{"id":995530,"date":"2024-12-27T09:05:36","date_gmt":"2024-12-27T01:05:36","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/995530.html"},"modified":"2024-12-27T09:05:38","modified_gmt":"2024-12-27T01:05:38","slug":"python%e5%a6%82%e4%bd%95%e5%be%97%e5%88%b0%e6%9c%88%e5%9d%87%e6%94%b6%e7%9b%8a","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/995530.html","title":{"rendered":"Python\u5982\u4f55\u5f97\u5230\u6708\u5747\u6536\u76ca"},"content":{"rendered":"

\"Python\u5982\u4f55\u5f97\u5230\u6708\u5747\u6536\u76ca\"<\/p>\n

\u5728Python\u4e2d\u8ba1\u7b97\u6708\u5747\u6536\u76ca\u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528Pandas\u5e93\u5904\u7406\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u3001\u901a\u8fc7\u8ba1\u7b97\u6bcf\u6708\u7684\u6536\u76ca\u7387\u3001\u7136\u540e\u6c42\u53d6\u8fd9\u4e9b\u6536\u76ca\u7387\u7684\u5e73\u5747\u503c\u3002<\/strong>\u4f7f\u7528Pandas\u5e93\u53ef\u4ee5\u65b9\u4fbf\u5730\u5bf9\u91d1\u878d\u6570\u636e\u8fdb\u884c\u64cd\u4f5c\uff0c\u5e76\u4e14\u53ef\u4ee5\u901a\u8fc7\u65e5\u671f\u7d22\u5f15\u8f7b\u677e\u8ba1\u7b97\u6bcf\u4e2a\u6708\u7684\u6536\u76ca\u3002\u5728\u8ba1\u7b97\u6708\u6536\u76ca\u65f6\uff0c\u9996\u5148\u9700\u8981\u5f97\u5230\u6bcf\u4e2a\u6708\u7684\u521d\u59cb\u548c\u6700\u7ec8\u4ef7\u683c\uff0c\u7136\u540e\u8ba1\u7b97\u6bcf\u6708\u7684\u6536\u76ca\u7387\uff0c\u6700\u540e\u6c42\u53d6\u6240\u6709\u6708\u6536\u76ca\u7387\u7684\u5e73\u5747\u503c\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u5728Python\u4e2d\u5b9e\u73b0\u8fd9\u4e00\u8fc7\u7a0b\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528Pandas\u5e93\u5904\u7406\u65f6\u95f4\u5e8f\u5217\u6570\u636e<\/p>\n<\/p>\n

Pandas\u662fPython\u4e2d\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5e93\uff0c\u7279\u522b\u9002\u7528\u4e8e\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u7684\u64cd\u4f5c\u3002\u5728\u8ba1\u7b97\u6708\u5747\u6536\u76ca\u65f6\uff0c\u901a\u5e38\u4f1a\u4f7f\u7528Pandas\u5e93\u6765\u52a0\u8f7d\u548c\u5904\u7406\u6570\u636e\u3002<\/p>\n<\/p>\n

    \n
  1. \n

    \u52a0\u8f7d\u6570\u636e<\/strong><\/p>\n<\/p>\n

    \u901a\u5e38\uff0c\u91d1\u878d\u6570\u636e\u4f1a\u4ee5CSV\u6587\u4ef6\u7684\u5f62\u5f0f\u5b58\u50a8\u3002\u53ef\u4ee5\u4f7f\u7528Pandas\u7684read_csv()<\/code>\u51fd\u6570\u6765\u52a0\u8f7d\u6570\u636e\u3002\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2aCSV\u6587\u4ef6\uff0c\u5176\u4e2d\u5305\u542b\u4e86\u67d0\u53ea\u80a1\u7968\u7684\u65e5\u671f\u548c\u6536\u76d8\u4ef7\u683c\u3002<\/p>\n<\/p>\n

    import pandas as pd<\/p>\n
    \u52a0\u8f7d\u6570\u636e<\/strong><\/h2>\n
    data = pd.read_csv('stock_data.csv')<\/p>\n
    \u67e5\u770b\u6570\u636e\u7684\u524d\u51e0\u884c<\/strong><\/h2>\n
    print(data.head())<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u52a0\u8f7d\u6570\u636e\u540e\uff0c\u901a\u5e38\u4f1a\u5f97\u5230\u4e00\u4e2aDataFrame\uff0c\u5176\u4e2d\u5305\u542b\u4e86\u65e5\u671f\u548c\u6536\u76d8\u4ef7\u683c\u4e24\u5217\u3002<\/p>\n<\/p>\n<\/li>\n
  2. \n
    \u8bbe\u7f6e\u65e5\u671f\u7d22\u5f15<\/strong><\/p>\n<\/p>\n
    \u4e3a\u4e86\u65b9\u4fbf\u5904\u7406\u65f6\u95f4\u5e8f\u5217\u6570\u636e\uff0c\u9700\u8981\u5c06\u65e5\u671f\u5217\u8bbe\u7f6e\u4e3aDataFrame\u7684\u7d22\u5f15\u3002<\/p>\n<\/p>\n
    # \u5c06\u65e5\u671f\u5217\u8f6c\u6362\u4e3a\u65e5\u671f\u7c7b\u578b<\/p>\n
    data['Date'] = pd.to_datetime(data['Date'])<\/p>\n
    \u8bbe\u7f6e\u65e5\u671f\u5217\u4e3a\u7d22\u5f15<\/strong><\/h2>\n
    data.set_index('Date', inplace=True)<\/p>\n
    \u67e5\u770b\u6570\u636e<\/strong><\/h2>\n
    print(data.head())<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u8fd9\u6837\u5904\u7406\u540e\uff0cDataFrame\u7684\u7d22\u5f15\u5c06\u662f\u65e5\u671f\uff0c\u8fd9\u6837\u5c31\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6309\u6708\u5206\u7ec4\u7b49\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n
    \u4e8c\u3001\u8ba1\u7b97\u6bcf\u6708\u7684\u6536\u76ca\u7387<\/p>\n<\/p>\n
    \u5728\u8ba1\u7b97\u6708\u6536\u76ca\u7387\u65f6\uff0c\u9700\u8981\u5f97\u5230\u6bcf\u4e2a\u6708\u7684\u521d\u59cb\u548c\u6700\u7ec8\u4ef7\u683c\u3002<\/p>\n<\/p>\n
      \n
    1. \n
      \u6309\u6708\u5206\u7ec4<\/strong><\/p>\n<\/p>\n
      \u4f7f\u7528Pandas\u7684resample()<\/code>\u51fd\u6570\uff0c\u53ef\u4ee5\u5f88\u65b9\u4fbf\u5730\u6309\u6708\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u7ec4\u3002<\/p>\n<\/p>\n
      # \u6309\u6708\u5206\u7ec4\u5e76\u83b7\u53d6\u6bcf\u6708\u7684\u6700\u540e\u4e00\u4e2a\u6570\u636e\u70b9<\/p>\n
      monthly_data = data.resample('M').last()<\/p>\n
      \u67e5\u770b\u6309\u6708\u5206\u7ec4\u7684\u6570\u636e<\/strong><\/h2>\n
      print(monthly_data.head())<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      resample('M')<\/code>\u5c06\u6570\u636e\u6309\u6708\u8fdb\u884c\u5206\u7ec4\uff0clast()<\/code>\u51fd\u6570\u5219\u83b7\u53d6\u6bcf\u4e2a\u6708\u7684\u6700\u540e\u4e00\u4e2a\u6570\u636e\u70b9\uff0c\u5373\u6bcf\u4e2a\u6708\u7684\u6536\u76d8\u4ef7\u683c\u3002<\/p>\n<\/p>\n<\/li>\n
    2. \n
      \u8ba1\u7b97\u6708\u6536\u76ca\u7387<\/strong><\/p>\n<\/p>\n
      \u6708\u6536\u76ca\u7387\u53ef\u4ee5\u901a\u8fc7\u672c\u6708\u7684\u6536\u76d8\u4ef7\u683c\u4e0e\u4e0a\u6708\u7684\u6536\u76d8\u4ef7\u683c\u8fdb\u884c\u6bd4\u8f83\u6765\u8ba1\u7b97\u3002<\/p>\n<\/p>\n
      # \u8ba1\u7b97\u6708\u6536\u76ca\u7387<\/p>\n
      monthly_data['Monthly Return'] = monthly_data['Close'].pct_change()<\/p>\n
      \u67e5\u770b\u6708\u6536\u76ca\u7387<\/strong><\/h2>\n
      print(monthly_data.head())<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      pct_change()<\/code>\u51fd\u6570\u7528\u4e8e\u8ba1\u7b97\u767e\u5206\u6bd4\u53d8\u5316\uff0c\u5373\u6536\u76ca\u7387\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n
      \u4e09\u3001\u6c42\u53d6\u6708\u5747\u6536\u76ca<\/p>\n<\/p>\n
      \u5728\u83b7\u5f97\u6bcf\u6708\u7684\u6536\u76ca\u7387\u540e\uff0c\u6700\u540e\u4e00\u6b65\u662f\u8ba1\u7b97\u8fd9\u4e9b\u6536\u76ca\u7387\u7684\u5e73\u5747\u503c\u3002<\/p>\n<\/p>\n
        \n
      1. \n
        \u8ba1\u7b97\u6708\u5747\u6536\u76ca<\/strong><\/p>\n<\/p>\n
        \u4f7f\u7528Pandas\u7684mean()<\/code>\u51fd\u6570\u53ef\u4ee5\u5f88\u65b9\u4fbf\u5730\u8ba1\u7b97\u5e73\u5747\u503c\u3002<\/p>\n<\/p>\n
        # \u8ba1\u7b97\u6708\u5747\u6536\u76ca<\/p>\n
        monthly_average_return = monthly_data['Monthly Return'].mean()<\/p>\n
        print(f"\u6708\u5747\u6536\u76ca: {monthly_average_return:.2%}")<\/p>\n
        <\/code><\/pre>\n<\/p>\n
        \u901a\u8fc7\u4e0a\u8ff0\u6b65\u9aa4\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u5f97\u5230\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u7684\u6708\u5747\u6536\u76ca\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n
        \u56db\u3001\u8003\u8651\u5176\u4ed6\u56e0\u7d20<\/p>\n<\/p>\n
        \u5728\u8ba1\u7b97\u6708\u5747\u6536\u76ca\u65f6\uff0c\u8fd8\u9700\u8981\u8003\u8651\u5176\u4ed6\u53ef\u80fd\u5f71\u54cd\u7ed3\u679c\u7684\u56e0\u7d20\uff0c\u4f8b\u5982\u6570\u636e\u7684\u5b8c\u6574\u6027\u3001\u5f02\u5e38\u503c\u7684\u5904\u7406\u7b49\u3002<\/p>\n<\/p>\n
          \n
        1. \n
          \u68c0\u67e5\u6570\u636e\u5b8c\u6574\u6027<\/strong><\/p>\n<\/p>\n
          \u5728\u8ba1\u7b97\u6536\u76ca\u7387\u65f6\uff0c\u786e\u4fdd\u6570\u636e\u7684\u5b8c\u6574\u6027\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002\u5982\u679c\u6570\u636e\u4e2d\u5b58\u5728\u7f3a\u5931\u503c\uff0c\u53ef\u80fd\u4f1a\u5bfc\u81f4\u8ba1\u7b97\u7ed3\u679c\u4e0d\u51c6\u786e\u3002\u53ef\u4ee5\u4f7f\u7528dropna()<\/code>\u51fd\u6570\u53bb\u9664\u7f3a\u5931\u503c\u3002<\/p>\n<\/p>\n
          # \u53bb\u9664\u7f3a\u5931\u503c<\/p>\n
          monthly_data.dropna(inplace=True)<\/p>\n
          <\/code><\/pre>\n<\/p>\n<\/li>\n
        2. \n
          \u5904\u7406\u5f02\u5e38\u503c<\/strong><\/p>\n<\/p>\n
          \u5728\u91d1\u878d\u6570\u636e\u4e2d\uff0c\u5f02\u5e38\u503c\u53ef\u80fd\u4f1a\u4e25\u91cd\u5f71\u54cd\u8ba1\u7b97\u7ed3\u679c\u3002\u56e0\u6b64\uff0c\u5728\u8ba1\u7b97\u4e4b\u524d\uff0c\u5e94\u8be5\u68c0\u67e5\u6570\u636e\u4e2d\u662f\u5426\u5b58\u5728\u5f02\u5e38\u503c\uff0c\u5e76\u8fdb\u884c\u9002\u5f53\u7684\u5904\u7406\u3002<\/p>\n<\/p>\n
          # \u4f7f\u7528\u7bb1\u7ebf\u56fe\u67e5\u770b\u6570\u636e\u5206\u5e03<\/p>\n
          import matplotlib.pyplot as plt<\/p>\n
          plt.boxplot(monthly_data['Monthly Return'].dropna())<\/p>\n
          plt.show()<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u5982\u679c\u53d1\u73b0\u5f02\u5e38\u503c\uff0c\u53ef\u4ee5\u8003\u8651\u4f7f\u7528\u4e2d\u4f4d\u6570\u66ff\u4ee3\u5f02\u5e38\u503c\uff0c\u6216\u8005\u76f4\u63a5\u53bb\u9664\u8fd9\u4e9b\u6570\u636e\u70b9\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n
          \u4e94\u3001\u4ee3\u7801\u5c01\u88c5<\/p>\n<\/p>\n
          \u4e3a\u4e86\u63d0\u9ad8\u4ee3\u7801\u7684\u91cd\u7528\u6027\uff0c\u53ef\u4ee5\u5c06\u4e0a\u8ff0\u6b65\u9aa4\u5c01\u88c5\u6210\u4e00\u4e2a\u51fd\u6570\u3002<\/p>\n<\/p>\n
          import pandas as pd<\/p>\n
          def calculate_monthly_average_return(file_path):<\/p>\n
              # \u52a0\u8f7d\u6570\u636e<\/p>\n
              data = pd.read_csv(file_path)<\/p>\n
              # \u5c06\u65e5\u671f\u5217\u8f6c\u6362\u4e3a\u65e5\u671f\u7c7b\u578b<\/p>\n
              data['Date'] = pd.to_datetime(data['Date'])<\/p>\n
              # \u8bbe\u7f6e\u65e5\u671f\u5217\u4e3a\u7d22\u5f15<\/p>\n
              data.set_index('Date', inplace=True)<\/p>\n
              # \u6309\u6708\u5206\u7ec4\u5e76\u83b7\u53d6\u6bcf\u6708\u7684\u6700\u540e\u4e00\u4e2a\u6570\u636e\u70b9<\/p>\n
              monthly_data = data.resample('M').last()<\/p>\n
              # \u8ba1\u7b97\u6708\u6536\u76ca\u7387<\/p>\n
              monthly_data['Monthly Return'] = monthly_data['Close'].pct_change()<\/p>\n
              # \u53bb\u9664\u7f3a\u5931\u503c<\/p>\n
              monthly_data.dropna(inplace=True)<\/p>\n
              # \u8ba1\u7b97\u6708\u5747\u6536\u76ca<\/p>\n
              monthly_average_return = monthly_data['Monthly Return'].mean()<\/p>\n
              return monthly_average_return<\/p>\n
          \u4f7f\u7528\u51fd\u6570\u8ba1\u7b97\u6708\u5747\u6536\u76ca<\/strong><\/h2>\n
          file_path = 'stock_data.csv'<\/p>\n
          result = calculate_monthly_average_return(file_path)<\/p>\n
          print(f"\u6708\u5747\u6536\u76ca: {result:.2%}")<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u901a\u8fc7\u4e0a\u8ff0\u65b9\u6cd5\uff0c\u53ef\u4ee5\u4f7f\u7528Python\u6709\u6548\u5730\u8ba1\u7b97\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u7684\u6708\u5747\u6536\u76ca\u3002\u8fd9\u4e0d\u4ec5\u9002\u7528\u4e8e\u80a1\u7968\u6570\u636e\uff0c\u8fd8\u53ef\u4ee5\u5e94\u7528\u4e8e\u5176\u4ed6\u7c7b\u578b\u7684\u91d1\u878d\u6570\u636e\u5206\u6790\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u8fd8\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u8fdb\u884c\u66f4\u591a\u7684\u81ea\u5b9a\u4e49\u5904\u7406\uff0c\u4f8b\u5982\u5bf9\u6570\u636e\u8fdb\u884c\u5f52\u4e00\u5316\u3001\u5bf9\u6536\u76ca\u7387\u8fdb\u884c\u66f4\u590d\u6742\u7684\u7edf\u8ba1\u5206\u6790\u7b49\u3002<\/p>\n<\/p>\n
          \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
           \u5982\u4f55\u4f7f\u7528Python\u8ba1\u7b97\u6295\u8d44\u7ec4\u5408\u7684\u6708\u5747\u6536\u76ca\u7387\uff1f<\/strong>
          \u8981\u8ba1\u7b97\u6295\u8d44\u7ec4\u5408\u7684\u6708\u5747\u6536\u76ca\u7387\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528pandas\u5e93\u6765\u5904\u7406\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u3002\u9996\u5148\uff0c\u6536\u96c6\u6bcf\u4e2a\u6708\u7684\u6536\u76ca\u6570\u636e\uff0c\u5c06\u5176\u8f6c\u6362\u4e3aDataFrame\u683c\u5f0f\u3002\u63a5\u4e0b\u6765\uff0c\u4f7f\u7528resample<\/code>\u65b9\u6cd5\u5c06\u6570\u636e\u6309\u6708\u6c47\u603b\uff0c\u5e76\u4f7f\u7528mean()<\/code>\u51fd\u6570\u8ba1\u7b97\u6bcf\u6708\u7684\u5e73\u5747\u6536\u76ca\u7387\u3002\u786e\u4fdd\u5c06\u6536\u76ca\u7387\u8f6c\u6362\u4e3a\u767e\u5206\u6bd4\u5f62\u5f0f\uff0c\u4ee5\u4fbf\u66f4\u6e05\u6670\u5730\u5c55\u793a\u7ed3\u679c\u3002<\/p>\n
          \u662f\u5426\u53ef\u4ee5\u901a\u8fc7Python\u81ea\u52a8\u83b7\u53d6\u80a1\u7968\u7684\u5386\u53f2\u6536\u76ca\u6570\u636e\uff1f<\/strong>
          \u662f\u7684\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528Python\u4e2d\u7684yfinance<\/code>\u5e93\u81ea\u52a8\u83b7\u53d6\u80a1\u7968\u7684\u5386\u53f2\u6536\u76ca\u6570\u636e\u3002\u8be5\u5e93\u5141\u8bb8\u60a8\u4eceYahoo Finance\u4e0b\u8f7d\u6240\u9700\u7684\u80a1\u7968\u6570\u636e\u3002\u60a8\u53ea\u9700\u5bfc\u5165\u5e93\u5e76\u4f7f\u7528download()<\/code>\u51fd\u6570\u8f93\u5165\u80a1\u7968\u4ee3\u7801\u548c\u65e5\u671f\u8303\u56f4\uff0c\u5373\u53ef\u83b7\u53d6\u76f8\u5e94\u7684\u5386\u53f2\u4ef7\u683c\u6570\u636e\uff0c\u5e76\u8fdb\u4e00\u6b65\u8ba1\u7b97\u6708\u5747\u6536\u76ca\u7387\u3002<\/p>\n
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