{"id":1079549,"date":"2025-01-08T12:21:58","date_gmt":"2025-01-08T04:21:58","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1079549.html"},"modified":"2025-01-08T12:22:01","modified_gmt":"2025-01-08T04:22:01","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e5%88%b6%e4%bd%9c%e4%b8%80%e4%b8%aa%e8%a1%a8%e5%a4%b4-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1079549.html","title":{"rendered":"\u5982\u4f55\u7528python\u5236\u4f5c\u4e00\u4e2a\u8868\u5934"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u5236\u4f5c\u4e00\u4e2a\u8868\u5934\"<\/p>\n

\u5982\u4f55\u7528Python\u5236\u4f5c\u4e00\u4e2a\u8868\u5934<\/strong><\/p>\n<\/p>\n

Python\u4e2d\u5236\u4f5c\u8868\u5934\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5305\u62ec\u4f7f\u7528Pandas\u5e93\u3001\u4f7f\u7528csv\u6a21\u5757\u3001\u4f7f\u7528openpyxl\u5e93\u7b49\u3002<\/strong> \u5176\u4e2d\uff0c\u4f7f\u7528Pandas\u5e93\u548ccsv\u6a21\u5757\u662f\u5e38\u89c1\u7684\u9009\u62e9\uff0c\u56e0\u4e3a\u5b83\u4eec\u7b80\u5355\u6613\u7528\u4e14\u529f\u80fd\u5f3a\u5927\u3002\u4f7f\u7528Pandas\u5e93\u53ef\u4ee5\u65b9\u4fbf\u5730\u5904\u7406\u6570\u636e\u5e76\u521b\u5efa\u5177\u6709\u8868\u5934\u7684\u6570\u636e\u6846\uff0c\u4f7f\u7528csv\u6a21\u5757\u53ef\u4ee5\u8f7b\u677e\u5730\u521b\u5efa\u548c\u64cd\u4f5cCSV\u6587\u4ef6<\/strong>\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u65b9\u6cd5\u6765\u5236\u4f5c\u8868\u5934\uff0c\u5e76\u8fdb\u4e00\u6b65\u6df1\u5165\u63a2\u8ba8\u5176\u76f8\u5173\u5e94\u7528\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528Pandas\u5e93\u5236\u4f5c\u8868\u5934<\/p>\n<\/p>\n

Pandas\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\u3002\u4f7f\u7528Pandas\u5e93\u53ef\u4ee5\u975e\u5e38\u65b9\u4fbf\u5730\u521b\u5efa\u5e26\u6709\u8868\u5934\u7684\u6570\u636e\u6846\u3002<\/p>\n<\/p>\n

1\u3001\u5b89\u88c5Pandas\u5e93<\/p>\n<\/p>\n

\u5728\u4f7f\u7528Pandas\u5e93\u4e4b\u524d\uff0c\u9700\u8981\u5148\u5b89\u88c5\u8be5\u5e93\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
2\u3001\u521b\u5efa\u5e26\u6709\u8868\u5934\u7684\u6570\u636e\u6846<\/p>\n<\/p>\n
\u4f7f\u7528Pandas\u5e93\u521b\u5efa\u5e26\u6709\u8868\u5934\u7684\u6570\u636e\u6846\u975e\u5e38\u7b80\u5355\uff0c\u53ef\u4ee5\u76f4\u63a5\u4f20\u5165\u5217\u540d\u53c2\u6570\u6765\u6307\u5b9a\u8868\u5934\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': ['Alice', 'Bob', 'Charlie'],<\/p>\n
    'Age': [25, 30, 35],<\/p>\n
    'City': ['New York', 'Los Angeles', 'Chicago']<\/p>\n
}<\/p>\n
\u521b\u5efa\u5e26\u6709\u8868\u5934\u7684\u6570\u636e\u6846<\/strong><\/h2>\n
df = pd.DataFrame(data)<\/p>\n
\u663e\u793a\u6570\u636e\u6846<\/strong><\/h2>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u521b\u5efa\u4e86\u4e00\u4e2a\u5305\u542b\u4e09\u5217\uff08Name\u3001Age\u3001City\uff09\u7684\u6570\u636e\u6846\uff0c\u5e76\u6307\u5b9a\u4e86\u6bcf\u5217\u7684\u8868\u5934\u3002\u8f93\u51fa\u7ed3\u679c\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
      Name  Age         City<\/p>\n
0    Alice   25     New York<\/p>\n
1      Bob   30  Los Angeles<\/p>\n
2  Charlie   35      Chicago<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u4fdd\u5b58\u6570\u636e\u6846\u5230CSV\u6587\u4ef6<\/p>\n<\/p>\n
Pandas\u5e93\u8fd8\u63d0\u4f9b\u4e86\u5c06\u6570\u636e\u6846\u4fdd\u5b58\u5230CSV\u6587\u4ef6\u7684\u529f\u80fd\uff0c\u53ef\u4ee5\u4f7f\u7528to_csv<\/code>\u65b9\u6cd5\u6765\u5b9e\u73b0\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
# \u5c06\u6570\u636e\u6846\u4fdd\u5b58\u5230CSV\u6587\u4ef6<\/p>\n
df.to_csv('output.csv', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8be5\u547d\u4ee4\u5c06\u6570\u636e\u6846\u4fdd\u5b58\u5230\u540d\u4e3aoutput.csv<\/code>\u7684\u6587\u4ef6\u4e2d\uff0c\u5e76\u4e14\u4e0d\u5305\u542b\u884c\u7d22\u5f15\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528csv\u6a21\u5757\u5236\u4f5c\u8868\u5934<\/p>\n<\/p>\n
Python\u7684csv\u6a21\u5757\u662f\u5904\u7406CSV\u6587\u4ef6\u7684\u6807\u51c6\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u7b80\u5355\u7684\u63a5\u53e3\u6765\u8bfb\u53d6\u548c\u5199\u5165CSV\u6587\u4ef6\u3002\u4f7f\u7528csv\u6a21\u5757\u4e5f\u53ef\u4ee5\u8f7b\u677e\u5730\u521b\u5efa\u5e26\u6709\u8868\u5934\u7684CSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n
1\u3001\u4f7f\u7528csv\u6a21\u5757\u521b\u5efaCSV\u6587\u4ef6<\/p>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4e00\u4e2a\u4f7f\u7528csv\u6a21\u5757\u521b\u5efa\u5e26\u6709\u8868\u5934\u7684CSV\u6587\u4ef6\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import csv<\/p>\n
\u5b9a\u4e49\u8868\u5934<\/strong><\/h2>\n
header = ['Name', 'Age', 'City']<\/p>\n
\u5b9a\u4e49\u6570\u636e<\/strong><\/h2>\n
rows = [<\/p>\n
    ['Alice', 25, 'New York'],<\/p>\n
    ['Bob', 30, 'Los Angeles'],<\/p>\n
    ['Charlie', 35, 'Chicago']<\/p>\n
]<\/p>\n
\u5199\u5165CSV\u6587\u4ef6<\/strong><\/h2>\n
with open('output.csv', 'w', newline='') as file:<\/p>\n
    writer = csv.writer(file)<\/p>\n
    writer.writerow(header)<\/p>\n
    writer.writerows(rows)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u5b9a\u4e49\u4e86\u8868\u5934\u548c\u6570\u636e\uff0c\u7136\u540e\u4f7f\u7528csv.writer<\/code>\u521b\u5efaCSV\u6587\u4ef6\uff0c\u5e76\u5199\u5165\u8868\u5934\u548c\u6570\u636e\u3002<\/p>\n<\/p>\n
2\u3001\u8bfb\u53d6CSV\u6587\u4ef6\u5e76\u663e\u793a\u8868\u5934<\/p>\n<\/p>\n
\u4f7f\u7528csv\u6a21\u5757\u8bfb\u53d6CSV\u6587\u4ef6\u4e5f\u975e\u5e38\u7b80\u5355\uff0c\u53ef\u4ee5\u4f7f\u7528csv.reader<\/code>\u6765\u8bfb\u53d6\u6587\u4ef6\u5185\u5bb9\uff0c\u5e76\u663e\u793a\u8868\u5934\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import csv<\/p>\n
\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
with open('output.csv', 'r') as file:<\/p>\n
    reader = csv.reader(file)<\/p>\n
    header = next(reader)<\/p>\n
    print('Header:', header)<\/p>\n
    for row in reader:<\/p>\n
        print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528next(reader)<\/code>\u65b9\u6cd5\u8bfb\u53d6\u8868\u5934\uff0c\u5e76\u663e\u793a\u51fa\u6765\u3002\u8f93\u51fa\u7ed3\u679c\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
Header: ['Name', 'Age', 'City']<\/p>\n
['Alice', '25', 'New York']<\/p>\n
['Bob', '30', 'Los Angeles']<\/p>\n
['Charlie', '35', 'Chicago']<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528openpyxl\u5e93\u5236\u4f5c\u8868\u5934<\/p>\n<\/p>\n
openpyxl\u662f\u4e00\u4e2a\u7528\u4e8e\u8bfb\u5199Excel\u6587\u4ef6\u7684\u7b2c\u4e09\u65b9\u5e93\uff0c\u53ef\u4ee5\u7528\u6765\u521b\u5efa\u548c\u64cd\u4f5cExcel\u5de5\u4f5c\u7c3f\u3002\u4f7f\u7528openpyxl\u5e93\u4e5f\u53ef\u4ee5\u65b9\u4fbf\u5730\u521b\u5efa\u5e26\u6709\u8868\u5934\u7684Excel\u6587\u4ef6\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5openpyxl\u5e93<\/p>\n<\/p>\n
\u5728\u4f7f\u7528openpyxl\u5e93\u4e4b\u524d\uff0c\u9700\u8981\u5148\u5b89\u88c5\u8be5\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install openpyxl<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u521b\u5efa\u5e26\u6709\u8868\u5934\u7684Excel\u6587\u4ef6<\/p>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4e00\u4e2a\u4f7f\u7528openpyxl\u5e93\u521b\u5efa\u5e26\u6709\u8868\u5934\u7684Excel\u6587\u4ef6\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
from openpyxl import Workbook<\/p>\n
\u521b\u5efa\u5de5\u4f5c\u7c3f\u548c\u5de5\u4f5c\u8868<\/strong><\/h2>\n
wb = Workbook()<\/p>\n
ws = wb.active<\/p>\n
\u5b9a\u4e49\u8868\u5934<\/strong><\/h2>\n
header = ['Name', 'Age', 'City']<\/p>\n
\u5199\u5165\u8868\u5934<\/strong><\/h2>\n
ws.append(header)<\/p>\n
\u5b9a\u4e49\u6570\u636e<\/strong><\/h2>\n
rows = [<\/p>\n
    ['Alice', 25, 'New York'],<\/p>\n
    ['Bob', 30, 'Los Angeles'],<\/p>\n
    ['Charlie', 35, 'Chicago']<\/p>\n
]<\/p>\n
\u5199\u5165\u6570\u636e<\/strong><\/h2>\n
for row in rows:<\/p>\n
    ws.append(row)<\/p>\n
\u4fdd\u5b58Excel\u6587\u4ef6<\/strong><\/h2>\n
wb.save('output.xlsx')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u521b\u5efa\u4e86\u4e00\u4e2a\u5de5\u4f5c\u7c3f\u548c\u5de5\u4f5c\u8868\uff0c\u7136\u540e\u4f7f\u7528ws.append<\/code>\u65b9\u6cd5\u5199\u5165\u8868\u5934\u548c\u6570\u636e\uff0c\u6700\u540e\u4fdd\u5b58\u4e3aExcel\u6587\u4ef6\u3002<\/p>\n<\/p>\n
3\u3001\u8bfb\u53d6Excel\u6587\u4ef6\u5e76\u663e\u793a\u8868\u5934<\/p>\n<\/p>\n
\u4f7f\u7528openpyxl\u5e93\u8bfb\u53d6Excel\u6587\u4ef6\u540c\u6837\u975e\u5e38\u7b80\u5355\uff0c\u53ef\u4ee5\u4f7f\u7528load_workbook<\/code>\u65b9\u6cd5\u6765\u8bfb\u53d6\u6587\u4ef6\u5185\u5bb9\uff0c\u5e76\u663e\u793a\u8868\u5934\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
from openpyxl import load_workbook<\/p>\n
\u8bfb\u53d6Excel\u6587\u4ef6<\/strong><\/h2>\n
wb = load_workbook('output.xlsx')<\/p>\n
ws = wb.active<\/p>\n
\u83b7\u53d6\u8868\u5934<\/strong><\/h2>\n
header = [cell.value for cell in ws[1]]<\/p>\n
print('Header:', header)<\/p>\n
\u83b7\u53d6\u6570\u636e<\/strong><\/h2>\n
for row in ws.iter_rows(min_row=2, values_only=True):<\/p>\n
    print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f\u6765\u83b7\u53d6\u8868\u5934\uff0c\u5e76\u663e\u793a\u51fa\u6765\u3002\u8f93\u51fa\u7ed3\u679c\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
Header: ['Name', 'Age', 'City']<\/p>\n
('Alice', 25, 'New York')<\/p>\n
('Bob', 30, 'Los Angeles')<\/p>\n
('Charlie', 35, 'Chicago')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u603b\u7ed3<\/p>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u4ecb\u7ecd\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0c\u4f7f\u7528Pandas\u5e93\u3001csv\u6a21\u5757\u548copenpyxl\u5e93\u90fd\u53ef\u4ee5\u65b9\u4fbf\u5730\u521b\u5efa\u5e26\u6709\u8868\u5934\u7684\u6570\u636e\u6587\u4ef6<\/strong>\u3002\u5176\u4e2d\uff0cPandas\u5e93\u9002\u5408\u8fdb\u884c\u590d\u6742\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790<\/strong>\uff0ccsv\u6a21\u5757\u9002\u5408\u5904\u7406\u7b80\u5355\u7684CSV\u6587\u4ef6<\/strong>\uff0copenpyxl\u5e93\u9002\u5408\u5904\u7406Excel\u6587\u4ef6<\/strong>\u3002\u6839\u636e\u4e0d\u540c\u7684\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\uff0c\u53ef\u4ee5\u63d0\u9ad8\u5de5\u4f5c\u6548\u7387\uff0c\u7b80\u5316\u6570\u636e\u5904\u7406\u8fc7\u7a0b\u3002\u5e0c\u671b\u672c\u6587\u5bf9\u60a8\u5728\u4f7f\u7528Python\u5236\u4f5c\u8868\u5934\u65f6\u6709\u6240\u5e2e\u52a9\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u521b\u5efa\u8868\u5934\u7684\u6700\u4f73\u65b9\u6cd5\u662f\u4ec0\u4e48\uff1f<\/strong>
\u5728Python\u4e2d\u521b\u5efa\u8868\u5934\u901a\u5e38\u4f7f\u7528Pandas\u5e93\u3002\u4f60\u53ef\u4ee5\u901a\u8fc7\u521b\u5efa\u4e00\u4e2aDataFrame\uff0c\u5e76\u5728\u6784\u9020\u65f6\u5b9a\u4e49\u5217\u540d\u6765\u5b9e\u73b0\u3002\u4f8b\u5982\uff1a  <\/p>\n
import pandas as pd\n\ndata = {\n    '\u59d3\u540d': ['\u5f20\u4e09', '\u674e\u56db'],\n    '\u5e74\u9f84': [28, 34],\n    '\u57ce\u5e02': ['\u5317\u4eac', '\u4e0a\u6d77']\n}\n\ndf = pd.DataFrame(data)\nprint(df)\n<\/code><\/pre>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c'\u59d3\u540d'\u3001'\u5e74\u9f84'\u548c'\u57ce\u5e02'\u5c31\u662f\u8868\u5934\u3002<\/p>\n
\u4f7f\u7528Python\u5236\u4f5c\u8868\u5934\u65f6\uff0c\u5982\u4f55\u81ea\u5b9a\u4e49\u6837\u5f0f\uff1f<\/strong>
\u5982\u679c\u4f60\u5e0c\u671b\u81ea\u5b9a\u4e49\u8868\u5934\u7684\u6837\u5f0f\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u7ed3\u5408Styler\u5bf9\u8c61\u3002\u4f60\u53ef\u4ee5\u6dfb\u52a0\u80cc\u666f\u989c\u8272\u3001\u5b57\u4f53\u6837\u5f0f\u7b49\u3002\u4f8b\u5982\uff1a  <\/p>\n
styled_df = df.style.set_table_attributes('style="font-size: 12px; color: black;"').set_caption("\u7528\u6237\u4fe1\u606f")\nstyled_df\n<\/code><\/pre>\n
\u8fd9\u6837\u53ef\u4ee5\u4f7f\u8868\u5934\u66f4\u5177\u5438\u5f15\u529b\u548c\u53ef\u8bfb\u6027\u3002<\/p>\n
\u5728Python\u4e2d\u5982\u4f55\u5c06\u5e26\u6709\u8868\u5934\u7684\u8868\u683c\u5bfc\u51fa\u5230Excel\uff1f<\/strong>
Pandas\u63d0\u4f9b\u4e86\u975e\u5e38\u65b9\u4fbf\u7684\u65b9\u6cd5\u6765\u5c06DataFrame\u5bfc\u51fa\u5230Excel\u6587\u4ef6\uff0c\u5e76\u4fdd\u7559\u8868\u5934\u3002\u53ef\u4ee5\u4f7f\u7528to_excel<\/code>\u65b9\u6cd5\u6765\u5b9e\u73b0\u8fd9\u4e00\u70b9\u3002\u793a\u4f8b\u5982\u4e0b\uff1a  <\/p>\n
df.to_excel('output.xlsx', index=False)\n<\/code><\/pre>\n
\u901a\u8fc7\u8bbe\u7f6eindex=False<\/code>\uff0c\u53ef\u4ee5\u907f\u514d\u5c06\u884c\u7d22\u5f15\u4e5f\u5199\u5165Excel\uff0c\u4ece\u800c\u4fdd\u6301\u8868\u683c\u7684\u6574\u6d01\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5982\u4f55\u7528Python\u5236\u4f5c\u4e00\u4e2a\u8868\u5934 Python\u4e2d\u5236\u4f5c\u8868\u5934\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5305\u62ec\u4f7f\u7528Pandas\u5e93\u3001\u4f7f\u7528csv\u6a21\u5757\u3001\u4f7f […]","protected":false},"author":3,"featured_media":1079557,"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\/1079549"}],"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=1079549"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1079549\/revisions"}],"predecessor-version":[{"id":1079560,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1079549\/revisions\/1079560"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1079557"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1079549"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1079549"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1079549"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}