{"id":1016661,"date":"2024-12-27T12:18:28","date_gmt":"2024-12-27T04:18:28","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1016661.html"},"modified":"2024-12-27T12:18:31","modified_gmt":"2024-12-27T04:18:31","slug":"python%e5%a6%82%e4%bd%95%e8%b0%83%e7%94%a8csv%e6%96%87%e4%bb%b6","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1016661.html","title":{"rendered":"python\u5982\u4f55\u8c03\u7528csv\u6587\u4ef6"},"content":{"rendered":"

\"python\u5982\u4f55\u8c03\u7528csv\u6587\u4ef6\"<\/p>\n

Python\u8c03\u7528CSV\u6587\u4ef6\u7684\u65b9\u6cd5\u4e3b\u8981\u6709\uff1a\u4f7f\u7528\u5185\u7f6e\u7684csv\u6a21\u5757\u3001\u901a\u8fc7pandas\u5e93\u3001\u4f7f\u7528numpy\u5e93\u7b49\u3002<\/strong>\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5176\u4e2d\u4e00\u79cd\u65b9\u6cd5\uff1a\u901a\u8fc7pandas\u5e93\u8bfb\u53d6CSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n

\u4f7f\u7528pandas\u5e93\u8bfb\u53d6CSV\u6587\u4ef6\u662f\u4e00\u79cd\u9ad8\u6548\u4e14\u7b80\u4fbf\u7684\u65b9\u6cd5\uff0c\u5c24\u5176\u9002\u7528\u4e8e\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u96c6\u3002pandas\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u5bf9\u6570\u636e\u8fdb\u884c\u64cd\u4f5c\u548c\u5206\u6790\u3002\u9996\u5148\u9700\u8981\u5b89\u88c5pandas\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528\u547d\u4ee4pip install pandas<\/code>\u8fdb\u884c\u5b89\u88c5\u3002\u4f7f\u7528pandas\u8bfb\u53d6CSV\u6587\u4ef6\u7684\u57fa\u672c\u6b65\u9aa4\u662f\uff1a\u5bfc\u5165pandas\u5e93\u3001\u4f7f\u7528pd.read_csv()<\/code>\u51fd\u6570\u8bfb\u53d6CSV\u6587\u4ef6\u3001\u5bf9\u6570\u636e\u8fdb\u884c\u57fa\u672c\u64cd\u4f5c\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528pandas\u8bfb\u53d6\u548c\u64cd\u4f5cCSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n

\n

\u4e00\u3001\u4f7f\u7528PANDAS\u8bfb\u53d6CSV\u6587\u4ef6<\/h2>\n<\/p>\n

1. \u5b89\u88c5\u548c\u5bfc\u5165PANDAS\u5e93<\/h3>\n<\/p>\n

\u5728\u4f7f\u7528pandas\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u786e\u4fddpandas\u5e93\u5df2\u7ecf\u5b89\u88c5\u5728Python\u73af\u5883\u4e2d\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u5c31\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165pandas\u5e93\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u8bfb\u53d6CSV\u6587\u4ef6<\/h3>\n<\/p>\n
pandas\u63d0\u4f9b\u4e86read_csv()<\/code>\u51fd\u6570\u6765\u8bfb\u53d6CSV\u6587\u4ef6\u3002\u4f7f\u7528\u8fd9\u4e2a\u51fd\u6570\u53ef\u4ee5\u8f7b\u677e\u5730\u5c06CSV\u6587\u4ef6\u52a0\u8f7d\u5230\u4e00\u4e2aDataFrame\u4e2d\u3002DataFrame\u662fpandas\u4e2d\u7528\u4e8e\u5b58\u50a8\u548c\u64cd\u4f5c\u8868\u683c\u6570\u636e\u7684\u6570\u636e\u7ed3\u6784\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
df = pd.read_csv('example.csv')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0cexample.csv<\/code>\u662f\u8981\u8bfb\u53d6\u7684CSV\u6587\u4ef6\u7684\u6587\u4ef6\u540d\u3002read_csv()<\/code>\u51fd\u6570\u4f1a\u5c06CSV\u6587\u4ef6\u4e2d\u7684\u6570\u636e\u52a0\u8f7d\u5230\u4e00\u4e2aDataFrame\u5bf9\u8c61df<\/code>\u4e2d\u3002<\/p>\n<\/p>\n
3. \u68c0\u67e5\u6570\u636e<\/h3>\n<\/p>\n
\u52a0\u8f7d\u6570\u636e\u4e4b\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528DataFrame\u63d0\u4f9b\u7684\u65b9\u6cd5\u6765\u68c0\u67e5\u548c\u64cd\u4f5c\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u7528\u7684\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n
    \n
  • \u67e5\u770b\u6570\u636e\u7684\u524d\u51e0\u884c\uff1a<\/li>\n<\/ul>\n
    print(df.head())<\/p>\n
    <\/code><\/pre>\n<\/p>\n
      \n
    • \u67e5\u770b\u6570\u636e\u7684\u57fa\u672c\u4fe1\u606f\uff1a<\/li>\n<\/ul>\n
      print(df.info())<\/p>\n
      <\/code><\/pre>\n<\/p>\n
        \n
      • \u67e5\u770b\u6570\u636e\u7684\u7edf\u8ba1\u4fe1\u606f\uff1a<\/li>\n<\/ul>\n
        print(df.describe())<\/p>\n
        <\/code><\/pre>\n<\/p>\n
        \u8fd9\u4e9b\u65b9\u6cd5\u53ef\u4ee5\u5e2e\u52a9\u5feb\u901f\u4e86\u89e3\u6570\u636e\u7684\u7ed3\u6784\u548c\u57fa\u672c\u7edf\u8ba1\u4fe1\u606f\u3002<\/p>\n<\/p>\n
        \u4e8c\u3001PANDAS\u5904\u7406CSV\u6587\u4ef6\u7684\u9ad8\u7ea7\u64cd\u4f5c<\/h2>\n<\/p>\n
        1. \u9009\u62e9\u548c\u8fc7\u6ee4\u6570\u636e<\/h3>\n<\/p>\n
        \u4f7f\u7528pandas\u53ef\u4ee5\u8f7b\u677e\u5730\u9009\u62e9\u548c\u8fc7\u6ee4\u6570\u636e\u3002\u53ef\u4ee5\u4f7f\u7528\u5217\u540d\u6765\u9009\u62e9\u7279\u5b9a\u7684\u5217\uff0c\u4e5f\u53ef\u4ee5\u4f7f\u7528\u6761\u4ef6\u6765\u8fc7\u6ee4\u6570\u636e\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
          \n
        • \u9009\u62e9\u7279\u5b9a\u7684\u5217\uff1a<\/li>\n<\/ul>\n
          selected_columns = df[['Column1', 'Column2']]<\/p>\n
          <\/code><\/pre>\n<\/p>\n
            \n
          • \u6839\u636e\u6761\u4ef6\u8fc7\u6ee4\u6570\u636e\uff1a<\/li>\n<\/ul>\n
            filtered_data = df[df['Column1'] > 10]<\/p>\n
            <\/code><\/pre>\n<\/p>\n
            2. \u6570\u636e\u6e05\u6d17<\/h3>\n<\/p>\n
            \u5728\u5904\u7406CSV\u6587\u4ef6\u65f6\uff0c\u6570\u636e\u6e05\u6d17\u662f\u4e00\u4e2a\u5e38\u89c1\u7684\u4efb\u52a1\u3002pandas\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u6765\u6e05\u6d17\u6570\u636e\uff0c\u5305\u62ec\u5904\u7406\u7f3a\u5931\u503c\u3001\u5220\u9664\u91cd\u590d\u9879\u7b49\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
              \n
            • \u5904\u7406\u7f3a\u5931\u503c\uff1a<\/li>\n<\/ul>\n
              df.fillna(0, inplace=True)<\/p>\n
              <\/code><\/pre>\n<\/p>\n
                \n
              • \u5220\u9664\u91cd\u590d\u9879\uff1a<\/li>\n<\/ul>\n
                df.drop_duplicates(inplace=True)<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                3. \u6570\u636e\u805a\u5408<\/h3>\n<\/p>\n
                pandas\u652f\u6301\u5bf9\u6570\u636e\u8fdb\u884c\u805a\u5408\u64cd\u4f5c\uff0c\u4f8b\u5982\u8ba1\u7b97\u5e73\u5747\u503c\u3001\u6c42\u548c\u7b49\u3002\u53ef\u4ee5\u4f7f\u7528groupby()<\/code>\u65b9\u6cd5\u6765\u5b9e\u73b0\u6570\u636e\u7684\u5206\u7ec4\u548c\u805a\u5408\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
                grouped_data = df.groupby('Column1').sum()<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                4. \u6570\u636e\u53ef\u89c6\u5316<\/h3>\n<\/p>\n
                pandas\u4e0ematplotlib\u5e93\u7ed3\u5408\u4f7f\u7528\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u5bf9\u6570\u636e\u8fdb\u884c\u53ef\u89c6\u5316\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
                import matplotlib.pyplot as plt<\/p>\n
                df['Column1'].hist()<\/p>\n
                plt.show()<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                \u4e09\u3001\u4f7f\u7528CSV\u6a21\u5757\u8bfb\u53d6CSV\u6587\u4ef6<\/h2>\n<\/p>\n
                1. \u5bfc\u5165CSV\u6a21\u5757<\/h3>\n<\/p>\n
                Python\u7684\u6807\u51c6\u5e93\u4e2d\u5305\u542b\u4e86\u4e00\u4e2a\u540d\u4e3acsv\u7684\u6a21\u5757\uff0c\u53ef\u4ee5\u7528\u6765\u8bfb\u53d6\u548c\u5199\u5165CSV\u6587\u4ef6\u3002\u9996\u5148\u9700\u8981\u5bfc\u5165\u8fd9\u4e2a\u6a21\u5757\uff1a<\/p>\n<\/p>\n
                import csv<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                2. \u8bfb\u53d6CSV\u6587\u4ef6<\/h3>\n<\/p>\n
                \u4f7f\u7528csv\u6a21\u5757\u8bfb\u53d6CSV\u6587\u4ef6\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528csv.reader()\u51fd\u6570\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
                with open('example.csv', newline='') as csvfile:<\/p>\n
                    csvreader = csv.reader(csvfile)<\/p>\n
                    for row in csvreader:<\/p>\n
                        print(row)<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                \u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0cexample.csv<\/code>\u662f\u8981\u8bfb\u53d6\u7684CSV\u6587\u4ef6\u7684\u6587\u4ef6\u540d\u3002csv.reader()\u51fd\u6570\u4f1a\u8fd4\u56de\u4e00\u4e2a\u8fed\u4ee3\u5668\uff0c\u53ef\u4ee5\u9010\u884c\u8bfb\u53d6CSV\u6587\u4ef6\u4e2d\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
                3. \u8bfb\u53d6\u5e26\u6709\u6807\u9898\u7684CSV\u6587\u4ef6<\/h3>\n<\/p>\n
                \u5982\u679cCSV\u6587\u4ef6\u7684\u7b2c\u4e00\u884c\u5305\u542b\u6807\u9898\uff0c\u53ef\u4ee5\u4f7f\u7528csv.DictReader()<\/code>\u51fd\u6570\u8bfb\u53d6\u6587\u4ef6\u3002\u8fd9\u4e2a\u51fd\u6570\u4f1a\u5c06\u6bcf\u884c\u6570\u636e\u6620\u5c04\u4e3a\u4e00\u4e2a\u5b57\u5178\uff0c\u5176\u4e2d\u952e\u662f\u6807\u9898\uff0c\u503c\u662f\u5bf9\u5e94\u7684\u503c\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
                with open('example.csv', newline='') as csvfile:<\/p>\n
                    csvreader = csv.DictReader(csvfile)<\/p>\n
                    for row in csvreader:<\/p>\n
                        print(row['ColumnName'])<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                4. \u5199\u5165CSV\u6587\u4ef6<\/h3>\n<\/p>\n
                \u9664\u4e86\u8bfb\u53d6CSV\u6587\u4ef6\uff0ccsv\u6a21\u5757\u8fd8\u53ef\u4ee5\u7528\u4e8e\u5199\u5165CSV\u6587\u4ef6\u3002\u53ef\u4ee5\u4f7f\u7528csv.writer()<\/code>\u51fd\u6570\u6765\u5b9e\u73b0\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
                with open('output.csv', 'w', newline='') as csvfile:<\/p>\n
                    csvwriter = csv.writer(csvfile)<\/p>\n
                    csvwriter.writerow(['Column1', 'Column2'])<\/p>\n
                    csvwriter.writerow([1, 2])<\/p>\n
                    csvwriter.writerow([3, 4])<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                \u56db\u3001\u4f7f\u7528NUMPY\u8bfb\u53d6CSV\u6587\u4ef6<\/h2>\n<\/p>\n
                1. \u5b89\u88c5\u548c\u5bfc\u5165NUMPY\u5e93<\/h3>\n<\/p>\n
                Numpy\u662f\u4e00\u4e2a\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86\u652f\u6301\u5927\u578b\u591a\u7ef4\u6570\u7ec4\u548c\u77e9\u9635\u7684\u9ad8\u6548\u64cd\u4f5c\u3002\u5728\u4f7f\u7528numpy\u4e4b\u524d\uff0c\u9700\u8981\u786e\u4fdd\u5df2\u5b89\u88c5numpy\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
                pip install numpy<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                \u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u5bfc\u5165numpy\u5e93\uff1a<\/p>\n<\/p>\n
                import numpy as np<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                2. \u4f7f\u7528NUMPY\u8bfb\u53d6CSV\u6587\u4ef6<\/h3>\n<\/p>\n
                Numpy\u63d0\u4f9b\u4e86genfromtxt()<\/code>\u548cloadtxt()<\/code>\u4e24\u4e2a\u51fd\u6570\u6765\u8bfb\u53d6CSV\u6587\u4ef6\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
                data = np.genfromtxt('example.csv', delimiter=',', skip_header=1)<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                \u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0cexample.csv<\/code>\u662f\u8981\u8bfb\u53d6\u7684CSV\u6587\u4ef6\u540d\uff0cdelimiter=','<\/code>\u6307\u5b9a\u4e86CSV\u6587\u4ef6\u7684\u5206\u9694\u7b26\uff0cskip_header=1<\/code>\u8868\u793a\u8df3\u8fc7\u7b2c\u4e00\u884c\uff08\u901a\u5e38\u662f\u6807\u9898\u884c\uff09\u3002<\/p>\n<\/p>\n
                3. \u4f7f\u7528NUMPY\u5904\u7406\u6570\u636e<\/h3>\n<\/p>\n
                \u8bfb\u53d6\u6570\u636e\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528numpy\u63d0\u4f9b\u7684\u591a\u79cd\u51fd\u6570\u5bf9\u6570\u636e\u8fdb\u884c\u5904\u7406\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u8ba1\u7b97\u6570\u636e\u7684\u5e73\u5747\u503c\u3001\u6807\u51c6\u5dee\u7b49\uff1a<\/p>\n<\/p>\n
                mean_value = np.mean(data, axis=0)<\/p>\n
                std_deviation = np.std(data, axis=0)<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                \u4e94\u3001\u603b\u7ed3<\/h2>\n<\/p>\n
                Python\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u6765\u8bfb\u53d6\u548c\u5904\u7406CSV\u6587\u4ef6\uff0c\u5305\u62ec\u4f7f\u7528pandas\u3001csv\u6a21\u5757\u3001numpy\u5e93\u7b49\u3002\u5176\u4e2d\uff0cpandas\u5e93\u662f\u5904\u7406CSV\u6587\u4ef6\u7684\u5f3a\u5927\u5de5\u5177\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\uff0c\u53ef\u4ee5\u8f7b\u677e\u5b9e\u73b0\u6570\u636e\u7684\u8bfb\u53d6\u3001\u6e05\u6d17\u3001\u5206\u6790\u548c\u53ef\u89c6\u5316\u3002csv\u6a21\u5757\u662fPython\u6807\u51c6\u5e93\u7684\u4e00\u90e8\u5206\uff0c\u9002\u5408\u4e8e\u7b80\u5355\u7684CSV\u6587\u4ef6\u8bfb\u5199\u64cd\u4f5c\u3002numpy\u5e93\u5219\u9002\u7528\u4e8e\u9700\u8981\u9ad8\u6548\u5904\u7406\u6570\u503c\u6570\u636e\u7684\u573a\u666f\u3002\u5728\u9009\u62e9\u5177\u4f53\u65b9\u6cd5\u65f6\uff0c\u53ef\u4ee5\u6839\u636e\u6570\u636e\u89c4\u6a21\u548c\u5177\u4f53\u9700\u6c42\u8fdb\u884c\u9009\u62e9\u3002\u901a\u8fc7\u638c\u63e1\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5728Python\u4e2d\u8f7b\u677e\u5730\u5904\u7406\u548c\u5206\u6790CSV\u6587\u4ef6\u4e2d\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
                \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
                 \u5982\u4f55\u5728Python\u4e2d\u8bfb\u53d6CSV\u6587\u4ef6\uff1f<\/strong>
                \u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5185\u7f6e\u7684csv<\/code>\u6a21\u5757\u6765\u8bfb\u53d6CSV\u6587\u4ef6\u3002\u9996\u5148\uff0c\u60a8\u9700\u8981\u5bfc\u5165\u8be5\u6a21\u5757\uff0c\u7136\u540e\u4f7f\u7528csv.reader<\/code>\u6216csv.DictReader<\/code>\u6765\u8bfb\u53d6\u6587\u4ef6\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a  <\/p>\n
                import csv\n\nwith open('file.csv', mode='r', newline='') as file:\n    reader = csv.reader(file)\n    for row in reader:\n        print(row)\n<\/code><\/pre>\n
                \u8fd9\u79cd\u65b9\u6cd5\u4f1a\u5c06\u6bcf\u4e00\u884c\u4f5c\u4e3a\u4e00\u4e2a\u5217\u8868\u8f93\u51fa\uff0c\u9002\u7528\u4e8e\u6570\u636e\u91cf\u8f83\u5c0f\u7684\u60c5\u51b5\u3002<\/p>\n
                \u5982\u4f55\u5728Python\u4e2d\u5199\u5165CSV\u6587\u4ef6\uff1f<\/strong>
                \u5199\u5165CSV\u6587\u4ef6\u540c\u6837\u53ef\u4ee5\u4f7f\u7528csv<\/code>\u6a21\u5757\u3002\u4f7f\u7528csv.writer<\/code>\u53ef\u4ee5\u5c06\u6570\u636e\u5199\u5165\u65b0\u521b\u5efa\u7684CSV\u6587\u4ef6\u4e2d\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a  <\/p>\n
                import csv\n\ndata = [['Name', 'Age'], ['Alice', 30], ['Bob', 25]]\n\nwith open('output.csv', mode='w', newline='') as file:\n    writer = csv.writer(file)\n    writer.writerows(data)\n<\/code><\/pre>\n
                \u8fd9\u79cd\u65b9\u5f0f\u53ef\u4ee5\u5c06\u4e00\u4e2a\u4e8c\u7ef4\u5217\u8868\u5199\u5165CSV\u6587\u4ef6\uff0c\u9002\u5408\u9700\u8981\u6279\u91cf\u5199\u5165\u6570\u636e\u7684\u573a\u666f\u3002<\/p>\n
                \u4f7f\u7528Pandas\u5e93\u5904\u7406CSV\u6587\u4ef6\u6709\u54ea\u4e9b\u4f18\u52bf\uff1f<\/strong>
                Pandas\u5e93\u63d0\u4f9b\u4e86\u66f4\u52a0\u5f3a\u5927\u548c\u7075\u6d3b\u7684\u6570\u636e\u5904\u7406\u529f\u80fd\u3002\u901a\u8fc7pandas.read_csv()<\/code>\u53ef\u4ee5\u8f7b\u677e\u8bfb\u53d6CSV\u6587\u4ef6\uff0c\u5e76\u5c06\u5176\u8f6c\u6362\u4e3aDataFrame\u683c\u5f0f\uff0c\u65b9\u4fbf\u540e\u7eed\u7684\u6570\u636e\u5206\u6790\u4e0e\u5904\u7406\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a  <\/p>\n
                import pandas as pd\n\ndf = pd.read_csv('file.csv')\nprint(df.head())\n<\/code><\/pre>\n
                \u8fd9\u79cd\u65b9\u6cd5\u4e0d\u4ec5\u80fd\u81ea\u52a8\u5904\u7406\u7f3a\u5931\u503c\uff0c\u8fd8\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u7b5b\u9009\u3001\u6392\u5e8f\u548c\u7edf\u8ba1\u5206\u6790\uff0c\u7279\u522b\u9002\u5408\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u8c03\u7528CSV\u6587\u4ef6\u7684\u65b9\u6cd5\u4e3b\u8981\u6709\uff1a\u4f7f\u7528\u5185\u7f6e\u7684csv\u6a21\u5757\u3001\u901a\u8fc7pandas\u5e93\u3001\u4f7f\u7528numpy\u5e93\u7b49\u3002\u4e0b\u9762\u5c06\u8be6 […]","protected":false},"author":3,"featured_media":1016673,"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\/1016661"}],"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=1016661"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1016661\/revisions"}],"predecessor-version":[{"id":1016677,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1016661\/revisions\/1016677"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1016673"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1016661"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1016661"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1016661"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}