{"id":1110656,"date":"2025-01-08T17:21:43","date_gmt":"2025-01-08T09:21:43","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1110656.html"},"modified":"2025-01-08T17:21:45","modified_gmt":"2025-01-08T09:21:45","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e5%b0%86%e4%b8%80%e7%bb%84%e5%b9%b4%e9%be%84%e5%88%86%e7%b1%bb","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1110656.html","title":{"rendered":"\u5982\u4f55\u7528python\u5c06\u4e00\u7ec4\u5e74\u9f84\u5206\u7c7b"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u5c06\u4e00\u7ec4\u5e74\u9f84\u5206\u7c7b\"<\/p>\n

\u7528Python\u5c06\u4e00\u7ec4\u5e74\u9f84\u5206\u7c7b\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528\u6761\u4ef6\u5224\u65ad\u3001\u5217\u8868\u63a8\u5bfc\u3001\u5b57\u5178\u6620\u5c04\u7b49\u3002\u4f60\u53ef\u4ee5\u9009\u62e9\u9002\u5408\u81ea\u5df1\u7684\u65b9\u6cd5\u6765\u5b9e\u73b0\u76ee\u6807\u3002<\/strong> \u5176\u4e2d\uff0c\u6700\u5e38\u89c1\u7684\u505a\u6cd5\u662f\u4f7f\u7528\u6761\u4ef6\u5224\u65ad\u6765\u786e\u5b9a\u6bcf\u4e2a\u5e74\u9f84\u6240\u5c5e\u7684\u7c7b\u522b\uff0c\u4f8b\u5982\u513f\u7ae5\u3001\u9752\u5c11\u5e74\u3001\u6210\u5e74\u4eba\u548c\u8001\u5e74\u4eba\u3002\u53ef\u4ee5\u901a\u8fc7\u6784\u5efa\u4e00\u4e2a\u51fd\u6570\u6765\u5206\u7c7b\u5e74\u9f84\uff0c\u7136\u540e\u5e94\u7528\u5230\u6574\u4e2a\u5e74\u9f84\u5217\u8868\u4e0a\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u51e0\u79cd\u5e38\u89c1\u7684\u65b9\u6cd5\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528\u6761\u4ef6\u5224\u65ad\u5206\u7c7b<\/h3>\n<\/p>\n

\u4f7f\u7528\u6761\u4ef6\u5224\u65ad\u53ef\u4ee5\u6839\u636e\u5e74\u9f84\u7684\u4e0d\u540c\u8303\u56f4\uff0c\u5c06\u5e74\u9f84\u5206\u7c7b\u5230\u4e0d\u540c\u7684\u7ec4\u522b\u4e2d\u3002\u8fd9\u662f\u6700\u76f4\u63a5\u4e14\u6613\u4e8e\u7406\u89e3\u7684\u65b9\u6cd5\u3002<\/p>\n<\/p>\n

1\u3001\u5b9a\u4e49\u5206\u7c7b\u51fd\u6570<\/h4>\n<\/p>\n

\u6211\u4eec\u53ef\u4ee5\u5b9a\u4e49\u4e00\u4e2a\u51fd\u6570\uff0c\u6839\u636e\u5e74\u9f84\u7684\u8303\u56f4\u8fd4\u56de\u5bf9\u5e94\u7684\u5206\u7c7b\u6807\u7b7e\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n

def classify_age(age):<\/p>\n
    if age < 13:<\/p>\n
        return '\u513f\u7ae5'<\/p>\n
    elif 13 <= age < 18:<\/p>\n
        return '\u9752\u5c11\u5e74'<\/p>\n
    elif 18 <= age < 60:<\/p>\n
        return '\u6210\u5e74\u4eba'<\/p>\n
    else:<\/p>\n
        return '\u8001\u5e74\u4eba'<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5e94\u7528\u5206\u7c7b\u51fd\u6570<\/h4>\n<\/p>\n
\u7136\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5c06\u8fd9\u4e2a\u51fd\u6570\u5e94\u7528\u5230\u4e00\u4e2a\u5e74\u9f84\u5217\u8868\u4e0a\uff0c\u5f97\u5230\u6bcf\u4e2a\u5e74\u9f84\u7684\u5206\u7c7b\u7ed3\u679c\uff1a<\/p>\n<\/p>\n
ages = [4, 15, 20, 35, 70, 12, 18]<\/p>\n
age_categories = [classify_age(age) for age in ages]<\/p>\n
print(age_categories)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u5c06\u8f93\u51fa\uff1a<\/p>\n<\/p>\n
['\u513f\u7ae5', '\u9752\u5c11\u5e74', '\u6210\u5e74\u4eba', '\u6210\u5e74\u4eba', '\u8001\u5e74\u4eba', '\u513f\u7ae5', '\u6210\u5e74\u4eba']<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528\u5b57\u5178\u6620\u5c04\u5206\u7c7b<\/h3>\n<\/p>\n
\u5b57\u5178\u6620\u5c04\u662f\u4e00\u79cd\u66f4\u52a0\u7b80\u6d01\u548c\u9ad8\u6548\u7684\u65b9\u6cd5\uff0c\u7279\u522b\u9002\u5408\u5904\u7406\u5206\u7c7b\u8303\u56f4\u660e\u786e\u4e14\u4e0d\u9700\u8981\u590d\u6742\u903b\u8f91\u7684\u60c5\u51b5\u3002<\/p>\n<\/p>\n
1\u3001\u5b9a\u4e49\u5e74\u9f84\u8303\u56f4\u548c\u5206\u7c7b\u6807\u7b7e<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u5b9a\u4e49\u4e00\u4e2a\u5305\u542b\u5e74\u9f84\u8303\u56f4\u548c\u5bf9\u5e94\u5206\u7c7b\u6807\u7b7e\u7684\u5b57\u5178\uff1a<\/p>\n<\/p>\n
age_ranges = {<\/p>\n
    '\u513f\u7ae5': range(0, 13),<\/p>\n
    '\u9752\u5c11\u5e74': range(13, 18),<\/p>\n
    '\u6210\u5e74\u4eba': range(18, 60),<\/p>\n
    '\u8001\u5e74\u4eba': range(60, 120)<\/p>\n
}<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u7f16\u5199\u5206\u7c7b\u51fd\u6570<\/h4>\n<\/p>\n
\u7136\u540e\uff0c\u7f16\u5199\u4e00\u4e2a\u51fd\u6570\uff0c\u901a\u8fc7\u904d\u5386\u5b57\u5178\u6765\u786e\u5b9a\u6bcf\u4e2a\u5e74\u9f84\u7684\u5206\u7c7b\uff1a<\/p>\n<\/p>\n
def classify_age_with_dict(age):<\/p>\n
    for category, age_range in age_ranges.items():<\/p>\n
        if age in age_range:<\/p>\n
            return category<\/p>\n
    return '\u672a\u77e5'<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u5e94\u7528\u5206\u7c7b\u51fd\u6570<\/h4>\n<\/p>\n
\u540c\u6837\u5730\uff0c\u5e94\u7528\u8fd9\u4e2a\u51fd\u6570\u5230\u4e00\u4e2a\u5e74\u9f84\u5217\u8868\u4e0a\uff1a<\/p>\n<\/p>\n
ages = [4, 15, 20, 35, 70, 12, 18]<\/p>\n
age_categories = [classify_age_with_dict(age) for age in ages]<\/p>\n
print(age_categories)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u4e5f\u5c06\u8f93\u51fa\uff1a<\/p>\n<\/p>\n
['\u513f\u7ae5', '\u9752\u5c11\u5e74', '\u6210\u5e74\u4eba', '\u6210\u5e74\u4eba', '\u8001\u5e74\u4eba', '\u513f\u7ae5', '\u6210\u5e74\u4eba']<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528Pandas\u8fdb\u884c\u5206\u7c7b<\/h3>\n<\/p>\n
Pandas\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u5e93\uff0c\u63d0\u4f9b\u4e86\u66f4\u52a0\u7075\u6d3b\u548c\u9ad8\u6548\u7684\u6570\u636e\u64cd\u4f5c\u65b9\u6cd5\uff0c\u5c24\u5176\u9002\u7528\u4e8e\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u3002<\/p>\n<\/p>\n
1\u3001\u5bfc\u5165Pandas\u5e93<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86Pandas\u5e93\uff0c\u5982\u679c\u6ca1\u6709\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5bfc\u5165Pandas\u5e93\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u521b\u5efa\u6570\u636e\u6846<\/h4>\n<\/p>\n
\u521b\u5efa\u4e00\u4e2a\u5305\u542b\u5e74\u9f84\u6570\u636e\u7684\u6570\u636e\u6846\uff1a<\/p>\n<\/p>\n
data = {'Age': [4, 15, 20, 35, 70, 12, 18]}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u5b9a\u4e49\u5206\u7c7b\u89c4\u5219<\/h4>\n<\/p>\n
\u4f7f\u7528Pandas\u7684cut<\/code>\u51fd\u6570\uff0c\u6839\u636e\u5e74\u9f84\u8303\u56f4\u8fdb\u884c\u5206\u7c7b\uff1a<\/p>\n<\/p>\n
bins = [0, 12, 17, 59, 120]<\/p>\n
labels = ['\u513f\u7ae5', '\u9752\u5c11\u5e74', '\u6210\u5e74\u4eba', '\u8001\u5e74\u4eba']<\/p>\n
df['Category'] = pd.cut(df['Age'], bins=bins, labels=labels, right=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u67e5\u770b\u7ed3\u679c<\/h4>\n<\/p>\n
\u6700\u540e\uff0c\u67e5\u770b\u5206\u7c7b\u7ed3\u679c\uff1a<\/p>\n<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u5c06\u8f93\u51fa\uff1a<\/p>\n<\/p>\n
   Age  Category<\/p>\n
0    4       \u513f\u7ae5<\/p>\n
1   15     \u9752\u5c11\u5e74<\/p>\n
2   20     \u6210\u5e74\u4eba<\/p>\n
3   35     \u6210\u5e74\u4eba<\/p>\n
4   70     \u8001\u5e74\u4eba<\/p>\n
5   12       \u513f\u7ae5<\/p>\n
6   18     \u6210\u5e74\u4eba<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4f7f\u7528Numpy\u8fdb\u884c\u5206\u7c7b<\/h3>\n<\/p>\n
Numpy\u662f\u53e6\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5e93\uff0c\u9002\u5408\u5904\u7406\u6570\u503c\u6570\u636e\u548c\u5927\u89c4\u6a21\u6570\u7ec4\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
1\u3001\u5bfc\u5165Numpy\u5e93<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86Numpy\u5e93\uff0c\u5982\u679c\u6ca1\u6709\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install numpy<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5bfc\u5165Numpy\u5e93\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u521b\u5efa\u5e74\u9f84\u6570\u7ec4<\/h4>\n<\/p>\n
\u521b\u5efa\u4e00\u4e2a\u5305\u542b\u5e74\u9f84\u6570\u636e\u7684\u6570\u7ec4\uff1a<\/p>\n<\/p>\n
ages = np.array([4, 15, 20, 35, 70, 12, 18])<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u5b9a\u4e49\u5206\u7c7b\u89c4\u5219<\/h4>\n<\/p>\n
\u4f7f\u7528Numpy\u7684digitize<\/code>\u51fd\u6570\uff0c\u6839\u636e\u5e74\u9f84\u8303\u56f4\u8fdb\u884c\u5206\u7c7b\uff1a<\/p>\n<\/p>\n
bins = [0, 13, 18, 60, 120]<\/p>\n
labels = np.array(['\u513f\u7ae5', '\u9752\u5c11\u5e74', '\u6210\u5e74\u4eba', '\u8001\u5e74\u4eba'])<\/p>\n
categories_indices = np.digitize(ages, bins, right=False)<\/p>\n
categories = labels[categories_indices - 1]<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u67e5\u770b\u7ed3\u679c<\/h4>\n<\/p>\n
\u6700\u540e\uff0c\u67e5\u770b\u5206\u7c7b\u7ed3\u679c\uff1a<\/p>\n<\/p>\n
print(categories)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u5c06\u8f93\u51fa\uff1a<\/p>\n<\/p>\n
['\u513f\u7ae5' '\u9752\u5c11\u5e74' '\u6210\u5e74\u4eba' '\u6210\u5e74\u4eba' '\u8001\u5e74\u4eba' '\u513f\u7ae5' '\u6210\u5e74\u4eba']<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u7528Python\u5c06\u4e00\u7ec4\u5e74\u9f84\u5206\u7c7b\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u5b9e\u73b0\uff0c\u5305\u62ec\u4f7f\u7528\u6761\u4ef6\u5224\u65ad\u3001\u5b57\u5178\u6620\u5c04\u3001Pandas\u5e93\u548cNumpy\u5e93\u7b49\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u52bf\u548c\u9002\u7528\u573a\u666f\u3002\u6761\u4ef6\u5224\u65ad\u9002\u7528\u4e8e\u7b80\u5355\u7684\u5206\u7c7b\u9700\u6c42\uff0c\u5b57\u5178\u6620\u5c04\u66f4\u4e3a\u7b80\u6d01\uff0cPandas\u548cNumpy\u5219\u9002\u5408\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u548c\u590d\u6742\u7684\u5206\u6790\u4efb\u52a1\u3002<\/strong> \u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u4e0d\u4ec5\u53ef\u4ee5\u63d0\u9ad8\u4ee3\u7801\u7684\u6548\u7387\u548c\u53ef\u8bfb\u6027\uff0c\u8fd8\u53ef\u4ee5\u66f4\u597d\u5730\u6ee1\u8db3\u7279\u5b9a\u7684\u4e1a\u52a1\u9700\u6c42\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u6839\u636e\u5e74\u9f84\u6bb5\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u7ec4\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u5e93\u4e2d\u7684cut<\/code>\u51fd\u6570\u8f7b\u677e\u5730\u5c06\u4e00\u7ec4\u5e74\u9f84\u5206\u4e3a\u4e0d\u540c\u7684\u5206\u7c7b\u3002\u4f8b\u5982\uff0c\u60a8\u53ef\u4ee5\u5b9a\u4e49\u5e74\u9f84\u6bb5\uff08\u59820-12\u5c81\u300113-19\u5c81\u300120-35\u5c81\u7b49\uff09\uff0c\u7136\u540e\u901a\u8fc7\u4f20\u5165\u5e74\u9f84\u6570\u636e\u548c\u8fd9\u4e9b\u533a\u95f4\u6765\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u5206\u7c7b\u5217\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n
import pandas as pd\n\n# \u521b\u5efa\u4e00\u4e2a\u5305\u542b\u5e74\u9f84\u7684\u793a\u4f8b\u6570\u636e\u6846\ndata = {'\u5e74\u9f84': [5, 12, 15, 22, 30, 45, 60]}\ndf = pd.DataFrame(data)\n\n# \u5b9a\u4e49\u5e74\u9f84\u533a\u95f4\u548c\u6807\u7b7e\nbins = [0, 12, 19, 35, 60, 100]\nlabels = ['\u513f\u7ae5', '\u9752\u5c11\u5e74', '\u9752\u5e74', '\u4e2d\u5e74', '\u8001\u5e74']\n\n# \u4f7f\u7528cut\u51fd\u6570\u8fdb\u884c\u5206\u7c7b\ndf['\u5e74\u9f84\u5206\u7c7b'] = pd.cut(df['\u5e74\u9f84'], bins=bins, labels=labels, right=False)\n\nprint(df)\n<\/code><\/pre>\n
\u8fd9\u6bb5\u4ee3\u7801\u4f1a\u5c06\u5e74\u9f84\u5206\u4e3a\u4e94\u4e2a\u7c7b\u522b\uff0c\u4fbf\u4e8e\u540e\u7eed\u5206\u6790\u548c\u5904\u7406\u3002<\/p>\n
\u5982\u4f55\u5904\u7406\u7f3a\u5931\u503c\u4ee5\u4fbf\u8fdb\u884c\u5e74\u9f84\u5206\u7c7b\uff1f<\/strong>
\u5904\u7406\u7f3a\u5931\u503c\u662f\u6570\u636e\u5206\u6790\u7684\u91cd\u8981\u6b65\u9aa4\u3002\u5728\u8fdb\u884c\u5e74\u9f84\u5206\u7c7b\u4e4b\u524d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u5e93\u7684fillna<\/code>\u65b9\u6cd5\u6765\u586b\u8865\u7f3a\u5931\u7684\u5e74\u9f84\u6570\u636e\uff0c\u6216\u8005\u4f7f\u7528dropna<\/code>\u65b9\u6cd5\u5220\u9664\u8fd9\u4e9b\u884c\u3002\u786e\u4fdd\u5728\u5206\u7c7b\u4e4b\u524d\u6e05\u6d17\u6570\u636e\uff0c\u4ee5\u63d0\u9ad8\u5206\u7c7b\u7684\u51c6\u786e\u6027\u3002\u4f8b\u5982\uff1a<\/p>\n
df['\u5e74\u9f84'] = df['\u5e74\u9f84'].fillna(df['\u5e74\u9f84'].mean())  # \u7528\u5e73\u5747\u503c\u586b\u8865\n<\/code><\/pre>\n
\u8fd9\u6837\uff0c\u53ef\u4ee5\u786e\u4fdd\u6240\u6709\u6570\u636e\u90fd\u6709\u5e74\u9f84\u4fe1\u606f\uff0c\u4fbf\u4e8e\u540e\u7eed\u5206\u7c7b\u3002<\/p>\n
\u5982\u4f55\u6839\u636e\u5e74\u9f84\u5206\u7c7b\u7ed3\u679c\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\uff1f<\/strong>
\u5728\u5b8c\u6210\u5e74\u9f84\u5206\u7c7b\u540e\uff0c\u60a8\u53ef\u80fd\u5e0c\u671b\u5bf9\u7ed3\u679c\u8fdb\u884c\u53ef\u89c6\u5316\uff0c\u4ee5\u4fbf\u66f4\u76f4\u89c2\u5730\u7406\u89e3\u6570\u636e\u5206\u5e03\u3002\u60a8\u53ef\u4ee5\u4f7f\u7528matplotlib<\/code>\u6216seaborn<\/code>\u7b49\u5e93\u6765\u521b\u5efa\u6761\u5f62\u56fe\u6216\u997c\u56fe\u3002\u4f8b\u5982\uff0c\u60a8\u53ef\u4ee5\u7ed8\u5236\u6bcf\u4e2a\u5e74\u9f84\u5206\u7c7b\u7684\u8ba1\u6570\uff1a<\/p>\n
import matplotlib.pyplot as plt\n\n# \u8ba1\u7b97\u6bcf\u4e2a\u5e74\u9f84\u5206\u7c7b\u7684\u6570\u91cf\nage_counts = df['\u5e74\u9f84\u5206\u7c7b'].value_counts()\n\n# \u7ed8\u5236\u6761\u5f62\u56fe\nage_counts.plot(kind='bar')\nplt.title('\u5e74\u9f84\u5206\u7c7b\u5206\u5e03')\nplt.xlabel('\u5e74\u9f84\u5206\u7c7b')\nplt.ylabel('\u6570\u91cf')\nplt.show()\n<\/code><\/pre>\n
\u901a\u8fc7\u53ef\u89c6\u5316\uff0c\u60a8\u53ef\u4ee5\u66f4\u597d\u5730\u5c55\u793a\u5e74\u9f84\u5206\u7c7b\u7684\u7ed3\u679c\uff0c\u5e76\u4e3a\u51b3\u7b56\u63d0\u4f9b\u4f9d\u636e\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u7528Python\u5c06\u4e00\u7ec4\u5e74\u9f84\u5206\u7c7b\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528\u6761\u4ef6\u5224\u65ad\u3001\u5217\u8868\u63a8\u5bfc\u3001\u5b57\u5178\u6620\u5c04\u7b49\u3002\u4f60\u53ef\u4ee5\u9009\u62e9\u9002\u5408\u81ea\u5df1\u7684\u65b9\u6cd5\u6765\u5b9e\u73b0\u76ee\u6807\u3002 […]","protected":false},"author":3,"featured_media":1110666,"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\/1110656"}],"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=1110656"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1110656\/revisions"}],"predecessor-version":[{"id":1110670,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1110656\/revisions\/1110670"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1110666"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1110656"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1110656"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1110656"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}