd3097d269\" class=\"colab-df-container\">\n","    <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>인구</th>\n","      <th>날씨</th>\n","      <th>습도</th>\n","      <th>자동차</th>\n","      <th>대도시</th>\n","      <th>big</th>\n","    </tr>\n","    <tr>\n","      <th>도시</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>부산</th>\n","      <td>350</td>\n","      <td>18</td>\n","      <td>60</td>\n","      <td>150</td>\n","      <td>1</td>\n","      <td>True</td>\n","    </tr>\n","    <tr>\n","      <th>대구</th>\n","      <td>250</td>\n","      <td>18</td>\n","      <td>65</td>\n","      <td>130</td>\n","      <td>1</td>\n","      <td>True</td>\n","    </tr>\n","    <tr>\n","      <th>대전</th>\n","      <td>154</td>\n","      <td>19</td>\n","      <td>70</td>\n","      <td>80</td>\n","      <td>1</td>\n","      <td>False</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cf24708c-1f09-43de-b929-e5fd3097d269')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-cf24708c-1f09-43de-b929-e5fd3097d269 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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삭제"]},{"cell_type":"code","execution_count":32,"id":"74585966","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"id":"74585966","executionInfo":{"status":"ok","timestamp":1727050810686,"user_tz":-540,"elapsed":9,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"14f54f19-f569-432a-c508-0d875033a7de"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     인구  날씨  습도  자동차  대도시\n","도시                       \n","서울  990  17  55  400    1\n","부산  350  18  60  150    1\n","대구  250  18  65  130    1\n","대전  154  19  70   80    1\n","광주  150  20  75   60    1"],"text/html":["\n","  <div id=\"df-a77e2c54-4674-45ad-8105-54fe8a9be788\" class=\"colab-df-container\">\n","    <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: 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정렬"]},{"cell_type":"code","execution_count":33,"id":"6405972b","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"id":"6405972b","executionInfo":{"status":"ok","timestamp":1727050810686,"user_tz":-540,"elapsed":8,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"de83d213-5061-4521-a251-119caba2d100"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     인구  날씨  습도  자동차  대도시    big\n","도시                              \n","광주  150  20  75   60    1  False\n","대전  154  19  70   80    1  False\n","대구  250  18  65  130    1   True\n","부산  350  18  60  150    1   True\n","서울  990  17  55  400    1   True"],"text/html":["\n","  <div id=\"df-e7b2910e-f5fb-49e5-bf50-0cff0fe93bca\" class=\"colab-df-container\">\n","    <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","    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Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-fb4ec364-c7fe-4594-9aa6-ab5df0b66057\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-fb4ec364-c7fe-4594-9aa6-ab5df0b66057')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-fb4ec364-c7fe-4594-9aa6-ab5df0b66057 button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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       \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\ub300\\ub3c4\\uc2dc\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"big\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":33}],"source":["## 특정 컬럼을 기준으로 순서 정렬하기\n","\n","df.sort_values(['인구'])"]},{"cell_type":"code","execution_count":34,"id":"26f10133","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"id":"26f10133","executionInfo":{"status":"ok","timestamp":1727050810686,"user_tz":-540,"elapsed":8,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"6a2d50d3-6e9a-4771-dcc6-d7cbe992d50d"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     인구  날씨  습도  자동차  대도시    big\n","도시                              \n","서울  990  17  55  400    1   True\n","부산  350  18  60  150    1   True\n","대구  250  18  65  130    1   True\n","대전  154  19  70   80    1  False\n","광주  150  20  75   60    1  False"],"text/html":["\n","  <div id=\"df-89345eb0-ffd0-443f-b7c0-62b5ac62ba38\" class=\"colab-df-container\">\n","    <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: 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<td>250</td>\n","      <td>18</td>\n","      <td>65</td>\n","      <td>130</td>\n","      <td>1</td>\n","      <td>True</td>\n","    </tr>\n","    <tr>\n","      <th>대전</th>\n","      <td>154</td>\n","      <td>19</td>\n","      <td>70</td>\n","      <td>80</td>\n","      <td>1</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>광주</th>\n","      <td>150</td>\n","      <td>20</td>\n","      <td>75</td>\n","      <td>60</td>\n","      <td>1</td>\n","      <td>False</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-89345eb0-ffd0-443f-b7c0-62b5ac62ba38')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path 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       \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\ub300\\ub3c4\\uc2dc\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"big\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":34}],"source":["## 내림차순으로 순서 정렬하기\n","\n","df.sort_values(['인구'], ascending=False)"]},{"cell_type":"markdown","id":"0e6b5ca2","metadata":{"id":"0e6b5ca2"},"source":["# Series\n","\n","- 데이터프레임에서 한 컬럼을 취하면 시리즈가 된다\n","- 시리즈는 리스트처럼 1차원 데이터인데, 인덱스가 붙어 있다"]},{"cell_type":"code","execution_count":35,"id":"84e77291","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":290},"id":"84e77291","executionInfo":{"status":"ok","timestamp":1727050811076,"user_tz":-540,"elapsed":398,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"55f92916-da95-4b85-a0ba-fe4925340e52"},"outputs":[{"output_type":"stream","name":"stdout","text":["<class 'pandas.core.series.Series'>\n"]},{"output_type":"execute_result","data":{"text/plain":["도시\n","서울    400\n","부산    150\n","대구    130\n","대전     80\n","광주     60\n","Name: 자동차, dtype: int64"],"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>자동차</th>\n","    </tr>\n","    <tr>\n","      <th>도시</th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>서울</th>\n","      <td>400</td>\n","    </tr>\n","    <tr>\n","      <th>부산</th>\n","      <td>150</td>\n","    </tr>\n","    <tr>\n","      <th>대구</th>\n","      <td>130</td>\n","    </tr>\n","    <tr>\n","      <th>대전</th>\n","      <td>80</td>\n","    </tr>\n","    <tr>\n","      <th>광주</th>\n","      <td>60</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div><br><label><b>dtype:</b> int64</label>"]},"metadata":{},"execution_count":35}],"source":["## 데이터프레임에서 시리즈 추출하기\n","\n","s = df['자동차']\n","print(type(s))\n","s"]},{"cell_type":"markdown","id":"146a9bec","metadata":{"id":"146a9bec"},"source":["## 시리즈 다루기\n","- 시리즈(하 컬럼 데이터)의 기초 통계치 보기"]},{"cell_type":"code","execution_count":36,"id":"f8d44899","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"f8d44899","executionInfo":{"status":"ok","timestamp":1727050811076,"user_tz":-540,"elapsed":7,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"a9f34d9e-54fd-4939-e333-2ec0c5c4f968"},"outputs":[{"output_type":"stream","name":"stdout","text":["[400 150 130  80  60]\n","5\n","400\n","60\n","164.0\n","자동차\n","400    1\n","150    1\n","130    1\n","80     1\n","60     1\n","Name: count, dtype: int64\n"]}],"source":["## 시리즈 항목의 종류와 빈도수 세기\n","\n","print(s.unique())       # 항목의 종류\n","print(s.nunique())      # 항목의 총수\n","print(s.max())       # 최대치\n","print(s.min())       # 최소치\n","print(s.mean())       # 평균\n","print(s.value_counts()) # 빈도수"]},{"cell_type":"markdown","id":"03926ba9","metadata":{"id":"03926ba9"},"source":["# 데이터프레임 저장\n","- to_csv(): csv 파일로 저장\n","- to_excel(): 액셀 파일로 저장\n","- 한글이 깨지는 경우 encoding='utf-8', 'cp949','euc-kr' 등의 옵션 사용\n","- [한글보기 블로그](https://teddylee777.github.io/pandas/%EA%B3%B5%EA%B3%B5%EB%8D%B0%EC%9D%B4%ED%84%B0-%ED%95%9C%EA%B8%80%EA%B9%A8%EC%A7%90%ED%98%84%EC%83%81-%ED%95%B4%EA%B2%B0%EB%B0%A9%EB%B2%95)"]},{"cell_type":"code","execution_count":37,"id":"61e82d39","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"61e82d39","executionInfo":{"status":"ok","timestamp":1727050811076,"user_tz":-540,"elapsed":6,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"426c9e42-52ed-49b0-e8e5-1eca11a70fb8"},"outputs":[{"output_type":"stream","name":"stdout","text":["도시,인구,날씨,습도,자동차,대도시,big\n","서울,990,17,55,400,1,True\n","부산,350,18,60,150,1,True\n","대구,250,18,65,130,1,True\n","대전,154,19,70,80,1,False\n","광주,150,20,75,60,1,False\n","\n"]}],"source":["## 데이터프레임을 csv 파일, 액셀로 저장하기\n","\n","df.to_csv('cities.csv')\n","df.to_excel('cities.xlsx')\n","\n","# 파일을 읽고 화면에 출력하기\n","with open('cities.csv', encoding='utf-8') as f:\n","    print(f.read())"]},{"cell_type":"code","execution_count":38,"id":"bc9b1461","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"bc9b1461","executionInfo":{"status":"ok","timestamp":1727050811076,"user_tz":-540,"elapsed":5,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"da12f00a-1152-4803-af93-24f1d7528db8"},"outputs":[{"output_type":"stream","name":"stdout","text":["인구,날씨,습도,자동차,대도시,big\n","990,17,55,400,1,True\n","350,18,60,150,1,True\n","250,18,65,130,1,True\n","154,19,70,80,1,False\n","150,20,75,60,1,False\n","\n"]}],"source":["## 데이터프레임 저장시 인덱스 제거하기\n","\n","df.to_csv('cities_2.csv', index=False)\n","with open('cities_2.csv', encoding='utf-8') as f:\n","    print(f.read())"]},{"cell_type":"markdown","id":"6fa6667a","metadata":{"id":"6fa6667a"},"source":["## 파일을 읽어 데이터프레임 만들기\n","- read_csv(): csv 파일을 데이터프레임으로 읽기\n","- read_excel(): 액셀, xlsx 파일을 데이터프레임으로 읽기"]},{"cell_type":"code","execution_count":39,"id":"7512ca4f","metadata":{"scrolled":true,"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"7512ca4f","executionInfo":{"status":"ok","timestamp":1727050811076,"user_tz":-540,"elapsed":5,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"fa1df4b1-318b-4362-8345-f527640a1972"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["   도시   인구  날씨  습도  자동차  대도시    big\n","0  서울  990  17  55  400    1   True\n","1  부산  350  18  60  150    1   True\n","2  대구  250  18  65  130    1   True\n","3  대전  154  19  70   80    1  False\n","4  광주  150  20  75   60    1  False"],"text/html":["\n","  <div id=\"df-e2686c92-72ff-4251-a3d5-c4473f19f608\" class=\"colab-df-container\">\n","    <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 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\"max\": 400,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          150,\n          60,\n          130\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\ub300\\ub3c4\\uc2dc\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"big\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":39}],"source":["## csv 파일을 읽어서 데이터프레임 만들기\n","\n","df2 = pd.read_csv('cities.csv')\n","df2"]},{"cell_type":"code","execution_count":40,"id":"eb7a41da","metadata":{"scrolled":true,"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"eb7a41da","executionInfo":{"status":"ok","timestamp":1727050811595,"user_tz":-540,"elapsed":523,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"458ced70-9333-4655-b5dd-a0f0a9c4e5e1"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["   도시   인구  날씨  습도  자동차  대도시    big\n","0  서울  990  17  55  400    1   True\n","1  부산  350  18  60  150    1   True\n","2  대구  250  18  65  130    1   True\n","3  대전  154  19  70   80    1  False\n","4  광주  150  20  75   60    1  False"],"text/html":["\n","  <div id=\"df-348d6f6f-2742-432a-9510-165ff00f782d\" class=\"colab-df-container\">\n","    <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: 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400,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          150,\n          60,\n          130\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\ub300\\ub3c4\\uc2dc\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"big\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":40}],"source":["# 액셀 읽기\n","\n","df = pd.read_excel('cities.xlsx')\n","df"]},{"cell_type":"markdown","id":"ad80b7b4","metadata":{"id":"ad80b7b4"},"source":["# merge\n","- 특정 열(컬럼)을 기준으로 두 데이터프레임 합치기\n","- (참고) 같은 인덱스를 기준으로 합칠때는 join()을 사용한다"]},{"cell_type":"markdown","id":"8e33d97d","metadata":{"id":"8e33d97d"},"source":["## 참조 테이블과 합치기\n","- merge 사용하여 상품별 매출과 가격표를 합치는 예"]},{"cell_type":"code","execution_count":41,"id":"9bc10bc6","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"id":"9bc10bc6","executionInfo":{"status":"ok","timestamp":1727050811596,"user_tz":-540,"elapsed":524,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"a53644d0-3278-4577-c58f-517b615d3ed8"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["   item logistic  2020  2021\n","0  eCar     ship    39    45\n","1  eCar      air    17    22\n","2    TV     ship    64    84\n","3    TV      air    33    57\n","4  Refr     ship    65    95\n","5  Refr      air    23    30"],"text/html":["\n","  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95, 30]}\n","df_export = pd.DataFrame(export)\n","df_export"]},{"cell_type":"code","execution_count":42,"id":"685dcc2a","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":143},"id":"685dcc2a","executionInfo":{"status":"ok","timestamp":1727050811596,"user_tz":-540,"elapsed":4,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"cc569cdc-de16-46f6-8744-b9fe06813974"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["   item  price\n","0  Refr    200\n","1  eCar   1000\n","2    TV    100"],"text/html":["\n","  <div id=\"df-f04effa1-56e1-4ff2-90cc-6fb391bbf9a1\" class=\"colab-df-container\">\n","    <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","  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\"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":42}],"source":["## 제품(item)별 가격표 테이블이 따로 제공되는 경우\n","\n","price_list = {'item': [ 'Refr', 'eCar', 'TV'],\n","        'price': [200, 1000, 100]}\n","df_price = pd.DataFrame(price_list)\n","df_price"]},{"cell_type":"code","execution_count":43,"id":"bc34cfb7","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"id":"bc34cfb7","executionInfo":{"status":"ok","timestamp":1727050812142,"user_tz":-540,"elapsed":550,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"60b5589b-9099-4394-ab4f-18e4d5700a03"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["   item logistic  2020  2021  price\n","0  eCar     ship    39    45   1000\n","1  eCar      air    17    22   1000\n","2    TV     ship    64    84    100\n","3    TV      air    33    57    100\n","4  Refr     ship    65    95    200\n","5  Refr      air    23    30    200"],"text/html":["\n","  <div id=\"df-6fef1ca3-9c00-4bca-adee-45ea81cd01bb\" class=\"colab-df-container\">\n","    <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>item</th>\n","      <th>logistic</th>\n","      <th>2020</th>\n","      <th>2021</th>\n","      <th>price</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>eCar</td>\n","      <td>ship</td>\n","      <td>39</td>\n","      <td>45</td>\n","      <td>1000</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>eCar</td>\n","      <td>air</td>\n","      <td>17</td>\n","      <td>22</td>\n","      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Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-90df7832-71f7-467d-9e5f-556b86c9dd68\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-90df7832-71f7-467d-9e5f-556b86c9dd68')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-90df7832-71f7-467d-9e5f-556b86c9dd68 button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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DataFrameGroupBy\n","print(g.ngroups)  # 3\n","print(g.groups)   # {'Refr': [4, 5], 'TV': [2, 3], 'eCar': [0, 1]}\n","print(g.size())   # 각 그룹 데이터프레임의 크기를 알려준다"]},{"cell_type":"code","execution_count":45,"id":"aebf8d6a","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":112},"id":"aebf8d6a","executionInfo":{"status":"ok","timestamp":1727050812142,"user_tz":-540,"elapsed":5,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"bf506c9d-d161-481d-89f5-c802f9a5ef2f"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["  item logistic  2020  2021  price\n","2   TV     ship    64    84    100\n","3   TV      air    33    57    100"],"text/html":["\n","  <div id=\"df-7720a81c-7457-4f76-9959-22d8b347a679\" class=\"colab-df-container\">\n","    <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>item</th>\n","      <th>logistic</th>\n","      <th>2020</th>\n","      <th>2021</th>\n","      <th>price</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2</th>\n","      <td>TV</td>\n","      <td>ship</td>\n","      <td>64</td>\n","      <td>84</td>\n","      <td>100</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>TV</td>\n","      <td>air</td>\n","      <td>33</td>\n","      <td>57</td>\n","      <td>100</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7720a81c-7457-4f76-9959-22d8b347a679')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-7720a81c-7457-4f76-9959-22d8b347a679 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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33\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"2021\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 19,\n        \"min\": 57,\n        \"max\": 84,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          57\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"price\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 100,\n        \"max\": 100,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          100\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":45}],"source":["## g로부터 item이 TV인 세부그룹 데이터프레임 얻기\n","# get_group()를 사용한다\n","\n","g.get_group('TV')"]},{"cell_type":"code","execution_count":46,"id":"b4212e86","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":112},"id":"b4212e86","executionInfo":{"status":"ok","timestamp":1727050812142,"user_tz":-540,"elapsed":4,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"b5c20179-d006-40c8-c352-89f0a87517b9"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["   item logistic  2020  2021  price\n","0  eCar     ship    39    45   1000\n","1  eCar      air    17    22   1000"],"text/html":["\n","  <div id=\"df-a7824de8-8869-440e-9e2e-4d2fb73ba205\" class=\"colab-df-container\">\n","    <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>item</th>\n","      <th>logistic</th>\n","      <th>2020</th>\n","      <th>2021</th>\n","      <th>price</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>eCar</td>\n","      <td>ship</td>\n","      <td>39</td>\n","      <td>45</td>\n","      <td>1000</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>eCar</td>\n","      <td>air</td>\n","      <td>17</td>\n","      <td>22</td>\n","      <td>1000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a7824de8-8869-440e-9e2e-4d2fb73ba205')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg 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Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-c28074fe-f371-4658-8668-614301de228b\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c28074fe-f371-4658-8668-614301de228b')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-c28074fe-f371-4658-8668-614301de228b button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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17\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"2021\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 16,\n        \"min\": 22,\n        \"max\": 45,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          22\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"price\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1000,\n        \"max\": 1000,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1000\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":46}],"source":["g.get_group('eCar')"]},{"cell_type":"code","execution_count":47,"id":"38422fb7","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"38422fb7","executionInfo":{"status":"ok","timestamp":1727050812142,"user_tz":-540,"elapsed":4,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"ae64cc53-628a-486e-bdfe-8ee362ee6070"},"outputs":[{"output_type":"stream","name":"stdout","text":["Refr\n","   item logistic  2020  2021  price\n","4  Refr     ship    65    95    200\n","5  Refr      air    23    30    200\n","62.5\n","------------------------------------\n","TV\n","  item logistic  2020  2021  price\n","2   TV     ship    64    84    100\n","3   TV      air    33    57    100\n","70.5\n","------------------------------------\n","eCar\n","   item logistic  2020  2021  price\n","0  eCar     ship    39    45   1000\n","1  eCar      air    17    22   1000\n","33.5\n","------------------------------------\n"]}],"source":["## 그룹바이 객체 g의 레이블(item)과 해당 그룹을 얻는 방법\n","# 아래는 각 그룹의 2021년도 평균치를 출력했다\n","\n","for item, group in g:\n","    print(item)\n","    print(group)\n","    print(group['2021'].mean())\n","    print('------------------------------------')"]},{"cell_type":"code","execution_count":48,"id":"f3e960ad","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":175},"id":"f3e960ad","executionInfo":{"status":"ok","timestamp":1727050812142,"user_tz":-540,"elapsed":3,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"fa83f898-a3ce-4c34-d771-fa666756f825"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["      2020  2021\n","item            \n","Refr    88   125\n","TV      97   141\n","eCar    56    67"],"text/html":["\n","  <div id=\"df-a23a6fe0-983f-4647-82cf-b704d94d1c3b\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type 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Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-539519dc-7433-401f-8426-c3eb67f0c87a\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-539519dc-7433-401f-8426-c3eb67f0c87a')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-539519dc-7433-401f-8426-c3eb67f0c87a button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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\"number\",\n        \"std\": 38,\n        \"min\": 67,\n        \"max\": 141,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          125,\n          141,\n          67\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":48}],"source":["# 그룹바이 모든 항목에 대한 연산수행\n","\n","g[['2020','2021']].sum()"]},{"cell_type":"code","execution_count":49,"id":"89b98860","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"89b98860","executionInfo":{"status":"ok","timestamp":1727050812142,"user_tz":-540,"elapsed":3,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"5ceeb6e6-1008-4afc-d4fe-76ad0f620ff3"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     2020                2021                \n","      max sum size  mean  max  sum size  mean\n","item                                         \n","Refr   65  88    2  44.0   95  125    2  62.5\n","TV     64  97    2  48.5   84  141    2  70.5\n","eCar   39  56    2  28.0   45   67    2  33.5"],"text/html":["\n","  <div id=\"df-2d7e9de4-f2b5-4d18-94d5-b2f26bf0a24c\" class=\"colab-df-container\">\n","    <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 tr th {\n","        text-align: left;\n","    }\n","\n","    .dataframe thead tr:last-of-type th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr>\n","      <th></th>\n","      <th colspan=\"4\" halign=\"left\">2020</th>\n","      <th colspan=\"4\" halign=\"left\">2021</th>\n","    </tr>\n","    <tr>\n","      <th></th>\n","      <th>max</th>\n","      <th>sum</th>\n","      <th>size</th>\n","      <th>mean</th>\n","      <th>max</th>\n","      <th>sum</th>\n","      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Visit the ' +\n","          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","          + ' to learn more about interactive tables.';\n","        element.innerHTML = '';\n","        dataTable['output_type'] = 'display_data';\n","        await google.colab.output.renderOutput(dataTable, element);\n","        const docLink = document.createElement('div');\n","        docLink.innerHTML = docLinkHtml;\n","        element.appendChild(docLink);\n","      }\n","    </script>\n","  </div>\n","\n","\n","<div id=\"df-7179994d-79d5-4e46-a50c-3be234629082\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7179994d-79d5-4e46-a50c-3be234629082')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-7179994d-79d5-4e46-a50c-3be234629082 button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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\"column\": [\n        \"2020\",\n        \"sum\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 21,\n        \"min\": 56,\n        \"max\": 97,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          88,\n          97,\n          56\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"2020\",\n        \"size\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 2,\n        \"max\": 2,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"2020\",\n        \"mean\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 10.774197572595991,\n        \"min\": 28.0,\n        \"max\": 48.5,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          44.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"2021\",\n        \"max\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 26,\n        \"min\": 45,\n        \"max\": 95,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          95\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"2021\",\n        \"sum\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 38,\n        \"min\": 67,\n        \"max\": 141,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          125\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"2021\",\n        \"size\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 2,\n        \"max\": 2,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"2021\",\n        \"mean\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 19.467922333931785,\n        \"min\": 33.5,\n        \"max\": 70.5,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          62.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":49}],"source":["## 그룹바이 모든 항목에 대여 여러가지 함수를 적용하는 경우\n","\n","g[['2020','2021']].agg(['max','sum', 'size','mean'])"]},{"cell_type":"code","execution_count":50,"id":"eaa47f0a","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"eaa47f0a","executionInfo":{"status":"ok","timestamp":1727050812622,"user_tz":-540,"elapsed":6,"user":{"displayName":"전석환","userId":"07131861431613450544"}},"outputId":"d2f948ec-9c58-4c1b-c659-036c7b74fb03"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     2020                     2021                    \n","      max  mean find_big_sale  max  mean find_big_sale\n","item                                                  \n","Refr   65  44.0          True   95  62.5          True\n","TV     64  48.5          True   84  70.5          True\n","eCar   39  28.0         False   45  33.5         False"],"text/html":["\n","  <div id=\"df-c05b207c-5580-4527-ac0c-09c734ef6f32\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: 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<td>True</td>\n","      <td>95</td>\n","      <td>62.5</td>\n","      <td>True</td>\n","    </tr>\n","    <tr>\n","      <th>TV</th>\n","      <td>64</td>\n","      <td>48.5</td>\n","      <td>True</td>\n","      <td>84</td>\n","      <td>70.5</td>\n","      <td>True</td>\n","    </tr>\n","    <tr>\n","      <th>eCar</th>\n","      <td>39</td>\n","      <td>28.0</td>\n","      <td>False</td>\n","      <td>45</td>\n","      <td>33.5</td>\n","      <td>False</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c05b207c-5580-4527-ac0c-09c734ef6f32')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path 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