{"id":1130487,"date":"2025-01-08T20:40:33","date_gmt":"2025-01-08T12:40:33","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1130487.html"},"modified":"2025-01-08T20:40:36","modified_gmt":"2025-01-08T12:40:36","slug":"python%e5%a6%82%e4%bd%95%e6%88%aa%e5%8f%96%e4%b8%80%e5%88%97%e6%95%b0%e6%8d%ae%e7%9a%84%e5%89%8d%e5%87%a0%e4%bd%8d","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1130487.html","title":{"rendered":"python\u5982\u4f55\u622a\u53d6\u4e00\u5217\u6570\u636e\u7684\u524d\u51e0\u4f4d"},"content":{"rendered":"

\"python\u5982\u4f55\u622a\u53d6\u4e00\u5217\u6570\u636e\u7684\u524d\u51e0\u4f4d\"<\/p>\n

PYTHON\u5982\u4f55\u622a\u53d6\u4e00\u5217\u6570\u636e\u7684\u524d\u51e0\u4f4d<\/h3>\n<\/p>\n

\u5728Python\u4e2d\uff0c\u622a\u53d6\u4e00\u5217\u6570\u636e\u7684\u524d\u51e0\u4f4d\u53ef\u4ee5\u4f7f\u7528\u5404\u79cd\u65b9\u6cd5\uff0c\u5982\u5217\u8868\u5207\u7247\u3001pandas\u5e93\u4e2d\u7684iloc\u65b9\u6cd5\u3001numpy\u5e93\u4e2d\u7684\u5207\u7247\u65b9\u6cd5<\/strong>\u3002\u672c\u6587\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u5e76\u9010\u4e00\u5c55\u5f00\u8ba8\u8bba\u5b83\u4eec\u7684\u4f18\u7f3a\u70b9\u548c\u5177\u4f53\u5b9e\u73b0\u3002<\/p>\n<\/p>\n

\u5217\u8868\u5207\u7247<\/h4>\n<\/p>\n

\u5217\u8868\u5207\u7247\u662fPython\u4e2d\u6700\u57fa\u672c\u548c\u5e38\u7528\u7684\u6570\u636e\u622a\u53d6\u65b9\u6cd5\u4e4b\u4e00\u3002\u5217\u8868\u5207\u7247\u64cd\u4f5c\u975e\u5e38\u7b80\u5355\uff0c\u5e76\u4e14\u9002\u7528\u4e8e\u6240\u6709\u5e8f\u5217\u7c7b\u578b\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n

# \u793a\u4f8b\u4ee3\u7801<\/p>\n
data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]<\/p>\n
\u622a\u53d6\u524d5\u4f4d<\/strong><\/h2>\n
subset_data = data[:5]<\/p>\n
print(subset_data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f18\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n
    \n
  • \u7b80\u5355\u6613\u7528<\/li>\n
  • \u9002\u5408\u5c0f\u89c4\u6a21\u6570\u636e<\/li>\n<\/ul>\n
    \u7f3a\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n
      \n
    • \u5bf9\u4e8e\u5927\u578b\u6570\u636e\u96c6\uff0c\u6548\u7387\u8f83\u4f4e<\/li>\n
    • \u4e0d\u9002\u5408\u5904\u7406\u590d\u6742\u7684\u6570\u636e\u7c7b\u578b<\/li>\n<\/ul>\n
      Pandas\u5e93\u4e2d\u7684iloc\u65b9\u6cd5<\/h4>\n<\/p>\n
      Pandas\u662fPython\u4e2d\u5904\u7406\u6570\u636e\u5206\u6790\u7684\u5f3a\u5927\u5e93\uff0c\u5176iloc\u65b9\u6cd5\u53ef\u4ee5\u975e\u5e38\u65b9\u4fbf\u5730\u622a\u53d6DataFrame\u6216Series\u4e2d\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
      import pandas as pd<\/p>\n
      \u793a\u4f8b\u4ee3\u7801<\/strong><\/h2>\n
      data = pd.Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])<\/p>\n
      \u622a\u53d6\u524d5\u4f4d<\/strong><\/h2>\n
      subset_data = data.iloc[:5]<\/p>\n
      print(subset_data)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u4f18\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n
        \n
      • \u9002\u7528\u4e8e\u5927\u89c4\u6a21\u6570\u636e<\/li>\n
      • \u652f\u6301\u591a\u79cd\u6570\u636e\u64cd\u4f5c<\/li>\n<\/ul>\n
        \u7f3a\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n
          \n
        • \u9700\u8981\u52a0\u8f7d\u989d\u5916\u7684\u5e93<\/li>\n
        • \u5b66\u4e60\u66f2\u7ebf\u76f8\u5bf9\u8f83\u9ad8<\/li>\n<\/ul>\n
          Numpy\u5e93\u4e2d\u7684\u5207\u7247\u65b9\u6cd5<\/h4>\n<\/p>\n
          Numpy\u662fPython\u4e2d\u5904\u7406\u6570\u503c\u8ba1\u7b97\u7684\u57fa\u7840\u5e93\uff0c\u5176\u5207\u7247\u65b9\u6cd5\u53ef\u4ee5\u975e\u5e38\u9ad8\u6548\u5730\u622a\u53d6\u6570\u7ec4\u4e2d\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
          import numpy as np<\/p>\n
          \u793a\u4f8b\u4ee3\u7801<\/strong><\/h2>\n
          data = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])<\/p>\n
          \u622a\u53d6\u524d5\u4f4d<\/strong><\/h2>\n
          subset_data = data[:5]<\/p>\n
          print(subset_data)<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u4f18\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n
            \n
          • \u9ad8\u6548<\/li>\n
          • \u652f\u6301\u5927\u89c4\u6a21\u6570\u503c\u8ba1\u7b97<\/li>\n<\/ul>\n
            \u7f3a\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n
              \n
            • \u9700\u8981\u52a0\u8f7d\u989d\u5916\u7684\u5e93<\/li>\n
            • \u4ec5\u9002\u7528\u4e8e\u6570\u503c\u6570\u636e<\/li>\n<\/ul>\n
              \u4e00\u3001\u5217\u8868\u5207\u7247\u7684\u8be6\u7ec6\u4ecb\u7ecd<\/h3>\n<\/p>\n
              \u5217\u8868\u5207\u7247\u662fPython\u4e2d\u975e\u5e38\u57fa\u7840\u4f46\u5374\u529f\u80fd\u5f3a\u5927\u7684\u64cd\u4f5c\u3002\u901a\u8fc7\u5217\u8868\u5207\u7247\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u83b7\u53d6\u5217\u8868\u4e2d\u7684\u4efb\u610f\u5b50\u96c6\u3002\u5207\u7247\u7684\u8bed\u6cd5\u4e3alist[start:stop:step]<\/code>\uff0c\u5176\u4e2dstart<\/code>\u662f\u8d77\u59cb\u7d22\u5f15\uff0cstop<\/code>\u662f\u7ed3\u675f\u7d22\u5f15\uff0cstep<\/code>\u662f\u6b65\u957f\u3002<\/p>\n<\/p>\n
              \u57fa\u672c\u7528\u6cd5<\/h4>\n<\/p>\n
              \u5217\u8868\u5207\u7247\u7684\u57fa\u672c\u7528\u6cd5\u975e\u5e38\u7b80\u5355\uff0c\u6211\u4eec\u53ea\u9700\u8981\u6307\u5b9a\u8d77\u59cb\u548c\u7ed3\u675f\u7d22\u5f15\u5373\u53ef\u3002<\/p>\n<\/p>\n
              data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]<\/p>\n
              \u622a\u53d6\u524d5\u4f4d<\/strong><\/h2>\n
              subset_data = data[:5]<\/p>\n
              print(subset_data)  # \u8f93\u51fa [1, 2, 3, 4, 5]<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u590d\u6742\u7528\u6cd5<\/h4>\n<\/p>\n
              \u6211\u4eec\u8fd8\u53ef\u4ee5\u901a\u8fc7\u6307\u5b9a\u6b65\u957f\u6765\u5b9e\u73b0\u66f4\u590d\u6742\u7684\u5207\u7247\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
              # \u6bcf\u9694\u4e00\u4e2a\u5143\u7d20\u622a\u53d6<\/p>\n
              subset_data = data[:5:2]<\/p>\n
              print(subset_data)  # \u8f93\u51fa [1, 3, 5]<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u6211\u4eec\u53ef\u4ee5\u975e\u5e38\u7075\u6d3b\u5730\u83b7\u53d6\u5217\u8868\u4e2d\u7684\u4efb\u610f\u5b50\u96c6\u3002<\/p>\n<\/p>\n
              \u6027\u80fd\u8003\u8651<\/h4>\n<\/p>\n
              \u867d\u7136\u5217\u8868\u5207\u7247\u975e\u5e38\u65b9\u4fbf\uff0c\u4f46\u5bf9\u4e8e\u975e\u5e38\u5927\u7684\u5217\u8868\uff0c\u5176\u6027\u80fd\u53ef\u80fd\u4e0d\u591f\u7406\u60f3\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u53ef\u80fd\u9700\u8981\u8003\u8651\u4f7f\u7528\u66f4\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\u6216\u7b97\u6cd5\u3002<\/p>\n<\/p>\n
              \u4e8c\u3001Pandas\u5e93\u4e2d\u7684iloc\u65b9\u6cd5<\/h3>\n<\/p>\n
              Pandas\u5e93\u662f\u6570\u636e\u79d1\u5b66\u548c\u6570\u636e\u5206\u6790\u9886\u57df\u4e2d\u6700\u5e38\u7528\u7684\u5de5\u5177\u4e4b\u4e00\u3002\u5176iloc\u65b9\u6cd5\u63d0\u4f9b\u4e86\u975e\u5e38\u5f3a\u5927\u7684\u6570\u636e\u622a\u53d6\u529f\u80fd\u3002<\/p>\n<\/p>\n
              \u57fa\u672c\u7528\u6cd5<\/h4>\n<\/p>\n
              Pandas\u7684iloc\u65b9\u6cd5\u53ef\u4ee5\u7528\u4e8eDataFrame\u548cSeries\uff0c\u4e0b\u9762\u662f\u4e00\u4e9b\u57fa\u672c\u7684\u7528\u6cd5\u3002<\/p>\n<\/p>\n
              import pandas as pd<\/p>\n
              \u793a\u4f8b\u4ee3\u7801<\/strong><\/h2>\n
              data = pd.Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])<\/p>\n
              \u622a\u53d6\u524d5\u4f4d<\/strong><\/h2>\n
              subset_data = data.iloc[:5]<\/p>\n
              print(subset_data)<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u9ad8\u7ea7\u7528\u6cd5<\/h4>\n<\/p>\n
              \u9664\u4e86\u57fa\u672c\u7684\u5207\u7247\u64cd\u4f5c\uff0ciloc\u8fd8\u652f\u6301\u591a\u79cd\u590d\u6742\u7684\u7d22\u5f15\u65b9\u5f0f\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u5e03\u5c14\u7d22\u5f15\u6765\u7b5b\u9009\u6570\u636e\u3002<\/p>\n<\/p>\n
              # \u793a\u4f8b\u4ee3\u7801<\/p>\n
              data = pd.Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])<\/p>\n
              \u622a\u53d6\u503c\u5927\u4e8e3\u7684\u524d5\u4f4d<\/strong><\/h2>\n
              subset_data = data[data > 3].iloc[:5]<\/p>\n
              print(subset_data)<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u8fd9\u79cd\u65b9\u6cd5\u975e\u5e38\u7075\u6d3b\uff0c\u9002\u7528\u4e8e\u5404\u79cd\u590d\u6742\u7684\u6570\u636e\u5206\u6790\u4efb\u52a1\u3002<\/p>\n<\/p>\n
              \u6027\u80fd\u8003\u8651<\/h4>\n<\/p>\n
              Pandas\u5e93\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u65f6\u8868\u73b0\u975e\u5e38\u51fa\u8272\uff0c\u5176\u5e95\u5c42\u5b9e\u73b0\u57fa\u4e8e\u9ad8\u6548\u7684\u6570\u503c\u8ba1\u7b97\u5e93\uff08\u5982NumPy\uff09\u3002\u56e0\u6b64\uff0c\u5bf9\u4e8e\u5927\u89c4\u6a21\u6570\u636e\u5206\u6790\u4efb\u52a1\uff0cPandas\u662f\u4e00\u4e2a\u975e\u5e38\u597d\u7684\u9009\u62e9\u3002<\/p>\n<\/p>\n
              \u4e09\u3001Numpy\u5e93\u4e2d\u7684\u5207\u7247\u65b9\u6cd5<\/h3>\n<\/p>\n
              Numpy\u5e93\u662fPython\u4e2d\u5904\u7406\u6570\u503c\u8ba1\u7b97\u7684\u57fa\u7840\u5e93\uff0c\u5176\u5207\u7247\u65b9\u6cd5\u975e\u5e38\u9ad8\u6548\uff0c\u9002\u7528\u4e8e\u5927\u89c4\u6a21\u6570\u503c\u8ba1\u7b97\u3002<\/p>\n<\/p>\n
              \u57fa\u672c\u7528\u6cd5<\/h4>\n<\/p>\n
              Numpy\u7684\u5207\u7247\u64cd\u4f5c\u4e0ePython\u7684\u5217\u8868\u5207\u7247\u975e\u5e38\u76f8\u4f3c\uff0c\u4f46\u5728\u6027\u80fd\u4e0a\u6709\u663e\u8457\u7684\u63d0\u5347\u3002<\/p>\n<\/p>\n
              import numpy as np<\/p>\n
              \u793a\u4f8b\u4ee3\u7801<\/strong><\/h2>\n
              data = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])<\/p>\n
              \u622a\u53d6\u524d5\u4f4d<\/strong><\/h2>\n
              subset_data = data[:5]<\/p>\n
              print(subset_data)<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u9ad8\u7ea7\u7528\u6cd5<\/h4>\n<\/p>\n
              Numpy\u8fd8\u652f\u6301\u591a\u7ef4\u6570\u7ec4\u7684\u5207\u7247\u64cd\u4f5c\uff0c\u8fd9\u4f7f\u5f97\u5176\u5728\u6570\u503c\u8ba1\u7b97\u548c\u79d1\u5b66\u8ba1\u7b97\u4e2d\u975e\u5e38\u5f3a\u5927\u3002<\/p>\n<\/p>\n
              # \u793a\u4f8b\u4ee3\u7801<\/p>\n
              data = np.arange(20).reshape(4, 5)<\/p>\n
              \u622a\u53d6\u524d\u4e24\u884c\u7684\u524d\u4e24\u5217<\/strong><\/h2>\n
              subset_data = data[:2, :2]<\/p>\n
              print(subset_data)<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u6211\u4eec\u53ef\u4ee5\u975e\u5e38\u7075\u6d3b\u5730\u5904\u7406\u591a\u7ef4\u6570\u7ec4\u3002<\/p>\n<\/p>\n
              \u6027\u80fd\u8003\u8651<\/h4>\n<\/p>\n
              Numpy\u5e93\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u503c\u8ba1\u7b97\u65f6\u8868\u73b0\u975e\u5e38\u51fa\u8272\uff0c\u5176\u5e95\u5c42\u5b9e\u73b0\u57fa\u4e8e\u9ad8\u6548\u7684C\u8bed\u8a00\u4ee3\u7801\u3002\u56e0\u6b64\uff0c\u5bf9\u4e8e\u9700\u8981\u8fdb\u884c\u5927\u91cf\u6570\u503c\u8ba1\u7b97\u7684\u4efb\u52a1\uff0cNumpy\u662f\u4e00\u4e2a\u975e\u5e38\u597d\u7684\u9009\u62e9\u3002<\/p>\n<\/p>\n
              \u56db\u3001\u5176\u4ed6\u622a\u53d6\u6570\u636e\u7684\u65b9\u6cd5<\/h3>\n<\/p>\n
              \u9664\u4e86\u4e0a\u8ff0\u4ecb\u7ecd\u7684\u65b9\u6cd5\uff0cPython\u4e2d\u8fd8\u6709\u5176\u4ed6\u4e00\u4e9b\u622a\u53d6\u6570\u636e\u7684\u65b9\u6cd5\uff0c\u5982itertools\u5e93\u4e2d\u7684islice\u51fd\u6570\u7b49\u3002<\/p>\n<\/p>\n
              itertools\u5e93\u4e2d\u7684islice\u51fd\u6570<\/h4>\n<\/p>\n
              itertools\u5e93\u63d0\u4f9b\u4e86\u4e00\u7cfb\u5217\u9ad8\u6548\u7684\u8fed\u4ee3\u5668\u5de5\u5177\uff0c\u5176\u4e2d\u7684islice\u51fd\u6570\u53ef\u4ee5\u7528\u4e8e\u622a\u53d6\u8fed\u4ee3\u5668\u4e2d\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
              import itertools<\/p>\n
              \u793a\u4f8b\u4ee3\u7801<\/strong><\/h2>\n
              data = iter([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])<\/p>\n
              \u622a\u53d6\u524d5\u4f4d<\/strong><\/h2>\n
              subset_data = list(itertools.islice(data, 5))<\/p>\n
              print(subset_data)<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u8fd9\u79cd\u65b9\u6cd5\u975e\u5e38\u9ad8\u6548\uff0c\u9002\u7528\u4e8e\u9700\u8981\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u6d41\u7684\u573a\u666f\u3002<\/p>\n<\/p>\n
              \u6027\u80fd\u8003\u8651<\/h4>\n<\/p>\n
              itertools\u5e93\u4e2d\u7684islice\u51fd\u6570\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u6d41\u65f6\u8868\u73b0\u975e\u5e38\u51fa\u8272\uff0c\u5176\u5e95\u5c42\u5b9e\u73b0\u57fa\u4e8e\u9ad8\u6548\u7684\u8fed\u4ee3\u5668\u3002\u56e0\u6b64\uff0c\u5bf9\u4e8e\u9700\u8981\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u6d41\u7684\u4efb\u52a1\uff0citertools\u5e93\u662f\u4e00\u4e2a\u975e\u5e38\u597d\u7684\u9009\u62e9\u3002<\/p>\n<\/p>\n
              \u4e94\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
              \u672c\u6587\u8be6\u7ec6\u4ecb\u7ecd\u4e86Python\u4e2d\u622a\u53d6\u4e00\u5217\u6570\u636e\u7684\u524d\u51e0\u4f4d\u7684\u591a\u79cd\u65b9\u6cd5<\/strong>\uff0c\u5305\u62ec\u5217\u8868\u5207\u7247\u3001Pandas\u5e93\u4e2d\u7684iloc\u65b9\u6cd5\u3001Numpy\u5e93\u4e2d\u7684\u5207\u7247\u65b9\u6cd5\u7b49\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u4f18\u7f3a\u70b9\u548c\u9002\u7528\u573a\u666f\u3002<\/p>\n<\/p>\n
                \n
              • \u5217\u8868\u5207\u7247<\/strong>\uff1a\u7b80\u5355\u6613\u7528\uff0c\u9002\u5408\u5c0f\u89c4\u6a21\u6570\u636e<\/li>\n
              • Pandas\u5e93\u4e2d\u7684iloc\u65b9\u6cd5<\/strong>\uff1a\u9002\u7528\u4e8e\u5927\u89c4\u6a21\u6570\u636e\uff0c\u652f\u6301\u591a\u79cd\u6570\u636e\u64cd\u4f5c<\/li>\n
              • Numpy\u5e93\u4e2d\u7684\u5207\u7247\u65b9\u6cd5<\/strong>\uff1a\u9ad8\u6548\uff0c\u9002\u7528\u4e8e\u5927\u89c4\u6a21\u6570\u503c\u8ba1\u7b97<\/li>\n
              • itertools\u5e93\u4e2d\u7684islice\u51fd\u6570<\/strong>\uff1a\u9ad8\u6548\uff0c\u9002\u7528\u4e8e\u5927\u89c4\u6a21\u6570\u636e\u6d41<\/li>\n<\/ul>\n
                \u5e0c\u671b\u672c\u6587\u80fd\u4e3a\u4f60\u5728\u5904\u7406\u6570\u636e\u622a\u53d6\u4efb\u52a1\u65f6\u63d0\u4f9b\u6709\u4ef7\u503c\u7684\u53c2\u8003\u3002\u6839\u636e\u5177\u4f53\u7684\u9700\u6c42\u548c\u6570\u636e\u89c4\u6a21\uff0c\u9009\u62e9\u6700\u5408\u9002\u7684\u65b9\u6cd5\u8fdb\u884c\u6570\u636e\u622a\u53d6\uff0c\u4ece\u800c\u63d0\u9ad8\u5de5\u4f5c\u6548\u7387\u3002<\/p>\n<\/p>\n
                \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
                 \u5982\u4f55\u5728Python\u4e2d\u622a\u53d6\u5b57\u7b26\u4e32\u7684\u524d\u51e0\u4f4d\uff1f<\/strong>
                \u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5207\u7247\u64cd\u4f5c\u6765\u622a\u53d6\u5b57\u7b26\u4e32\u7684\u524d\u51e0\u4f4d\u3002\u5047\u8bbe\u6709\u4e00\u4e2a\u5b57\u7b26\u4e32\u53d8\u91cfmy_string<\/code>\uff0c\u4f60\u53ef\u4ee5\u901a\u8fc7my_string[:n]<\/code>\u6765\u83b7\u53d6\u524dn\u4e2a\u5b57\u7b26\u3002\u4f8b\u5982\uff0cmy_string[:5]<\/code>\u5c06\u8fd4\u56de\u5b57\u7b26\u4e32\u7684\u524d5\u4e2a\u5b57\u7b26\u3002<\/p>\n
                \u5982\u4f55\u5229\u7528pandas\u622a\u53d6DataFrame\u4e2d\u7279\u5b9a\u5217\u7684\u524d\u51e0\u4f4d\uff1f<\/strong>
                \u5982\u679c\u4f60\u4f7f\u7528pandas\u5e93\u5904\u7406\u6570\u636e\uff0c\u53ef\u4ee5\u901a\u8fc7DataFrame<\/code>\u5bf9\u8c61\u7684apply<\/code>\u65b9\u6cd5\u6765\u622a\u53d6\u7279\u5b9a\u5217\u7684\u524d\u51e0\u4f4d\u3002\u5047\u8bbe\u4f60\u7684DataFrame\u540d\u4e3adf<\/code>\uff0c\u800c\u4f60\u60f3\u622a\u53d6\u5217'column_name'<\/code>\u7684\u524dn\u4e2a\u5b57\u7b26\uff0c\u53ef\u4ee5\u8fd9\u6837\u5199\uff1adf['column_name'] = df['column_name'].apply(lambda x: x[:n])<\/code>\u3002<\/p>\n
                \u5728\u622a\u53d6\u6570\u636e\u65f6\uff0c\u5982\u4f55\u5904\u7406\u7a7a\u503c\u6216\u7f3a\u5931\u503c\uff1f<\/strong>
                \u5728\u5904\u7406\u6570\u636e\u65f6\uff0c\u7a7a\u503c\u6216\u7f3a\u5931\u503c\u53ef\u80fd\u4f1a\u5bfc\u81f4\u9519\u8bef\u3002\u53ef\u4ee5\u5728\u622a\u53d6\u4e4b\u524d\u4f7f\u7528fillna()<\/code>\u65b9\u6cd5\u586b\u5145\u7f3a\u5931\u503c\uff0c\u6216\u8005\u5728apply<\/code>\u51fd\u6570\u4e2d\u52a0\u5165\u6761\u4ef6\u5224\u65ad\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528df['column_name'].apply(lambda x: x[:n] if pd.notnull(x) else '')<\/code>\uff0c\u8fd9\u6837\u5c31\u80fd\u786e\u4fdd\u5728\u9047\u5230\u7a7a\u503c\u65f6\u4e0d\u4f1a\u51fa\u9519\uff0c\u5e76\u53ef\u4ee5\u8fd4\u56de\u4e00\u4e2a\u9ed8\u8ba4\u503c\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"PYTHON\u5982\u4f55\u622a\u53d6\u4e00\u5217\u6570\u636e\u7684\u524d\u51e0\u4f4d \u5728Python\u4e2d\uff0c\u622a\u53d6\u4e00\u5217\u6570\u636e\u7684\u524d\u51e0\u4f4d\u53ef\u4ee5\u4f7f\u7528\u5404\u79cd\u65b9\u6cd5\uff0c\u5982\u5217\u8868\u5207\u7247\u3001pa […]","protected":false},"author":3,"featured_media":1130500,"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\/1130487"}],"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=1130487"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1130487\/revisions"}],"predecessor-version":[{"id":1130503,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1130487\/revisions\/1130503"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1130500"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1130487"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1130487"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1130487"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}