{"id":1180720,"date":"2025-01-15T18:41:58","date_gmt":"2025-01-15T10:41:58","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1180720.html"},"modified":"2025-01-15T18:42:03","modified_gmt":"2025-01-15T10:42:03","slug":"python%e5%a6%82%e4%bd%95%e8%ae%a1%e7%ae%97%e5%88%97%e8%a1%a8%e5%b9%b3%e5%9d%87%e5%88%86","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1180720.html","title":{"rendered":"python\u5982\u4f55\u8ba1\u7b97\u5217\u8868\u5e73\u5747\u5206"},"content":{"rendered":"

\"python\u5982\u4f55\u8ba1\u7b97\u5217\u8868\u5e73\u5747\u5206\"<\/p>\n

Python\u8ba1\u7b97\u5217\u8868\u5e73\u5747\u5206\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528\u5185\u7f6e\u51fd\u6570\u3001numpy\u5e93\u3001pandas\u5e93\u7b49\u3002\u901a\u8fc7\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u4f60\u53ef\u4ee5\u65b9\u4fbf\u5730\u8ba1\u7b97\u51fa\u5217\u8868\u4e2d\u5143\u7d20\u7684\u5e73\u5747\u503c\u3002<\/strong>\u672c\u6587\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u5e76\u5206\u6790\u5176\u4f18\u7f3a\u70b9\uff0c\u4ee5\u5e2e\u52a9\u4f60\u9009\u62e9\u6700\u9002\u5408\u7684\u65b9\u5f0f\u8fdb\u884c\u8ba1\u7b97\u3002\u4ee5\u4e0b\u662f\u8be6\u7ec6\u89e3\u91ca\u5176\u4e2d\u4e00\u4e2a\u5e38\u7528\u65b9\u6cd5\u2014\u2014\u4f7f\u7528\u5185\u7f6e\u51fd\u6570\u3002<\/p>\n<\/p>\n

\u4f7f\u7528Python\u5185\u7f6e\u51fd\u6570\u8ba1\u7b97\u5217\u8868\u5e73\u5747\u5206<\/h3>\n<\/p>\n

Python\u5185\u7f6e\u7684\u51fd\u6570\u548c\u64cd\u4f5c\u7b26\u53ef\u4ee5\u65b9\u4fbf\u5730\u8ba1\u7b97\u5217\u8868\u7684\u5e73\u5747\u5206\u3002\u5177\u4f53\u6b65\u9aa4\u5982\u4e0b\uff1a<\/p>\n<\/p>\n

    \n
  1. \u8ba1\u7b97\u5217\u8868\u5143\u7d20\u7684\u603b\u548c<\/strong>\uff1a\u4f7f\u7528sum()<\/code>\u51fd\u6570\u3002<\/li>\n
  2. \u8ba1\u7b97\u5217\u8868\u7684\u957f\u5ea6<\/strong>\uff1a\u4f7f\u7528len()<\/code>\u51fd\u6570\u3002<\/li>\n
  3. \u8ba1\u7b97\u5e73\u5747\u503c<\/strong>\uff1a\u5c06\u603b\u548c\u9664\u4ee5\u957f\u5ea6\u3002<\/li>\n<\/ol>\n

    \u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n<\/p>\n

    def calculate_average(numbers):<\/p>\n
        return sum(numbers) \/ len(numbers)<\/p>\n
    \u793a\u4f8b\u5217\u8868<\/strong><\/h2>\n
    numbers = [1, 2, 3, 4, 5]<\/p>\n
    average = calculate_average(numbers)<\/p>\n
    print(f"\u5217\u8868\u7684\u5e73\u5747\u503c\u662f: {average}")<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0csum(numbers)<\/code>\u8ba1\u7b97\u5217\u8868\u5143\u7d20\u7684\u603b\u548c\uff0clen(numbers)<\/code>\u8fd4\u56de\u5217\u8868\u7684\u957f\u5ea6\uff0c\u5c06\u4e24\u8005\u76f8\u9664\u5f97\u5230\u5e73\u5747\u503c\u3002<\/p>\n<\/p>\n
    \u4e00\u3001\u4f7f\u7528\u5185\u7f6e\u51fd\u6570\u7684\u4f18\u7f3a\u70b9<\/h3>\n<\/p>\n
    \u4f18\u70b9\uff1a<\/h4>\n<\/p>\n
      \n
    1. \u7b80\u6d01\u660e\u4e86<\/strong>\uff1a\u5185\u7f6e\u51fd\u6570\u7684\u4f7f\u7528\u975e\u5e38\u76f4\u89c2\uff0c\u4ee3\u7801\u7b80\u6d01\u6613\u61c2\u3002<\/li>\n
    2. \u6027\u80fd\u826f\u597d<\/strong>\uff1a\u5bf9\u4e8e\u5c0f\u89c4\u6a21\u6570\u636e\u96c6\uff0c\u5185\u7f6e\u51fd\u6570\u7684\u6027\u80fd\u975e\u5e38\u597d\u3002<\/li>\n
    3. \u65e0\u9700\u989d\u5916\u4f9d\u8d56<\/strong>\uff1a\u4e0d\u9700\u8981\u5b89\u88c5\u989d\u5916\u7684\u5e93\uff0c\u9002\u7528\u4e8e\u7b80\u5355\u7684\u8ba1\u7b97\u573a\u666f\u3002<\/li>\n<\/ol>\n
      \u7f3a\u70b9\uff1a<\/h4>\n<\/p>\n
        \n
      1. \u6269\u5c55\u6027\u5dee<\/strong>\uff1a\u5bf9\u4e8e\u590d\u6742\u7684\u6570\u636e\u5904\u7406\u9700\u6c42\uff0c\u53ef\u80fd\u9700\u8981\u7f16\u5199\u989d\u5916\u7684\u4ee3\u7801\u3002<\/li>\n
      2. \u4e0d\u9002\u5408\u5927\u6570\u636e\u96c6<\/strong>\uff1a\u5f53\u6570\u636e\u96c6\u975e\u5e38\u5927\u65f6\uff0c\u5185\u7f6e\u51fd\u6570\u7684\u6027\u80fd\u53ef\u80fd\u4f1a\u53d7\u5230\u5f71\u54cd\u3002<\/li>\n<\/ol>\n
        \u4e8c\u3001\u4f7f\u7528numpy\u5e93\u8ba1\u7b97\u5217\u8868\u5e73\u5747\u5206<\/h3>\n<\/p>\n
        Numpy\u662fPython\u4e2d\u4e00\u4e2a\u975e\u5e38\u5f3a\u5927\u7684\u79d1\u5b66\u8ba1\u7b97\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u8bb8\u591a\u9ad8\u6548\u7684\u6570\u7ec4\u64cd\u4f5c\u51fd\u6570\u3002\u4f7f\u7528numpy\u8ba1\u7b97\u5217\u8868\u5e73\u5747\u5206\u7684\u65b9\u6cd5\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
          \n
        1. \u5bfc\u5165numpy\u5e93<\/strong>\u3002<\/li>\n
        2. \u5c06\u5217\u8868\u8f6c\u6362\u4e3anumpy\u6570\u7ec4<\/strong>\uff1a\u4f7f\u7528numpy.array()<\/code>\u51fd\u6570\u3002<\/li>\n
        3. \u8ba1\u7b97\u5e73\u5747\u503c<\/strong>\uff1a\u4f7f\u7528numpy.mean()<\/code>\u51fd\u6570\u3002<\/li>\n<\/ol>\n
          \u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
          import numpy as np<\/p>\n
          def calculate_average(numbers):<\/p>\n
              array = np.array(numbers)<\/p>\n
              return np.mean(array)<\/p>\n
          \u793a\u4f8b\u5217\u8868<\/strong><\/h2>\n
          numbers = [1, 2, 3, 4, 5]<\/p>\n
          average = calculate_average(numbers)<\/p>\n
          print(f"\u5217\u8868\u7684\u5e73\u5747\u503c\u662f: {average}")<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0cnp.array(numbers)<\/code>\u5c06\u5217\u8868\u8f6c\u6362\u4e3anumpy\u6570\u7ec4\uff0cnp.mean(array)<\/code>\u8ba1\u7b97\u6570\u7ec4\u7684\u5e73\u5747\u503c\u3002<\/p>\n<\/p>\n
          \u4f18\u70b9\uff1a<\/h4>\n<\/p>\n
            \n
          1. \u9ad8\u6548<\/strong>\uff1anumpy\u5bf9\u5927\u89c4\u6a21\u6570\u636e\u96c6\u7684\u5904\u7406\u975e\u5e38\u9ad8\u6548\u3002<\/li>\n
          2. \u529f\u80fd\u4e30\u5bcc<\/strong>\uff1a\u63d0\u4f9b\u4e86\u8bb8\u591a\u79d1\u5b66\u8ba1\u7b97\u51fd\u6570\uff0c\u9002\u7528\u4e8e\u590d\u6742\u7684\u6570\u636e\u5904\u7406\u9700\u6c42\u3002<\/li>\n
          3. \u6613\u4e8e\u6269\u5c55<\/strong>\uff1a\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u77e9\u9635\u8fd0\u7b97\u548c\u5176\u4ed6\u9ad8\u7ea7\u8ba1\u7b97\u3002<\/li>\n<\/ol>\n
            \u7f3a\u70b9\uff1a<\/h4>\n<\/p>\n
              \n
            1. \u9700\u8981\u989d\u5916\u5b89\u88c5\u5e93<\/strong>\uff1a\u9700\u8981\u5b89\u88c5numpy\u5e93\uff0c\u5bf9\u4e8e\u7b80\u5355\u7684\u8ba1\u7b97\u53ef\u80fd\u663e\u5f97\u8fc7\u4e8e\u590d\u6742\u3002<\/li>\n
            2. \u5b66\u4e60\u66f2\u7ebf<\/strong>\uff1anumpy\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\uff0c\u521d\u5b66\u8005\u53ef\u80fd\u9700\u8981\u4e00\u5b9a\u65f6\u95f4\u5b66\u4e60\u548c\u9002\u5e94\u3002<\/li>\n<\/ol>\n
              \u4e09\u3001\u4f7f\u7528pandas\u5e93\u8ba1\u7b97\u5217\u8868\u5e73\u5747\u5206<\/h3>\n<\/p>\n
              Pandas\u662f\u53e6\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5e93\uff0c\u7279\u522b\u9002\u7528\u4e8e\u6570\u636e\u5206\u6790\u3002\u4f7f\u7528pandas\u8ba1\u7b97\u5217\u8868\u5e73\u5747\u5206\u7684\u65b9\u6cd5\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
                \n
              1. \u5bfc\u5165pandas\u5e93<\/strong>\u3002<\/li>\n
              2. \u5c06\u5217\u8868\u8f6c\u6362\u4e3apandas Series\u5bf9\u8c61<\/strong>\uff1a\u4f7f\u7528pandas.Series()<\/code>\u51fd\u6570\u3002<\/li>\n
              3. \u8ba1\u7b97\u5e73\u5747\u503c<\/strong>\uff1a\u4f7f\u7528Series.mean()<\/code>\u65b9\u6cd5\u3002<\/li>\n<\/ol>\n
                \u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
                import pandas as pd<\/p>\n
                def calculate_average(numbers):<\/p>\n
                    series = pd.Series(numbers)<\/p>\n
                    return series.mean()<\/p>\n
                \u793a\u4f8b\u5217\u8868<\/strong><\/h2>\n
                numbers = [1, 2, 3, 4, 5]<\/p>\n
                average = calculate_average(numbers)<\/p>\n
                print(f"\u5217\u8868\u7684\u5e73\u5747\u503c\u662f: {average}")<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                \u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0cpd.Series(numbers)<\/code>\u5c06\u5217\u8868\u8f6c\u6362\u4e3apandas Series\u5bf9\u8c61\uff0cseries.mean()<\/code>\u8ba1\u7b97Series\u5bf9\u8c61\u7684\u5e73\u5747\u503c\u3002<\/p>\n<\/p>\n
                \u4f18\u70b9\uff1a<\/h4>\n<\/p>\n
                  \n
                1. \u6570\u636e\u5904\u7406\u529f\u80fd\u5f3a\u5927<\/strong>\uff1apandas\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u529f\u80fd\uff0c\u9002\u7528\u4e8e\u590d\u6742\u7684\u6570\u636e\u5206\u6790\u9700\u6c42\u3002<\/li>\n
                2. \u65b9\u4fbf\u4e0e\u5176\u4ed6\u5e93\u7ed3\u5408\u4f7f\u7528<\/strong>\uff1apandas\u4e0enumpy\u3001matplotlib\u7b49\u5e93\u914d\u5408\u4f7f\u7528\uff0c\u53ef\u4ee5\u8fdb\u884c\u9ad8\u6548\u7684\u6570\u636e\u5206\u6790\u548c\u53ef\u89c6\u5316\u3002<\/li>\n
                3. \u652f\u6301\u7f3a\u5931\u503c\u5904\u7406<\/strong>\uff1apandas\u53ef\u4ee5\u65b9\u4fbf\u5730\u5904\u7406\u7f3a\u5931\u503c\uff0c\u8ba1\u7b97\u5e73\u5747\u503c\u65f6\u81ea\u52a8\u5ffd\u7565NaN\u503c\u3002<\/li>\n<\/ol>\n
                  \u7f3a\u70b9\uff1a<\/h4>\n<\/p>\n
                    \n
                  1. \u9700\u8981\u989d\u5916\u5b89\u88c5\u5e93<\/strong>\uff1a\u9700\u8981\u5b89\u88c5pandas\u5e93\uff0c\u5bf9\u4e8e\u7b80\u5355\u7684\u8ba1\u7b97\u53ef\u80fd\u663e\u5f97\u8fc7\u4e8e\u590d\u6742\u3002<\/li>\n
                  2. \u5b66\u4e60\u66f2\u7ebf<\/strong>\uff1apandas\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\uff0c\u521d\u5b66\u8005\u53ef\u80fd\u9700\u8981\u4e00\u5b9a\u65f6\u95f4\u5b66\u4e60\u548c\u9002\u5e94\u3002<\/li>\n<\/ol>\n
                    \u56db\u3001\u4f7f\u7528\u7edf\u8ba1\u5e93statistics\u8ba1\u7b97\u5217\u8868\u5e73\u5747\u5206<\/h3>\n<\/p>\n
                    Python\u7684statistics\u5e93\u662f\u4e00\u4e2a\u6807\u51c6\u5e93\uff0c\u4e13\u95e8\u7528\u4e8e\u7edf\u8ba1\u8ba1\u7b97\u3002\u4f7f\u7528statistics\u5e93\u8ba1\u7b97\u5217\u8868\u5e73\u5747\u5206\u7684\u65b9\u6cd5\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
                      \n
                    1. \u5bfc\u5165statistics\u5e93<\/strong>\u3002<\/li>\n
                    2. \u8ba1\u7b97\u5e73\u5747\u503c<\/strong>\uff1a\u4f7f\u7528statistics.mean()<\/code>\u51fd\u6570\u3002<\/li>\n<\/ol>\n
                      \u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
                      import statistics<\/p>\n
                      def calculate_average(numbers):<\/p>\n
                          return statistics.mean(numbers)<\/p>\n
                      \u793a\u4f8b\u5217\u8868<\/strong><\/h2>\n
                      numbers = [1, 2, 3, 4, 5]<\/p>\n
                      average = calculate_average(numbers)<\/p>\n
                      print(f"\u5217\u8868\u7684\u5e73\u5747\u503c\u662f: {average}")<\/p>\n
                      <\/code><\/pre>\n<\/p>\n
                      \u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0cstatistics.mean(numbers)<\/code>\u76f4\u63a5\u8ba1\u7b97\u5217\u8868\u7684\u5e73\u5747\u503c\u3002<\/p>\n<\/p>\n
                      \u4f18\u70b9\uff1a<\/h4>\n<\/p>\n
                        \n
                      1. \u7b80\u6d01\u660e\u4e86<\/strong>\uff1astatistics\u5e93\u7684\u4f7f\u7528\u975e\u5e38\u76f4\u89c2\uff0c\u4ee3\u7801\u7b80\u6d01\u6613\u61c2\u3002<\/li>\n
                      2. \u6027\u80fd\u826f\u597d<\/strong>\uff1a\u5bf9\u4e8e\u5c0f\u89c4\u6a21\u6570\u636e\u96c6\uff0cstatistics\u5e93\u7684\u6027\u80fd\u975e\u5e38\u597d\u3002<\/li>\n
                      3. \u65e0\u9700\u989d\u5916\u5b89\u88c5\u5e93<\/strong>\uff1astatistics\u662fPython\u7684\u6807\u51c6\u5e93\uff0c\u4e0d\u9700\u8981\u989d\u5916\u5b89\u88c5\u3002<\/li>\n<\/ol>\n
                        \u7f3a\u70b9\uff1a<\/h4>\n<\/p>\n
                          \n
                        1. \u529f\u80fd\u6709\u9650<\/strong>\uff1astatistics\u5e93\u7684\u529f\u80fd\u76f8\u5bf9\u6709\u9650\uff0c\u9002\u7528\u4e8e\u7b80\u5355\u7684\u7edf\u8ba1\u8ba1\u7b97\u3002<\/li>\n
                        2. \u4e0d\u9002\u5408\u5927\u6570\u636e\u96c6<\/strong>\uff1a\u5f53\u6570\u636e\u96c6\u975e\u5e38\u5927\u65f6\uff0cstatistics\u5e93\u7684\u6027\u80fd\u53ef\u80fd\u4f1a\u53d7\u5230\u5f71\u54cd\u3002<\/li>\n<\/ol>\n
                          \u4e94\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
                          \u7efc\u4e0a\u6240\u8ff0\uff0cPython\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u8ba1\u7b97\u5217\u8868\u7684\u5e73\u5747\u5206\uff0c\u5305\u62ec\u4f7f\u7528\u5185\u7f6e\u51fd\u6570\u3001numpy\u5e93\u3001pandas\u5e93\u548cstatistics\u5e93\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u4f18\u7f3a\u70b9\uff0c\u9002\u7528\u4e8e\u4e0d\u540c\u7684\u5e94\u7528\u573a\u666f\u3002\u5bf9\u4e8e\u7b80\u5355\u7684\u8ba1\u7b97\uff0c\u53ef\u4ee5\u9009\u62e9\u4f7f\u7528\u5185\u7f6e\u51fd\u6570\u6216statistics\u5e93\uff1b\u5bf9\u4e8e\u5927\u89c4\u6a21\u6570\u636e\u96c6\u6216\u590d\u6742\u7684\u6570\u636e\u5904\u7406\u9700\u6c42\uff0c\u53ef\u4ee5\u9009\u62e9\u4f7f\u7528numpy\u6216pandas\u5e93\u3002\u5e0c\u671b\u672c\u6587\u4ecb\u7ecd\u7684\u65b9\u6cd5\u548c\u5206\u6790\u80fd\u5e2e\u52a9\u4f60\u9009\u62e9\u6700\u9002\u5408\u7684\u65b9\u5f0f\u8fdb\u884c\u5217\u8868\u5e73\u5747\u5206\u7684\u8ba1\u7b97\u3002<\/p>\n<\/p>\n
                          \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
                           \u5982\u4f55\u5728Python\u4e2d\u8ba1\u7b97\u4e00\u4e2a\u5217\u8868\u7684\u5e73\u5747\u503c\uff1f<\/strong>
                          \u5728Python\u4e2d\uff0c\u8ba1\u7b97\u5217\u8868\u7684\u5e73\u5747\u503c\u53ef\u4ee5\u901a\u8fc7\u5185\u7f6e\u7684sum()<\/code>\u51fd\u6570\u548clen()<\/code>\u51fd\u6570\u5b9e\u73b0\u3002\u9996\u5148\uff0c\u4f7f\u7528sum()<\/code>\u51fd\u6570\u8ba1\u7b97\u5217\u8868\u4e2d\u6240\u6709\u5143\u7d20\u7684\u603b\u548c\uff0c\u7136\u540e\u4f7f\u7528len()<\/code>\u51fd\u6570\u83b7\u53d6\u5217\u8868\u7684\u5143\u7d20\u6570\u91cf\u3002\u5c06\u603b\u548c\u9664\u4ee5\u6570\u91cf\u5373\u53ef\u5f97\u5230\u5e73\u5747\u503c\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a  <\/p>\n
                          numbers = [10, 20, 30, 40, 50]\naverage = sum(numbers) \/ len(numbers)\nprint(average)  # \u8f93\u51fa 30.0\n<\/code><\/pre>\n
                          \u5982\u679c\u5217\u8868\u4e3a\u7a7a\uff0c\u5982\u4f55\u5904\u7406\u5e73\u5747\u503c\u7684\u8ba1\u7b97\uff1f<\/strong>
                          \u5728\u8ba1\u7b97\u5e73\u5747\u503c\u65f6\uff0c\u5982\u679c\u5217\u8868\u4e3a\u7a7a\uff0c\u5c06\u4f1a\u5bfc\u81f4\u9664\u4ee5\u96f6\u7684\u9519\u8bef\u3002\u4e3a\u907f\u514d\u8fd9\u79cd\u60c5\u51b5\uff0c\u5efa\u8bae\u5728\u8ba1\u7b97\u4e4b\u524d\u68c0\u67e5\u5217\u8868\u662f\u5426\u4e3a\u7a7a\u3002\u53ef\u4ee5\u4f7f\u7528\u6761\u4ef6\u8bed\u53e5\u6765\u5224\u65ad\uff0c\u5982\u679c\u5217\u8868\u4e3a\u7a7a\uff0c\u5219\u8fd4\u56de\u4e00\u4e2a\u7279\u5b9a\u7684\u503c\u6216\u63d0\u793a\u4fe1\u606f\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a  <\/p>\n
                          numbers = []\nif len(numbers) == 0:\n    average = None\nelse:\n    average = sum(numbers) \/ len(numbers)\nprint(average)  # \u8f93\u51fa None\n<\/code><\/pre>\n
                          Python\u4e2d\u662f\u5426\u6709\u5176\u4ed6\u5e93\u53ef\u4ee5\u7b80\u5316\u5e73\u5747\u503c\u7684\u8ba1\u7b97\uff1f<\/strong>
                          \u662f\u7684\uff0cPython\u4e2d\u7684numpy<\/code>\u5e93\u63d0\u4f9b\u4e86\u66f4\u4e3a\u7b80\u4fbf\u7684\u65b9\u6cd5\u6765\u8ba1\u7b97\u5e73\u5747\u503c\u3002\u4f7f\u7528numpy.mean()<\/code>\u51fd\u6570\u53ef\u4ee5\u76f4\u63a5\u8ba1\u7b97\u6570\u7ec4\u7684\u5e73\u5747\u503c\uff0c\u800c\u4e14\u8be5\u65b9\u6cd5\u5728\u5904\u7406\u5927\u578b\u6570\u636e\u65f6\u66f4\u4e3a\u9ad8\u6548\u3002\u4f7f\u7528\u793a\u4f8b\uff1a  <\/p>\n
                          import numpy as np\nnumbers = [10, 20, 30, 40, 50]\naverage = np.mean(numbers)\nprint(average)  # \u8f93\u51fa 30.0\n<\/code><\/pre>\n
                          \u901a\u8fc7\u4f7f\u7528numpy<\/code>\uff0c\u4e0d\u4ec5\u53ef\u4ee5\u63d0\u9ad8\u4ee3\u7801\u7684\u53ef\u8bfb\u6027\uff0c\u8fd8\u53ef\u4ee5\u63d0\u5347\u8ba1\u7b97\u6548\u7387\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u8ba1\u7b97\u5217\u8868\u5e73\u5747\u5206\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528\u5185\u7f6e\u51fd\u6570\u3001numpy\u5e93\u3001pandas\u5e93\u7b49\u3002\u901a\u8fc7\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u4f60\u53ef\u4ee5\u65b9\u4fbf\u5730\u8ba1 […]","protected":false},"author":3,"featured_media":1180726,"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\/1180720"}],"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=1180720"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1180720\/revisions"}],"predecessor-version":[{"id":1180727,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1180720\/revisions\/1180727"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1180726"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1180720"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1180720"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1180720"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}