{"id":1045976,"date":"2024-12-31T13:28:59","date_gmt":"2024-12-31T05:28:59","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1045976.html"},"modified":"2024-12-31T13:29:05","modified_gmt":"2024-12-31T05:29:05","slug":"python%e5%a6%82%e4%bd%95%e5%b0%86%e7%bb%93%e6%9e%9c%e4%bf%9d%e5%ad%98%e5%88%b0csv","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1045976.html","title":{"rendered":"python\u5982\u4f55\u5c06\u7ed3\u679c\u4fdd\u5b58\u5230csv"},"content":{"rendered":"

\"python\u5982\u4f55\u5c06\u7ed3\u679c\u4fdd\u5b58\u5230csv\"<\/p>\n

\u5728Python\u4e2d\uff0c\u5c06\u7ed3\u679c\u4fdd\u5b58\u5230CSV\u6587\u4ef6\u6709\u51e0\u4e2a\u5173\u952e\u6b65\u9aa4\uff0c\u5305\u62ec\u4f7f\u7528\u9002\u5f53\u7684\u5e93\u3001\u521b\u5efa\u6570\u636e\u7ed3\u6784\u3001\u7f16\u5199\u5230CSV\u6587\u4ef6\u4e2d\u7b49\u3002<\/strong>\u53ef\u4ee5\u4f7f\u7528 pandas<\/code> \u5e93\u3001csv<\/code> \u6a21\u5757\u3001numpy<\/code> \u5e93\u7b49\u65b9\u6cd5\u6765\u5b9e\u73b0\u3002\u672c\u6587\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u65b9\u6cd5\u5c06\u6570\u636e\u4fdd\u5b58\u5230CSV\u6587\u4ef6\u4e2d\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528pandas\u5e93<\/h3>\n<\/p>\n

Pandas\u662f\u4e00\u4e2a\u975e\u5e38\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5e93\uff0c\u80fd\u591f\u65b9\u4fbf\u5730\u5904\u7406\u6570\u636e\u5e76\u5bfc\u51fa\u5230CSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n

1\u3001\u5b89\u88c5pandas<\/h4>\n<\/p>\n

\u5982\u679c\u4f60\u8fd8\u6ca1\u6709\u5b89\u88c5pandas\uff0c\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
2\u3001\u521b\u5efaDataFrame\u5e76\u4fdd\u5b58\u4e3aCSV<\/h4>\n<\/p>\n
Pandas\u4e2d\u7684DataFrame\u662f\u4e00\u4e2a\u4e8c\u7ef4\u7684\u8868\u683c\u6570\u636e\u7ed3\u6784\uff0c\u53ef\u4ee5\u5f88\u65b9\u4fbf\u5730\u5c06\u5176\u5bfc\u51fa\u4e3aCSV\u6587\u4ef6\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u521b\u5efa\u6570\u636e<\/strong><\/h2>\n
data = {<\/p>\n
    'Name': ['John', 'Anna', 'Peter', 'Linda'],<\/p>\n
    'Age': [28, 24, 35, 32],<\/p>\n
    'City': ['New York', 'Paris', 'Berlin', 'London']<\/p>\n
}<\/p>\n
\u521b\u5efaDataFrame<\/strong><\/h2>\n
df = pd.DataFrame(data)<\/p>\n
\u4fdd\u5b58\u5230CSV\u6587\u4ef6<\/strong><\/h2>\n
df.to_csv('output.csv', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u5bfc\u5165\u4e86pandas\u5e93\uff0c\u7136\u540e\u521b\u5efa\u4e86\u4e00\u4e2a\u5305\u542b\u540d\u5b57\u3001\u5e74\u9f84\u548c\u57ce\u5e02\u7684\u6570\u636e\u5b57\u5178\u3002\u63a5\u7740\uff0c\u6211\u4eec\u4f7f\u7528\u8fd9\u4e2a\u6570\u636e\u5b57\u5178\u521b\u5efa\u4e86\u4e00\u4e2aDataFrame\uff0c\u6700\u540e\u4f7f\u7528to_csv<\/code>\u65b9\u6cd5\u5c06DataFrame\u4fdd\u5b58\u4e3aCSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n
3\u3001\u5e38\u89c1\u53c2\u6570\u4ecb\u7ecd<\/h4>\n<\/p>\n
to_csv<\/code>\u65b9\u6cd5\u6709\u8bb8\u591a\u53c2\u6570\uff0c\u53ef\u4ee5\u6839\u636e\u9700\u8981\u8fdb\u884c\u8c03\u6574\uff1a<\/p>\n<\/p>\n
    \n
  • path_or_buf<\/code>\uff1a\u6587\u4ef6\u8def\u5f84\u6216\u5bf9\u8c61\uff0c\u9ed8\u8ba4\u4e3aNone\u3002<\/li>\n
  • sep<\/code>\uff1a\u5b57\u6bb5\u5206\u9694\u7b26\uff0c\u9ed8\u8ba4\u4e3a\u9017\u53f7\uff08,<\/code>\uff09\u3002<\/li>\n
  • na_rep<\/code>\uff1a\u7f3a\u5931\u503c\u8868\u793a\uff0c\u9ed8\u8ba4\u4e3a\u7a7a\u5b57\u7b26\u4e32\u3002<\/li>\n
  • columns<\/code>\uff1a\u8981\u5199\u5165\u7684\u5217\u6807\u7b7e\u5e8f\u5217\uff0c\u9ed8\u8ba4\u4e3aNone\u3002<\/li>\n
  • index<\/code>\uff1a\u662f\u5426\u5199\u5165\u884c\u7d22\u5f15\uff0c\u9ed8\u8ba4\u4e3aTrue\u3002<\/li>\n<\/ul>\n
    \u4f8b\u5982\uff0c\u5982\u679c\u4f60\u60f3\u6307\u5b9a\u5206\u9694\u7b26\u4e3a\u5206\u53f7\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
    df.to_csv('output.csv', sep=';', index=False)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e8c\u3001\u4f7f\u7528csv\u6a21\u5757<\/h3>\n<\/p>\n
    Python\u5185\u7f6e\u7684csv\u6a21\u5757\u4e5f\u53ef\u4ee5\u7528\u4e8e\u5c06\u6570\u636e\u4fdd\u5b58\u5230CSV\u6587\u4ef6\u4e2d\u3002<\/p>\n<\/p>\n
    1\u3001\u7f16\u5199\u5230CSV\u6587\u4ef6<\/h4>\n<\/p>\n
    \u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u5c55\u793a\u4e86\u5982\u4f55\u4f7f\u7528csv\u6a21\u5757\u5c06\u6570\u636e\u5199\u5165CSV\u6587\u4ef6\uff1a<\/p>\n<\/p>\n
    import csv<\/p>\n
    \u6570\u636e<\/strong><\/h2>\n
    data = [<\/p>\n
        ['Name', 'Age', 'City'],<\/p>\n
        ['John', 28, 'New York'],<\/p>\n
        ['Anna', 24, 'Paris'],<\/p>\n
        ['Peter', 35, 'Berlin'],<\/p>\n
        ['Linda', 32, 'London']<\/p>\n
    ]<\/p>\n
    \u4fdd\u5b58\u5230CSV\u6587\u4ef6<\/strong><\/h2>\n
    with open('output.csv', mode='w', newline='') as file:<\/p>\n
        writer = csv.writer(file)<\/p>\n
        writer.writerows(data)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u5bfc\u5165\u4e86csv\u6a21\u5757\uff0c\u7136\u540e\u5b9a\u4e49\u4e86\u4e00\u4e2a\u5305\u542b\u6570\u636e\u7684\u5217\u8868\u3002\u63a5\u7740\uff0c\u6211\u4eec\u4f7f\u7528open<\/code>\u51fd\u6570\u4ee5\u5199\u6a21\u5f0f\u6253\u5f00\u4e00\u4e2a\u6587\u4ef6\uff0c\u5e76\u521b\u5efa\u4e00\u4e2acsv.writer\u5bf9\u8c61\u3002\u6700\u540e\uff0c\u6211\u4eec\u4f7f\u7528writerows<\/code>\u65b9\u6cd5\u5c06\u6240\u6709\u6570\u636e\u884c\u5199\u5165CSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n
    2\u3001\u4f7f\u7528DictWriter<\/h4>\n<\/p>\n
    \u5982\u679c\u6570\u636e\u662f\u4ee5\u5b57\u5178\u5f62\u5f0f\u5b58\u50a8\u7684\uff0c\u53ef\u4ee5\u4f7f\u7528csv\u6a21\u5757\u7684DictWriter\u7c7b\uff1a<\/p>\n<\/p>\n
    import csv<\/p>\n
    \u6570\u636e<\/strong><\/h2>\n
    data = [<\/p>\n
        {'Name': 'John', 'Age': 28, 'City': 'New York'},<\/p>\n
        {'Name': 'Anna', 'Age': 24, 'City': 'Paris'},<\/p>\n
        {'Name': 'Peter', 'Age': 35, 'City': 'Berlin'},<\/p>\n
        {'Name': 'Linda', 'Age': 32, 'City': 'London'}<\/p>\n
    ]<\/p>\n
    \u4fdd\u5b58\u5230CSV\u6587\u4ef6<\/strong><\/h2>\n
    with open('output.csv', mode='w', newline='') as file:<\/p>\n
        fieldnames = ['Name', 'Age', 'City']<\/p>\n
        writer = csv.DictWriter(file, fieldnames=fieldnames)<\/p>\n
        writer.writeheader()<\/p>\n
        writer.writerows(data)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528\u5b57\u5178\u5217\u8868\u5b58\u50a8\u6570\u636e\uff0c\u5e76\u521b\u5efa\u4e86\u4e00\u4e2aDictWriter\u5bf9\u8c61\u3002\u4f7f\u7528writeheader<\/code>\u65b9\u6cd5\u5199\u5165\u8868\u5934\uff0c\u4f7f\u7528writerows<\/code>\u65b9\u6cd5\u5199\u5165\u6570\u636e\u884c\u3002<\/p>\n<\/p>\n
    \u4e09\u3001\u4f7f\u7528numpy\u5e93<\/h3>\n<\/p>\n
    numpy\u5e93\u4e5f\u53ef\u4ee5\u7528\u4e8e\u5c06\u6570\u636e\u4fdd\u5b58\u5230CSV\u6587\u4ef6\u4e2d\uff0c\u7279\u522b\u9002\u7528\u4e8e\u5904\u7406\u6570\u503c\u578b\u6570\u636e\u3002<\/p>\n<\/p>\n
    1\u3001\u5b89\u88c5numpy<\/h4>\n<\/p>\n
    \u5982\u679c\u4f60\u8fd8\u6ca1\u6709\u5b89\u88c5numpy\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
    2\u3001\u4fdd\u5b58\u6570\u636e\u5230CSV\u6587\u4ef6<\/h4>\n<\/p>\n
    \u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u5c55\u793a\u4e86\u5982\u4f55\u4f7f\u7528numpy\u5c06\u6570\u636e\u4fdd\u5b58\u5230CSV\u6587\u4ef6\u4e2d\uff1a<\/p>\n<\/p>\n
    import numpy as np<\/p>\n
    \u6570\u636e<\/strong><\/h2>\n
    data = np.array([<\/p>\n
        ['Name', 'Age', 'City'],<\/p>\n
        ['John', 28, 'New York'],<\/p>\n
        ['Anna', 24, 'Paris'],<\/p>\n
        ['Peter', 35, 'Berlin'],<\/p>\n
        ['Linda', 32, 'London']<\/p>\n
    ])<\/p>\n
    \u4fdd\u5b58\u5230CSV\u6587\u4ef6<\/strong><\/h2>\n
    np.savetxt('output.csv', data, delimiter=',', fmt='%s')<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u5bfc\u5165\u4e86numpy\u5e93\uff0c\u7136\u540e\u521b\u5efa\u4e86\u4e00\u4e2a\u5305\u542b\u6570\u636e\u7684numpy\u6570\u7ec4\u3002\u63a5\u7740\uff0c\u6211\u4eec\u4f7f\u7528savetxt<\/code>\u65b9\u6cd5\u5c06\u6570\u7ec4\u4fdd\u5b58\u5230CSV\u6587\u4ef6\u4e2d\uff0c\u6307\u5b9a\u5206\u9694\u7b26\u4e3a\u9017\u53f7\uff0c\u6570\u636e\u683c\u5f0f\u4e3a\u5b57\u7b26\u4e32\u3002<\/p>\n<\/p>\n
    \u56db\u3001\u5176\u4ed6\u65b9\u6cd5<\/h3>\n<\/p>\n
    \u9664\u4e86\u4e0a\u8ff0\u65b9\u6cd5\uff0c\u8fd8\u6709\u4e00\u4e9b\u5176\u4ed6\u65b9\u6cd5\u53ef\u4ee5\u5c06\u6570\u636e\u4fdd\u5b58\u5230CSV\u6587\u4ef6\u4e2d\uff0c\u6bd4\u5982\u4f7f\u7528openpyxl<\/code>\u5e93\u5904\u7406Excel\u6587\u4ef6\uff0c\u7136\u540e\u5c06\u5176\u8f6c\u6362\u4e3aCSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n
    1\u3001\u4f7f\u7528openpyxl\u5e93<\/h4>\n<\/p>\n
    \u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u5c55\u793a\u4e86\u5982\u4f55\u4f7f\u7528openpyxl\u5e93\u5c06\u6570\u636e\u4fdd\u5b58\u5230CSV\u6587\u4ef6\u4e2d\uff1a<\/p>\n<\/p>\n
    from openpyxl import Workbook<\/p>\n
    \u521b\u5efaWorkbook<\/strong><\/h2>\n
    wb = Workbook()<\/p>\n
    ws = wb.active<\/p>\n
    \u6570\u636e<\/strong><\/h2>\n
    data = [<\/p>\n
        ['Name', 'Age', 'City'],<\/p>\n
        ['John', 28, 'New York'],<\/p>\n
        ['Anna', 24, 'Paris'],<\/p>\n
        ['Peter', 35, 'Berlin'],<\/p>\n
        ['Linda', 32, 'London']<\/p>\n
    ]<\/p>\n
    \u5199\u5165\u6570\u636e<\/strong><\/h2>\n
    for row in data:<\/p>\n
        ws.append(row)<\/p>\n
    \u4fdd\u5b58\u4e3aExcel\u6587\u4ef6<\/strong><\/h2>\n
    wb.save('output.xlsx')<\/p>\n
    \u5c06Excel\u6587\u4ef6\u8f6c\u6362\u4e3aCSV\u6587\u4ef6<\/strong><\/h2>\n
    import pandas as pd<\/p>\n
    df = pd.read_excel('output.xlsx')<\/p>\n
    df.to_csv('output.csv', index=False)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u4f7f\u7528openpyxl\u5e93\u521b\u5efa\u4e86\u4e00\u4e2aWorkbook\u5bf9\u8c61\uff0c\u5e76\u5199\u5165\u6570\u636e\u3002\u63a5\u7740\uff0c\u6211\u4eec\u5c06Workbook\u4fdd\u5b58\u4e3aExcel\u6587\u4ef6\u3002\u6700\u540e\uff0c\u6211\u4eec\u4f7f\u7528pandas\u5e93\u5c06Excel\u6587\u4ef6\u8f6c\u6362\u4e3aCSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n
    \u603b\u7ed3<\/h3>\n<\/p>\n
    \u5728Python\u4e2d\uff0c\u6709\u591a\u79cd\u65b9\u6cd5\u53ef\u4ee5\u5c06\u7ed3\u679c\u4fdd\u5b58\u5230CSV\u6587\u4ef6\uff0c\u5305\u62ec\u4f7f\u7528pandas\u5e93\u3001csv\u6a21\u5757\u3001numpy\u5e93\u548copenpyxl\u5e93\u7b49\u3002\u9009\u62e9\u9002\u5f53\u7684\u65b9\u6cd5\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u548c\u6570\u636e\u7c7b\u578b\u6765\u51b3\u5b9a\u3002\u638c\u63e1\u8fd9\u4e9b\u65b9\u6cd5\u53ef\u4ee5\u5e2e\u52a9\u4f60\u66f4\u65b9\u4fbf\u5730\u5904\u7406\u548c\u4fdd\u5b58\u6570\u636e\u3002<\/p>\n<\/p>\n
    \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
     \u5982\u4f55\u4f7f\u7528Python\u5c06\u6570\u636e\u4fdd\u5b58\u4e3aCSV\u6587\u4ef6\uff1f<\/strong>
    \u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5185\u7f6e\u7684csv<\/code>\u6a21\u5757\u6216pandas<\/code>\u5e93\u5c06\u6570\u636e\u4fdd\u5b58\u4e3aCSV\u6587\u4ef6\u3002\u5bf9\u4e8e\u7b80\u5355\u7684\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528csv<\/code>\u6a21\u5757\u7684writer<\/code>\u5bf9\u8c61\u3002\u5bf9\u4e8e\u66f4\u590d\u6742\u7684\u6570\u636e\u5904\u7406\uff0cpandas<\/code>\u63d0\u4f9b\u4e86\u66f4\u4e3a\u5f3a\u5927\u7684\u529f\u80fd\u3002\u4ee5\u4e0b\u662f\u57fa\u672c\u793a\u4f8b\uff1a<\/p>\n
    import csv\n\ndata = [['Name', 'Age'], ['Alice', 30], ['Bob', 25]]\nwith open('output.csv', 'w', newline='') as file:\n    writer = csv.writer(file)\n    writer.writerows(data)\n<\/code><\/pre>\n
    \u5982\u679c\u4f7f\u7528pandas<\/code>\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u65b9\u5f0f\u4fdd\u5b58\uff1a<\/p>\n
    import pandas as pd\n\ndf = pd.DataFrame(data, columns=['Name', 'Age'])\ndf.to_csv('output.csv', index=False)\n<\/code><\/pre>\n
    \u4f7f\u7528CSV\u6587\u4ef6\u65f6\uff0c\u6211\u9700\u8981\u6ce8\u610f\u54ea\u4e9b\u4e8b\u9879\uff1f<\/strong>
    \u5728\u4f7f\u7528CSV\u6587\u4ef6\u65f6\uff0c\u6709\u51e0\u4e2a\u5173\u952e\u4e8b\u9879\u9700\u8981\u6ce8\u610f\u3002\u9996\u5148\uff0c\u786e\u4fdd\u6570\u636e\u4e2d\u4e0d\u5305\u542b\u6362\u884c\u7b26\u6216\u9017\u53f7\uff0c\u8fd9\u53ef\u80fd\u4f1a\u7834\u574f\u6587\u4ef6\u7684\u7ed3\u6784\u3002\u5982\u679c\u6570\u636e\u4e2d\u5b58\u5728\u8fd9\u4e9b\u5b57\u7b26\uff0c\u53ef\u4ee5\u4f7f\u7528\u5f15\u53f7\u5c06\u5176\u5305\u88f9\u3002\u5176\u6b21\uff0c\u4e86\u89e3\u7f16\u7801\u683c\u5f0f\u5f88\u91cd\u8981\uff0c\u901a\u5e38\u4f7f\u7528utf-8<\/code>\u7f16\u7801\uff0c\u4f46\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u53ef\u80fd\u9700\u8981\u4f7f\u7528\u5176\u4ed6\u7f16\u7801\u3002\u6b64\u5916\uff0c\u786e\u4fdd\u5728\u5199\u5165\u6587\u4ef6\u65f6\u6b63\u786e\u8bbe\u7f6enewline=''<\/code>\u53c2\u6570\uff0c\u4ee5\u907f\u514d\u5728Windows\u7cfb\u7edf\u4e0b\u51fa\u73b0\u7a7a\u884c\u3002<\/p>\n
    \u5982\u4f55\u5904\u7406\u5305\u542b\u7279\u6b8a\u5b57\u7b26\u7684\u6570\u636e\uff1f<\/strong>
    \u5904\u7406\u5305\u542b\u7279\u6b8a\u5b57\u7b26\u7684\u6570\u636e\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528csv<\/code>\u6a21\u5757\u7684quotechar<\/code>\u53c2\u6570\u6765\u6307\u5b9a\u5305\u88f9\u7279\u6b8a\u5b57\u7b26\u7684\u5f15\u53f7\u7c7b\u578b\u3002\u8fd9\u6837\u53ef\u4ee5\u786e\u4fdd\u6570\u636e\u5728\u4fdd\u5b58\u5230CSV\u65f6\u4e0d\u4f1a\u88ab\u9519\u8bef\u89e3\u6790\u3002\u4f8b\u5982\uff1a<\/p>\n
    with open('output.csv', 'w', newline='') as file:\n    writer = csv.writer(file, quotechar='"', quoting=csv.QUOTE_ALL)\n    writer.writerow(['Name', 'Comment'])\n    writer.writerow(['Alice', 'She sAI<\/a>d, "Hello!"'])\n<\/code><\/pre>\n
    \u4f7f\u7528pandas<\/code>\u65f6\uff0c\u901a\u5e38\u4f1a\u81ea\u52a8\u5904\u7406\u8fd9\u4e9b\u7279\u6b8a\u5b57\u7b26\uff0c\u4f46\u5728\u4fdd\u5b58\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7quotechar<\/code>\u548cquoting<\/code>\u53c2\u6570\u8fdb\u4e00\u6b65\u63a7\u5236\u5904\u7406\u65b9\u5f0f\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u5c06\u7ed3\u679c\u4fdd\u5b58\u5230CSV\u6587\u4ef6\u6709\u51e0\u4e2a\u5173\u952e\u6b65\u9aa4\uff0c\u5305\u62ec\u4f7f\u7528\u9002\u5f53\u7684\u5e93\u3001\u521b\u5efa\u6570\u636e\u7ed3\u6784\u3001\u7f16\u5199\u5230CSV\u6587\u4ef6\u4e2d\u7b49\u3002 […]","protected":false},"author":3,"featured_media":1045998,"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\/1045976"}],"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=1045976"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1045976\/revisions"}],"predecessor-version":[{"id":1046001,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1045976\/revisions\/1046001"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1045998"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1045976"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1045976"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1045976"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}