{"id":937617,"date":"2024-12-26T19:55:31","date_gmt":"2024-12-26T11:55:31","guid":{"rendered":""},"modified":"2024-12-26T19:55:33","modified_gmt":"2024-12-26T11:55:33","slug":"python%e5%a6%82%e4%bd%95%e8%b0%83%e6%95%b0%e6%8d%ae","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/937617.html","title":{"rendered":"python\u5982\u4f55\u8c03\u6570\u636e"},"content":{"rendered":"

\"python\u5982\u4f55\u8c03\u6570\u636e\"<\/p>\n

Python\u8c03\u6570\u636e\u7684\u65b9\u6cd5\u4e3b\u8981\u5305\u62ec\uff1a\u4f7f\u7528Pandas\u5e93\u8fdb\u884c\u6570\u636e\u5904\u7406\u3001\u5229\u7528NumPy\u8fdb\u884c\u6570\u503c\u8ba1\u7b97\u3001\u4f7f\u7528Matplotlib\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u3001\u7ed3\u5408SQLAlchemy\u8fde\u63a5\u6570\u636e\u5e93\u3002<\/strong>\u5176\u4e2d\uff0cPandas\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u6570\u636e\u5904\u7406\u5e93\uff0c\u63d0\u4f9b\u4e86\u6570\u636e\u6e05\u6d17\u3001\u5408\u5e76\u3001\u5206\u7ec4\u3001\u91cd\u5851\u7b49\u529f\u80fd\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u5c06\u8be6\u7ec6\u63cf\u8ff0\u5982\u4f55\u5229\u7528Pandas\u5e93\u8c03\u53d6\u548c\u5904\u7406\u6570\u636e\u3002<\/p>\n<\/p>\n

Pandas\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u548c\u6570\u636e\u5904\u7406\u5e93\uff0c\u9002\u7528\u4e8e\u5904\u7406\u7ed3\u6784\u5316\u6570\u636e\u3002\u901a\u8fc7DataFrame\u548cSeries\u8fd9\u4e24\u79cd\u6570\u636e\u7ed3\u6784\uff0cPandas\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u64cd\u4f5c\u80fd\u529b\u3002DataFrame\u7c7b\u4f3c\u4e8eExcel\u4e2d\u7684\u7535\u5b50\u8868\u683c\uff0c\u5177\u6709\u884c\u5217\u6807\u7b7e\uff0c\u800cSeries\u5219\u662f\u4e00\u7ef4\u6570\u636e\u7ed3\u6784\uff0c\u7c7b\u4f3c\u4e8e\u5217\u8868\u6216\u6570\u7ec4\u3002<\/p>\n<\/p>\n

\n

\u4e00\u3001PANDAS\u5e93\u7684\u6570\u636e\u64cd\u4f5c<\/h3>\n<\/p>\n

1.1\u3001\u8bfb\u53d6\u6570\u636e<\/h4>\n<\/p>\n

Pandas\u652f\u6301\u4ece\u591a\u79cd\u6570\u636e\u6e90\u8bfb\u53d6\u6570\u636e\uff0c\u5982CSV\u6587\u4ef6\u3001Excel\u6587\u4ef6\u3001SQL\u6570\u636e\u5e93\u7b49\u3002\u6700\u5e38\u7528\u7684\u8bfb\u53d6\u65b9\u6cd5\u662fpd.read_csv()<\/code>\uff0c\u7528\u4e8e\u4eceCSV\u6587\u4ef6\u4e2d\u8bfb\u53d6\u6570\u636e\u3002<\/p>\n<\/p>\n

import pandas as pd<\/p>\n
\u4eceCSV\u6587\u4ef6\u8bfb\u53d6\u6570\u636e<\/strong><\/h2>\n
data = pd.read_csv('data.csv')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u9664\u4e86CSV\u6587\u4ef6\uff0cPandas\u8fd8\u63d0\u4f9b\u4e86pd.read_excel()<\/code>\u3001pd.read_sql()<\/code>\u7b49\u65b9\u6cd5\uff0c\u5206\u522b\u7528\u4e8e\u8bfb\u53d6Excel\u6587\u4ef6\u548cSQL\u6570\u636e\u5e93\u4e2d\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
1.2\u3001\u6570\u636e\u6e05\u6d17<\/h4>\n<\/p>\n
\u6570\u636e\u6e05\u6d17\u662f\u6570\u636e\u5206\u6790\u4e2d\u7684\u91cd\u8981\u6b65\u9aa4\uff0cPandas\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u65b9\u6cd5\u6765\u5904\u7406\u7f3a\u5931\u6570\u636e\u3001\u91cd\u590d\u6570\u636e\u7b49\u95ee\u9898\u3002<\/p>\n<\/p>\n
    \n
  • \u5904\u7406\u7f3a\u5931\u6570\u636e<\/strong>\uff1a\u4f7f\u7528dropna()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c\u6216\u5217\uff0c\u4f7f\u7528fillna()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u7528\u6307\u5b9a\u503c\u66ff\u6362\u7f3a\u5931\u503c\u3002<\/li>\n<\/ul>\n
    # \u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c<\/p>\n
    data_cleaned = data.dropna()<\/p>\n
    \u75280\u66ff\u6362\u7f3a\u5931\u503c<\/strong><\/h2>\n
    data_filled = data.fillna(0)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
      \n
    • \u53bb\u91cd<\/strong>\uff1a\u4f7f\u7528drop_duplicates()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u5220\u9664\u91cd\u590d\u7684\u884c\u3002<\/li>\n<\/ul>\n
      # \u5220\u9664\u91cd\u590d\u884c<\/p>\n
      data_unique = data.drop_duplicates()<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      1.3\u3001\u6570\u636e\u9009\u62e9\u4e0e\u8fc7\u6ee4<\/h4>\n<\/p>\n
      Pandas\u63d0\u4f9b\u4e86\u7075\u6d3b\u7684\u6570\u636e\u9009\u62e9\u4e0e\u8fc7\u6ee4\u529f\u80fd\uff0c\u5141\u8bb8\u7528\u6237\u6839\u636e\u6761\u4ef6\u9009\u62e9\u7279\u5b9a\u7684\u884c\u6216\u5217\u3002<\/p>\n<\/p>\n
        \n
      • \u9009\u62e9\u5217<\/strong>\uff1a\u53ef\u4ee5\u901a\u8fc7\u5217\u540d\u76f4\u63a5\u9009\u62e9\u3002<\/li>\n<\/ul>\n
        # \u9009\u62e9\u5355\u5217<\/p>\n
        column_data = data['column_name']<\/p>\n
        \u9009\u62e9\u591a\u5217<\/strong><\/h2>\n
        subset_data = data[['column1', 'column2']]<\/p>\n
        <\/code><\/pre>\n<\/p>\n
          \n
        • \u6761\u4ef6\u8fc7\u6ee4<\/strong>\uff1a\u53ef\u4ee5\u6839\u636e\u6761\u4ef6\u8fc7\u6ee4\u6570\u636e\u3002<\/li>\n<\/ul>\n
          # \u9009\u62e9\u6ee1\u8db3\u6761\u4ef6\u7684\u884c<\/p>\n
          filtered_data = data[data['column_name'] > threshold]<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          1.4\u3001\u6570\u636e\u5206\u7ec4\u4e0e\u805a\u5408<\/h4>\n<\/p>\n
          \u6570\u636e\u5206\u7ec4\u4e0e\u805a\u5408\u662f\u6570\u636e\u5206\u6790\u4e2d\u7684\u5e38\u89c1\u64cd\u4f5c\uff0cPandas\u63d0\u4f9b\u4e86groupby()<\/code>\u65b9\u6cd5\u7528\u4e8e\u5206\u7ec4\uff0cagg()<\/code>\u65b9\u6cd5\u7528\u4e8e\u805a\u5408\u3002<\/p>\n<\/p>\n
          # \u6309\u67d0\u5217\u5206\u7ec4\u5e76\u8ba1\u7b97\u5747\u503c<\/p>\n
          grouped_data = data.groupby('group_column').mean()<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u4e8c\u3001NUMPY\u5e93\u7684\u6570\u503c\u8ba1\u7b97<\/h3>\n<\/p>\n
          2.1\u3001\u6570\u7ec4\u64cd\u4f5c<\/h4>\n<\/p>\n
          NumPy\u662fPython\u4e2d\u8fdb\u884c\u6570\u503c\u8ba1\u7b97\u7684\u57fa\u7840\u5e93\uff0c\u63d0\u4f9b\u4e86\u591a\u7ef4\u6570\u7ec4\u5bf9\u8c61\u548c\u4e30\u5bcc\u7684\u6570\u5b66\u51fd\u6570\u3002<\/p>\n<\/p>\n
            \n
          • \u521b\u5efa\u6570\u7ec4<\/strong>\uff1a\u4f7f\u7528np.array()<\/code>\u53ef\u4ee5\u521b\u5efa\u6570\u7ec4\u3002<\/li>\n<\/ul>\n
            import numpy as np<\/p>\n
            \u521b\u5efa\u6570\u7ec4<\/strong><\/h2>\n
            array = np.array([1, 2, 3, 4, 5])<\/p>\n
            <\/code><\/pre>\n<\/p>\n
              \n
            • \u6570\u7ec4\u8fd0\u7b97<\/strong>\uff1aNumPy\u652f\u6301\u6570\u7ec4\u7684\u7b97\u672f\u8fd0\u7b97\u3002<\/li>\n<\/ul>\n
              # \u6570\u7ec4\u52a0\u6cd5<\/p>\n
              result = array + 10<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              2.2\u3001\u6570\u7ec4\u64cd\u4f5c\u4e0e\u53d8\u5f62<\/h4>\n<\/p>\n
              NumPy\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u6765\u53d8\u5f62\u548c\u64cd\u4f5c\u6570\u7ec4\u3002<\/p>\n<\/p>\n
                \n
              • \u6570\u7ec4\u53d8\u5f62<\/strong>\uff1a\u4f7f\u7528reshape()<\/code>\u53ef\u4ee5\u66f4\u6539\u6570\u7ec4\u5f62\u72b6\u3002<\/li>\n<\/ul>\n
                # \u53d8\u5f62\u4e3a2x3\u6570\u7ec4<\/p>\n
                reshaped_array = array.reshape(2, 3)<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                  \n
                • \u6570\u7ec4\u5408\u5e76<\/strong>\uff1a\u4f7f\u7528concatenate()<\/code>\u53ef\u4ee5\u5408\u5e76\u6570\u7ec4\u3002<\/li>\n<\/ul>\n
                  # \u6570\u7ec4\u5408\u5e76<\/p>\n
                  concatenated_array = np.concatenate((array1, array2))<\/p>\n
                  <\/code><\/pre>\n<\/p>\n
                  \u4e09\u3001MATPLOTLIB\u5e93\u7684\u6570\u636e\u53ef\u89c6\u5316<\/h3>\n<\/p>\n
                  3.1\u3001\u7ed8\u5236\u57fa\u672c\u56fe\u5f62<\/h4>\n<\/p>\n
                  Matplotlib\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u6570\u636e\u53ef\u89c6\u5316\u5e93\uff0c\u652f\u6301\u7ed8\u5236\u591a\u79cd\u7c7b\u578b\u7684\u56fe\u5f62\u3002<\/p>\n<\/p>\n
                    \n
                  • \u6298\u7ebf\u56fe<\/strong>\uff1a\u4f7f\u7528plt.plot()<\/code>\u53ef\u4ee5\u7ed8\u5236\u6298\u7ebf\u56fe\u3002<\/li>\n<\/ul>\n
                    import matplotlib.pyplot as plt<\/p>\n
                    \u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\n
                    plt.plot(array)<\/p>\n
                    plt.show()<\/p>\n
                    <\/code><\/pre>\n<\/p>\n
                      \n
                    • \u67f1\u72b6\u56fe<\/strong>\uff1a\u4f7f\u7528plt.bar()<\/code>\u53ef\u4ee5\u7ed8\u5236\u67f1\u72b6\u56fe\u3002<\/li>\n<\/ul>\n
                      # \u7ed8\u5236\u67f1\u72b6\u56fe<\/p>\n
                      plt.bar(['A', 'B', 'C'], [5, 7, 9])<\/p>\n
                      plt.show()<\/p>\n
                      <\/code><\/pre>\n<\/p>\n
                      3.2\u3001\u56fe\u5f62\u5b9a\u5236<\/h4>\n<\/p>\n
                      Matplotlib\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u5f62\u5b9a\u5236\u9009\u9879\uff0c\u5982\u8bbe\u7f6e\u6807\u9898\u3001\u6807\u7b7e\u3001\u989c\u8272\u7b49\u3002<\/p>\n<\/p>\n
                      # \u8bbe\u7f6e\u6807\u9898\u548c\u6807\u7b7e<\/p>\n
                      plt.title('Sample Plot')<\/p>\n
                      plt.xlabel('X-axis')<\/p>\n
                      plt.ylabel('Y-axis')<\/p>\n
                      \u7ed8\u5236\u56fe\u5f62<\/strong><\/h2>\n
                      plt.plot(array)<\/p>\n
                      plt.show()<\/p>\n
                      <\/code><\/pre>\n<\/p>\n
                      \u56db\u3001\u5229\u7528SQLALCHEMY\u8fde\u63a5\u6570\u636e\u5e93<\/h3>\n<\/p>\n
                      4.1\u3001\u6570\u636e\u5e93\u8fde\u63a5<\/h4>\n<\/p>\n
                      SQLAlchemy\u662fPython\u4e2d\u7684ORM\u5e93\uff0c\u652f\u6301\u8fde\u63a5\u591a\u79cd\u6570\u636e\u5e93\uff0c\u5e76\u4f7f\u7528Python\u5bf9\u8c61\u64cd\u4f5c\u6570\u636e\u5e93\u3002<\/p>\n<\/p>\n
                        \n
                      • \u8fde\u63a5\u6570\u636e\u5e93<\/strong>\uff1a\u4f7f\u7528create_engine()<\/code>\u53ef\u4ee5\u521b\u5efa\u6570\u636e\u5e93\u8fde\u63a5\u3002<\/li>\n<\/ul>\n
                        from sqlalchemy import create_engine<\/p>\n
                        \u521b\u5efa\u6570\u636e\u5e93\u8fde\u63a5<\/strong><\/h2>\n
                        engine = create_engine('sqlite:\/\/\/database.db')<\/p>\n
                        <\/code><\/pre>\n<\/p>\n
                        4.2\u3001\u6267\u884cSQL\u67e5\u8be2<\/h4>\n<\/p>\n
                        SQLAlchemy\u5141\u8bb8\u7528\u6237\u6267\u884cSQL\u67e5\u8be2\uff0c\u5e76\u5c06\u7ed3\u679c\u52a0\u8f7d\u5230Pandas DataFrame\u4e2d\u3002<\/p>\n<\/p>\n
                        # \u6267\u884cSQL\u67e5\u8be2<\/p>\n
                        query = 'SELECT * FROM table_name'<\/p>\n
                        data = pd.read_sql(query, engine)<\/p>\n
                        <\/code><\/pre>\n<\/p>\n
                        \u4e94\u3001\u7efc\u5408\u5e94\u7528<\/h3>\n<\/p>\n
                        \u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u901a\u5e38\u9700\u8981\u7ed3\u5408\u4f7f\u7528Pandas\u3001NumPy\u3001Matplotlib\u548cSQLAlchemy\uff0c\u4ee5\u5b9e\u73b0\u5b8c\u6574\u7684\u6570\u636e\u5904\u7406\u3001\u5206\u6790\u548c\u53ef\u89c6\u5316\u6d41\u7a0b\u3002<\/p>\n<\/p>\n
                        5.1\u3001\u6570\u636e\u5206\u6790\u6d41\u7a0b<\/h4>\n<\/p>\n
                        \u4e0b\u9762\u662f\u4e00\u4e2a\u5178\u578b\u7684\u6570\u636e\u5206\u6790\u6d41\u7a0b\uff0c\u7ed3\u5408\u4e86\u6570\u636e\u8bfb\u53d6\u3001\u6e05\u6d17\u3001\u5206\u6790\u548c\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n
                        # \u8bfb\u53d6\u6570\u636e<\/p>\n
                        data = pd.read_csv('data.csv')<\/p>\n
                        \u6570\u636e\u6e05\u6d17<\/strong><\/h2>\n
                        data_cleaned = data.dropna()<\/p>\n
                        \u6570\u636e\u5206\u6790<\/strong><\/h2>\n
                        average_values = data_cleaned.groupby('category').mean()<\/p>\n
                        \u6570\u636e\u53ef\u89c6\u5316<\/strong><\/h2>\n
                        plt.bar(average_values.index, average_values['value'])<\/p>\n
                        plt.title('Average Values by Category')<\/p>\n
                        plt.xlabel('Category')<\/p>\n
                        plt.ylabel('Average Value')<\/p>\n
                        plt.show()<\/p>\n
                        <\/code><\/pre>\n<\/p>\n
                        5.2\u3001\u6570\u636e\u5e93\u64cd\u4f5c\u4e0e\u5206\u6790<\/h4>\n<\/p>\n
                        \u7ed3\u5408SQLAlchemy\u548cPandas\uff0c\u53ef\u4ee5\u5b9e\u73b0\u6570\u636e\u5e93\u7684\u6570\u636e\u5206\u6790\u548c\u7ed3\u679c\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n
                        # \u521b\u5efa\u6570\u636e\u5e93\u8fde\u63a5<\/p>\n
                        engine = create_engine('sqlite:\/\/\/database.db')<\/p>\n
                        \u6267\u884cSQL\u67e5\u8be2\u5e76\u52a0\u8f7d\u6570\u636e<\/strong><\/h2>\n
                        query = 'SELECT * FROM sales'<\/p>\n
                        sales_data = pd.read_sql(query, engine)<\/p>\n
                        \u6570\u636e\u5206\u6790<\/strong><\/h2>\n
                        total_sales = sales_data.groupby('product').sum()<\/p>\n
                        \u6570\u636e\u53ef\u89c6\u5316<\/strong><\/h2>\n
                        plt.bar(total_sales.index, total_sales['amount'])<\/p>\n
                        plt.title('Total Sales by Product')<\/p>\n
                        plt.xlabel('Product')<\/p>\n
                        plt.ylabel('Total Sales')<\/p>\n
                        plt.show()<\/p>\n
                        <\/code><\/pre>\n<\/p>\n
                        \u901a\u8fc7\u4e0a\u8ff0\u65b9\u6cd5\u548c\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u5728Python\u4e2d\u9ad8\u6548\u5730\u8c03\u53d6\u3001\u5904\u7406\u548c\u5206\u6790\u6570\u636e\u3002\u8fd9\u4e9b\u5de5\u5177\u548c\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\uff0c\u80fd\u591f\u6ee1\u8db3\u5404\u79cd\u6570\u636e\u64cd\u4f5c\u9700\u6c42\u3002<\/p>\n<\/p>\n
                        \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
                         \u5982\u4f55\u5728Python\u4e2d\u8bfb\u53d6\u6570\u636e\u6587\u4ef6\uff1f<\/strong>
                        \u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u5e93\u6765\u8bfb\u53d6\u6570\u636e\u6587\u4ef6\uff0c\u5982pandas<\/code>\u3001csv<\/code>\u548copen<\/code>\u3002\u5bf9\u4e8eCSV\u6587\u4ef6\uff0cpandas<\/code>\u5e93\u63d0\u4f9b\u4e86\u975e\u5e38\u65b9\u4fbf\u7684read_csv<\/code>\u51fd\u6570\uff0c\u53ef\u4ee5\u5feb\u901f\u5c06CSV\u6587\u4ef6\u52a0\u8f7d\u4e3aDataFrame\uff0c\u4fbf\u4e8e\u540e\u7eed\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u3002\u53ea\u9700\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a  <\/p>\n
                        import pandas as pd\ndata = pd.read_csv('\u6587\u4ef6\u8def\u5f84.csv')\n<\/code><\/pre>\n
                        \u5bf9\u4e8eExcel\u6587\u4ef6\uff0c\u53ef\u4ee5\u4f7f\u7528pd.read_excel<\/code>\uff0c\u800c\u5bf9\u4e8eJSON\u6587\u4ef6\uff0c\u4f7f\u7528pd.read_json<\/code>\u3002\u8fd9\u4e9b\u65b9\u6cd5\u90fd\u652f\u6301\u591a\u79cd\u53c2\u6570\u914d\u7f6e\uff0c\u4ee5\u6ee1\u8db3\u4e0d\u540c\u7684\u6570\u636e\u8bfb\u53d6\u9700\u6c42\u3002<\/p>\n
                        \u5728Python\u4e2d\u5982\u4f55\u5904\u7406\u7f3a\u5931\u6570\u636e\uff1f<\/strong>
                        \u5904\u7406\u7f3a\u5931\u6570\u636e\u662f\u6570\u636e\u9884\u5904\u7406\u4e2d\u7684\u91cd\u8981\u6b65\u9aa4\u3002\u4f7f\u7528pandas<\/code>\u5e93\uff0c\u53ef\u4ee5\u901a\u8fc7isnull()<\/code>\u548cdropna()<\/code>\u7b49\u51fd\u6570\u6765\u8bc6\u522b\u548c\u5904\u7406\u7f3a\u5931\u503c\u3002\u4f8b\u5982\uff0cdata.dropna()<\/code>\u5c06\u5220\u9664\u542b\u6709\u7f3a\u5931\u503c\u7684\u884c\uff0c\u800cdata.fillna(0)<\/code>\u53ef\u4ee5\u75280\u66ff\u4ee3\u6240\u6709\u7f3a\u5931\u503c\u3002\u6839\u636e\u5177\u4f53\u7684\u5206\u6790\u9700\u6c42\uff0c\u53ef\u4ee5\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u6765\u5904\u7406\u7f3a\u5931\u6570\u636e\uff0c\u4ece\u800c\u786e\u4fdd\u6570\u636e\u7684\u5b8c\u6574\u6027\u3002<\/p>\n
                        Python\u4e2d\u5982\u4f55\u5bf9\u6570\u636e\u8fdb\u884c\u6e05\u6d17\u548c\u8f6c\u6362\uff1f<\/strong>
                        \u6570\u636e\u6e05\u6d17\u548c\u8f6c\u6362\u662f\u6570\u636e\u5206\u6790\u7684\u91cd\u8981\u73af\u8282\u3002\u5728Python\u4e2d\uff0cpandas<\/code>\u5e93\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u5de5\u5177\u6765\u5b9e\u73b0\u8fd9\u4e9b\u64cd\u4f5c\u3002\u53ef\u4ee5\u4f7f\u7528astype()<\/code>\u65b9\u6cd5\u5c06\u6570\u636e\u7c7b\u578b\u8f6c\u6362\uff0creplace()<\/code>\u65b9\u6cd5\u66ff\u6362\u7279\u5b9a\u503c\uff0c\u6216\u4f7f\u7528apply()<\/code>\u51fd\u6570\u5bf9\u5217\u8fdb\u884c\u81ea\u5b9a\u4e49\u5904\u7406\u3002\u6b64\u5916\uff0c\u53ef\u4ee5\u5229\u7528groupby()<\/code>\u548cagg()<\/code>\u65b9\u6cd5\u8fdb\u884c\u6570\u636e\u805a\u5408\u548c\u7edf\u8ba1\uff0c\u786e\u4fdd\u6570\u636e\u7b26\u5408\u5206\u6790\u9700\u6c42\u3002\u901a\u8fc7\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u53ef\u4ee5\u6709\u6548\u63d0\u5347\u6570\u636e\u8d28\u91cf\uff0c\u4ece\u800c\u83b7\u5f97\u66f4\u51c6\u786e\u7684\u5206\u6790\u7ed3\u679c\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u8c03\u6570\u636e\u7684\u65b9\u6cd5\u4e3b\u8981\u5305\u62ec\uff1a\u4f7f\u7528Pandas\u5e93\u8fdb\u884c\u6570\u636e\u5904\u7406\u3001\u5229\u7528NumPy\u8fdb\u884c\u6570\u503c\u8ba1\u7b97\u3001\u4f7f\u7528Matplo […]","protected":false},"author":3,"featured_media":937622,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/937617"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=937617"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/937617\/revisions"}],"predecessor-version":[{"id":937623,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/937617\/revisions\/937623"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/937622"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=937617"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=937617"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=937617"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}