{"id":1074555,"date":"2025-01-08T11:35:49","date_gmt":"2025-01-08T03:35:49","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1074555.html"},"modified":"2025-01-08T11:35:51","modified_gmt":"2025-01-08T03:35:51","slug":"python%e5%a6%82%e4%bd%95%e6%8c%89%e6%9d%a1%e4%bb%b6%e6%b7%bb%e5%8a%a0%e4%b8%80%e8%a1%8c-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1074555.html","title":{"rendered":"python\u5982\u4f55\u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c"},"content":{"rendered":"

\"python\u5982\u4f55\u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c\"<\/p>\n

Python\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c\uff1a\u4f7f\u7528pandas\u5e93\u3001\u5217\u8868\u64cd\u4f5c\u3001\u751f\u6210\u5668\u8868\u8fbe\u5f0f\u7b49\u3002<\/strong>\u5176\u4e2d\uff0c\u6700\u5e38\u7528\u7684\u65b9\u6cd5\u662f\u4f7f\u7528pandas\u5e93\uff0c\u56e0\u4e3a\u5b83\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u64cd\u4f5c\u529f\u80fd\u3002\u4ee5\u4e0b\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528pandas\u5e93\u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c\uff0c\u5e76\u63d0\u4f9b\u4e00\u4e9b\u5b9e\u7528\u7684\u793a\u4f8b\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528Pandas\u5e93<\/h3>\n<\/p>\n

Pandas\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u6570\u636e\u5904\u7406\u5e93\u4e4b\u4e00\uff0c\u7279\u522b\u9002\u7528\u4e8e\u5904\u7406\u8868\u683c\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pandas\u5e93\u4e2d\u7684DataFrame\u6765\u5b58\u50a8\u548c\u64cd\u4f5c\u6570\u636e\u3002<\/p>\n<\/p>\n

1. \u521b\u5efaDataFrame<\/h4>\n<\/p>\n

\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u521b\u5efa\u4e00\u4e2aDataFrame\u3002DataFrame\u662fpandas\u5e93\u4e2d\u7684\u4e00\u4e2a\u6570\u636e\u7ed3\u6784\uff0c\u7c7b\u4f3c\u4e8e\u7535\u5b50\u8868\u683c\u6216\u8005SQL\u8868\u683c\u3002<\/p>\n<\/p>\n

import pandas as pd<\/p>\n
\u521b\u5efa\u4e00\u4e2a\u793a\u4f8bDataFrame<\/strong><\/h2>\n
data = {<\/p>\n
    'Name': ['Alice', 'Bob', 'Charlie'],<\/p>\n
    'Age': [24, 30, 22],<\/p>\n
    'City': ['New York', 'Los Angeles', 'Chicago']<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c<\/h4>\n<\/p>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u6761\u4ef6\u5224\u65ad\u6765\u51b3\u5b9a\u662f\u5426\u6dfb\u52a0\u4e00\u884c\u5230DataFrame\u4e2d\u3002\u5047\u8bbe\u6211\u4eec\u5e0c\u671b\u5728\u6ee1\u8db3\u67d0\u4e2a\u6761\u4ef6\u65f6\u6dfb\u52a0\u4e00\u884c\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528append()<\/code>\u65b9\u6cd5\u6216\u8005loc[]<\/code>\u65b9\u6cd5\u3002<\/p>\n<\/p>\n
\u4f7f\u7528append()<\/code>\u65b9\u6cd5<\/strong>\uff1a<\/p>\n<\/p>\n
# \u5b9a\u4e49\u6761\u4ef6<\/p>\n
condition = True<\/p>\n
\u5b9a\u4e49\u8981\u6dfb\u52a0\u7684\u884c<\/strong><\/h2>\n
new_row = {'Name': 'David', 'Age': 28, 'City': 'San Francisco'}<\/p>\n
\u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c<\/strong><\/h2>\n
if condition:<\/p>\n
    df = df.append(new_row, ignore_index=True)<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f7f\u7528loc[]<\/code>\u65b9\u6cd5<\/strong>\uff1a<\/p>\n<\/p>\n
# \u5b9a\u4e49\u6761\u4ef6<\/p>\n
condition = True<\/p>\n
\u5b9a\u4e49\u8981\u6dfb\u52a0\u7684\u884c<\/strong><\/h2>\n
new_row = {'Name': 'David', 'Age': 28, 'City': 'San Francisco'}<\/p>\n
\u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c<\/strong><\/h2>\n
if condition:<\/p>\n
    df.loc[len(df.index)] = new_row<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528\u5217\u8868\u64cd\u4f5c<\/h3>\n<\/p>\n
\u5982\u679c\u6570\u636e\u91cf\u8f83\u5c0f\u6216\u8005\u4e0d\u9700\u8981\u4f7f\u7528pandas\uff0c\u53ef\u4ee5\u4f7f\u7528\u5217\u8868\u64cd\u4f5c\u6765\u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c\u3002<\/p>\n<\/p>\n
1. \u521b\u5efa\u5217\u8868<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u521b\u5efa\u4e00\u4e2a\u5217\u8868\u6765\u5b58\u50a8\u6570\u636e\u3002<\/p>\n<\/p>\n
# \u521b\u5efa\u4e00\u4e2a\u793a\u4f8b\u5217\u8868<\/p>\n
data = [<\/p>\n
    ['Alice', 24, 'New York'],<\/p>\n
    ['Bob', 30, 'Los Angeles'],<\/p>\n
    ['Charlie', 22, 'Chicago']<\/p>\n
]<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c<\/h4>\n<\/p>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u6761\u4ef6\u5224\u65ad\u6765\u51b3\u5b9a\u662f\u5426\u6dfb\u52a0\u4e00\u884c\u6570\u636e\u5230\u5217\u8868\u4e2d\u3002<\/p>\n<\/p>\n
# \u5b9a\u4e49\u6761\u4ef6<\/p>\n
condition = True<\/p>\n
\u5b9a\u4e49\u8981\u6dfb\u52a0\u7684\u884c<\/strong><\/h2>\n
new_row = ['David', 28, 'San Francisco']<\/p>\n
\u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c<\/strong><\/h2>\n
if condition:<\/p>\n
    data.append(new_row)<\/p>\n
print(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528\u751f\u6210\u5668\u8868\u8fbe\u5f0f<\/h3>\n<\/p>\n
\u751f\u6210\u5668\u8868\u8fbe\u5f0f\u662fPython\u4e2d\u7684\u4e00\u79cd\u9ad8\u7ea7\u7279\u6027\uff0c\u9002\u7528\u4e8e\u9700\u8981\u6309\u6761\u4ef6\u751f\u6210\u6570\u636e\u7684\u60c5\u51b5\u3002\u867d\u7136\u4e0d\u76f4\u63a5\u7528\u4e8e\u6dfb\u52a0\u4e00\u884c\uff0c\u4f46\u53ef\u4ee5\u7528\u4e8e\u6309\u6761\u4ef6\u751f\u6210\u65b0\u7684\u6570\u636e\u96c6\u3002<\/p>\n<\/p>\n
1. \u521b\u5efa\u751f\u6210\u5668\u8868\u8fbe\u5f0f<\/h4>\n<\/p>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u751f\u6210\u5668\u8868\u8fbe\u5f0f\u6765\u6309\u6761\u4ef6\u751f\u6210\u65b0\u7684\u6570\u636e\u96c6\u3002<\/p>\n<\/p>\n
# \u521b\u5efa\u4e00\u4e2a\u793a\u4f8b\u5217\u8868<\/p>\n
data = [<\/p>\n
    ['Alice', 24, 'New York'],<\/p>\n
    ['Bob', 30, 'Los Angeles'],<\/p>\n
    ['Charlie', 22, 'Chicago']<\/p>\n
]<\/p>\n
\u5b9a\u4e49\u6761\u4ef6<\/strong><\/h2>\n
condition = lambda row: row[1] > 25<\/p>\n
\u6309\u6761\u4ef6\u751f\u6210\u65b0\u7684\u6570\u636e\u96c6<\/strong><\/h2>\n
new_data = [row for row in data if condition(row)]<\/p>\n
\u5b9a\u4e49\u8981\u6dfb\u52a0\u7684\u884c<\/strong><\/h2>\n
new_row = ['David', 28, 'San Francisco']<\/p>\n
\u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c<\/strong><\/h2>\n
if condition(new_row):<\/p>\n
    new_data.append(new_row)<\/p>\n
print(new_data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u7ed3\u5408\u5b9e\u9645\u5e94\u7528<\/h3>\n<\/p>\n
\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u6211\u4eec\u7ecf\u5e38\u9700\u8981\u6839\u636e\u590d\u6742\u6761\u4ef6\u6765\u6dfb\u52a0\u6570\u636e\u3002\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u5305\u542b\u5b66\u751f\u6210\u7ee9\u7684DataFrame\uff0c\u6211\u4eec\u5e0c\u671b\u5728\u67d0\u4e2a\u5b66\u751f\u6210\u7ee9\u8fbe\u5230\u67d0\u4e2a\u9608\u503c\u65f6\u6dfb\u52a0\u4e00\u884c\u6570\u636e\u3002<\/p>\n<\/p>\n
1. \u521b\u5efa\u5305\u542b\u5b66\u751f\u6210\u7ee9\u7684DataFrame<\/h4>\n<\/p>\n
import pandas as pd<\/p>\n
\u521b\u5efa\u4e00\u4e2a\u793a\u4f8bDataFrame<\/strong><\/h2>\n
data = {<\/p>\n
    'Student': ['Alice', 'Bob', 'Charlie'],<\/p>\n
    'Math': [85, 90, 78],<\/p>\n
    'Science': [88, 92, 80],<\/p>\n
    'English': [87, 85, 83]<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c<\/h4>\n<\/p>\n
\u6211\u4eec\u53ef\u4ee5\u5b9a\u4e49\u4e00\u4e2a\u51fd\u6570\u6765\u68c0\u67e5\u67d0\u4e2a\u5b66\u751f\u7684\u6210\u7ee9\u662f\u5426\u8fbe\u5230\u67d0\u4e2a\u9608\u503c\uff0c\u5e76\u5728\u6ee1\u8db3\u6761\u4ef6\u65f6\u6dfb\u52a0\u4e00\u884c\u6570\u636e\u3002<\/p>\n<\/p>\n
# \u5b9a\u4e49\u6761\u4ef6\u51fd\u6570<\/p>\n
def check_threshold(row, threshold=85):<\/p>\n
    return row['Math'] > threshold and row['Science'] > threshold and row['English'] > threshold<\/p>\n
\u5b9a\u4e49\u8981\u6dfb\u52a0\u7684\u884c<\/strong><\/h2>\n
new_row = {'Student': 'David', 'Math': 92, 'Science': 95, 'English': 93}<\/p>\n
\u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c<\/strong><\/h2>\n
if check_threshold(new_row):<\/p>\n
    df = df.append(new_row, ignore_index=True)<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u793a\u4f8b\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u5982\u4f55\u4f7f\u7528pandas\u5e93\u3001\u5217\u8868\u64cd\u4f5c\u548c\u751f\u6210\u5668\u8868\u8fbe\u5f0f\u6765\u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c\u6570\u636e\u3002\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\uff0c\u80fd\u591f\u63d0\u9ad8\u4ee3\u7801\u7684\u53ef\u8bfb\u6027\u548c\u6267\u884c\u6548\u7387\u3002<\/p>\n<\/p>\n
\u4e94\u3001\u4f18\u5316\u548c\u6700\u4f73\u5b9e\u8df5<\/h3>\n<\/p>\n
\u5728\u5b9e\u9645\u9879\u76ee\u4e2d\uff0c\u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c\u5f80\u5f80\u662f\u6570\u636e\u5904\u7406\u8fc7\u7a0b\u4e2d\u7684\u4e00\u90e8\u5206\u3002\u4e3a\u4e86\u63d0\u9ad8\u4ee3\u7801\u7684\u53ef\u8bfb\u6027\u548c\u7ef4\u62a4\u6027\uff0c\u53ef\u4ee5\u8003\u8651\u4ee5\u4e0b\u4f18\u5316\u548c\u6700\u4f73\u5b9e\u8df5\u3002<\/p>\n<\/p>\n
1. \u4f7f\u7528\u51fd\u6570\u5c01\u88c5\u903b\u8f91<\/h4>\n<\/p>\n
\u5c06\u6761\u4ef6\u5224\u65ad\u548c\u6dfb\u52a0\u884c\u7684\u903b\u8f91\u5c01\u88c5\u5230\u51fd\u6570\u4e2d\uff0c\u53ef\u4ee5\u63d0\u9ad8\u4ee3\u7801\u7684\u53ef\u8bfb\u6027\u548c\u590d\u7528\u6027\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
def create_dataframe():<\/p>\n
    data = {<\/p>\n
        'Name': ['Alice', 'Bob', 'Charlie'],<\/p>\n
        'Age': [24, 30, 22],<\/p>\n
        'City': ['New York', 'Los Angeles', 'Chicago']<\/p>\n
    }<\/p>\n
    return pd.DataFrame(data)<\/p>\n
def add_row_if_condition(df, new_row, condition):<\/p>\n
    if condition(new_row):<\/p>\n
        df = df.append(new_row, ignore_index=True)<\/p>\n
    return df<\/p>\n
\u793a\u4f8b\u4f7f\u7528<\/strong><\/h2>\n
df = create_dataframe()<\/p>\n
new_row = {'Name': 'David', 'Age': 28, 'City': 'San Francisco'}<\/p>\n
condition = lambda row: row['Age'] > 25<\/p>\n
df = add_row_if_condition(df, new_row, condition)<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u4f7f\u7528\u5f02\u5e38\u5904\u7406<\/h4>\n<\/p>\n
\u5728\u5b9e\u9645\u9879\u76ee\u4e2d\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u6570\u636e\u683c\u5f0f\u4e0d\u4e00\u81f4\u6216\u8005\u5176\u4ed6\u5f02\u5e38\u60c5\u51b5\u3002\u53ef\u4ee5\u4f7f\u7528\u5f02\u5e38\u5904\u7406\u6765\u63d0\u9ad8\u4ee3\u7801\u7684\u5065\u58ee\u6027\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
def add_row_with_exception_handling(df, new_row, condition):<\/p>\n
    try:<\/p>\n
        if condition(new_row):<\/p>\n
            df = df.append(new_row, ignore_index=True)<\/p>\n
    except Exception as e:<\/p>\n
        print(f"Error adding row: {e}")<\/p>\n
    return df<\/p>\n
\u793a\u4f8b\u4f7f\u7528<\/strong><\/h2>\n
df = create_dataframe()<\/p>\n
new_row = {'Name': 'David', 'Age': 'twenty-eight', 'City': 'San Francisco'}  # \u9519\u8bef\u7684\u5e74\u9f84\u683c\u5f0f<\/p>\n
condition = lambda row: isinstance(row['Age'], int) and row['Age'] > 25<\/p>\n
df = add_row_with_exception_handling(df, new_row, condition)<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u8fd9\u4e9b\u4f18\u5316\u548c\u6700\u4f73\u5b9e\u8df5\uff0c\u53ef\u4ee5\u63d0\u9ad8\u4ee3\u7801\u7684\u53ef\u8bfb\u6027\u3001\u590d\u7528\u6027\u548c\u5065\u58ee\u6027\uff0c\u4ece\u800c\u66f4\u597d\u5730\u5e94\u5bf9\u5b9e\u9645\u9879\u76ee\u4e2d\u7684\u6570\u636e\u5904\u7406\u9700\u6c42\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5728Python\u4e2d\uff0c\u5982\u4f55\u6839\u636e\u7279\u5b9a\u6761\u4ef6\u5728\u6570\u636e\u6846\u4e2d\u6dfb\u52a0\u65b0\u884c\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u4f7f\u7528Pandas\u5e93\u53ef\u4ee5\u8f7b\u677e\u5730\u6839\u636e\u6761\u4ef6\u5411\u6570\u636e\u6846\u6dfb\u52a0\u65b0\u884c\u3002\u53ef\u4ee5\u901a\u8fc7\u5b9a\u4e49\u4e00\u4e2a\u6761\u4ef6\u5e76\u4f7f\u7528loc<\/code>\u6216append<\/code>\u65b9\u6cd5\u6765\u5b9e\u73b0\u3002\u4f8b\u5982\uff0c\u60a8\u53ef\u4ee5\u6839\u636e\u67d0\u4e00\u5217\u7684\u503c\u6765\u51b3\u5b9a\u662f\u5426\u6dfb\u52a0\u65b0\u884c\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n
import pandas as pd\n\n# \u521b\u5efa\u4e00\u4e2a\u793a\u4f8b\u6570\u636e\u6846\ndf = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})\n\n# \u5b9a\u4e49\u6761\u4ef6\u548c\u65b0\u884c\u6570\u636e\ncondition = df['A'] > 2\nnew_row = {'A': 4, 'B': 7}\n\n# \u6839\u636e\u6761\u4ef6\u6dfb\u52a0\u65b0\u884c\nif condition.any():\n    df = df.append(new_row, ignore_index=True)\n\nprint(df)\n<\/code><\/pre>\n
\u5982\u4f55\u5728Python\u5217\u8868\u4e2d\u6309\u6761\u4ef6\u6dfb\u52a0\u5143\u7d20\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f\u6216if<\/code>\u8bed\u53e5\u6765\u6839\u636e\u6761\u4ef6\u5411\u5217\u8868\u4e2d\u6dfb\u52a0\u5143\u7d20\u3002\u4f8b\u5982\uff0c\u5982\u679c\u60a8\u60f3\u8981\u5c06\u7b26\u5408\u67d0\u4e2a\u6761\u4ef6\u7684\u503c\u6dfb\u52a0\u5230\u65b0\u5217\u8868\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5982\u4e0b\u4ee3\u7801\uff1a<\/p>\n
original_list = [1, 2, 3, 4, 5]\nnew_list = []\n\nfor item in original_list:\n    if item > 3:\n        new_list.append(item)\n\nprint(new_list)  # \u8f93\u51fa: [4, 5]\n<\/code><\/pre>\n
\u662f\u5426\u53ef\u4ee5\u5728Python\u7684\u5b57\u5178\u4e2d\u6309\u6761\u4ef6\u6dfb\u52a0\u952e\u503c\u5bf9\uff1f<\/strong>
\u662f\u7684\uff0c\u60a8\u53ef\u4ee5\u5728Python\u5b57\u5178\u4e2d\u6839\u636e\u7279\u5b9a\u6761\u4ef6\u6dfb\u52a0\u952e\u503c\u5bf9\u3002\u53ef\u4ee5\u4f7f\u7528\u6761\u4ef6\u8bed\u53e5\u68c0\u67e5\u6761\u4ef6\u662f\u5426\u6ee1\u8db3\uff0c\u7136\u540e\u6267\u884c\u6dfb\u52a0\u64cd\u4f5c\u3002\u4f8b\u5982\uff1a<\/p>\n
my_dict = {'a': 1, 'b': 2}\n\n# \u5b9a\u4e49\u6761\u4ef6\nkey = 'c'\nvalue = 3\n\nif value > 2:  # \u4ec5\u5728\u503c\u5927\u4e8e2\u65f6\u6dfb\u52a0\n    my_dict[key] = value\n\nprint(my_dict)  # \u8f93\u51fa: {'a': 1, 'b': 2, 'c': 3}\n<\/code><\/pre>\n
\u8fd9\u4e9b\u65b9\u6cd5\u4f7f\u60a8\u80fd\u591f\u7075\u6d3b\u5730\u5728Python\u6570\u636e\u7ed3\u6784\u4e2d\u6309\u6761\u4ef6\u6dfb\u52a0\u65b0\u884c\u6216\u65b0\u5143\u7d20\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u6309\u6761\u4ef6\u6dfb\u52a0\u4e00\u884c\uff1a\u4f7f\u7528pandas\u5e93\u3001\u5217\u8868\u64cd\u4f5c\u3001\u751f\u6210\u5668\u8868\u8fbe\u5f0f\u7b49\u3002\u5176\u4e2d\uff0c\u6700\u5e38\u7528\u7684\u65b9\u6cd5\u662f […]","protected":false},"author":3,"featured_media":1074565,"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\/1074555"}],"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=1074555"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1074555\/revisions"}],"predecessor-version":[{"id":1074566,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1074555\/revisions\/1074566"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1074565"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1074555"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1074555"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1074555"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}