![\"python\u5982\u4f55\u63d0\u53d6\u6570\u636e\u96c6\u91cc\u7684\u6570\"](\"https:\/\/cdn-docs.pingcode.com\/wp-content\/uploads\/2024\/12\/f8cbdf2e-f444-48c2-833a-56b67029f9b7.webp?x-oss-process=image\/auto-orient,1\/format,webp\")
<\/p>\n<\/p>\n
Python \u5982\u4f55\u63d0\u53d6\u6570\u636e\u96c6\u91cc\u7684\u6570<\/strong><\/p>\n<\/p>\n \u5728Python\u4e2d\uff0c\u63d0\u53d6\u6570\u636e\u96c6\u91cc\u7684\u6570\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u6765\u5b9e\u73b0\uff0c\u4e3b\u8981\u5305\u62ec\u4f7f\u7528\u5185\u7f6e\u7684\u6587\u4ef6\u64cd\u4f5c\u51fd\u6570\u3001Pandas\u5e93\u3001Numpy\u5e93\u7b49\u3002\u4f7f\u7528\u5185\u7f6e\u7684\u6587\u4ef6\u64cd\u4f5c\u51fd\u6570\u3001Pandas\u5e93\u3001Numpy\u5e93<\/strong>\u662f\u6700\u5e38\u89c1\u7684\u65b9\u6cd5\u3002\u6211\u4eec\u5c06\u6df1\u5165\u63a2\u8ba8\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u5de5\u5177\u6765\u63d0\u53d6\u6570\u636e\u96c6\u91cc\u7684\u6570\uff0c\u5e76\u4e14\u8be6\u7ec6\u4ecb\u7ecd\u5176\u4e2d\u7684\u4e00\u4e2a\u65b9\u6cd5\u3002<\/p>\n<\/p>\n \u4f7f\u7528Python\u7684\u5185\u7f6e\u6587\u4ef6\u64cd\u4f5c\u51fd\u6570\uff0c\u4f60\u53ef\u4ee5\u8bfb\u53d6\u5404\u79cd\u683c\u5f0f\u7684\u6570\u636e\u6587\u4ef6\uff0c\u5982\u6587\u672c\u6587\u4ef6\uff08.txt\uff09\u3001CSV\u6587\u4ef6\uff08.csv\uff09\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u7528\u7684\u6587\u4ef6\u64cd\u4f5c\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n with open('data.txt', 'r') as file:<\/p>\n data = file.readlines()<\/p>\n # \u63d0\u53d6\u6570\u503c<\/p>\n numbers = [float(line.strip()) for line in data]<\/p>\n print(numbers)<\/p>\n <\/code><\/pre>\n<\/p>\n with open('data.csv', 'r') as file:<\/p>\n reader = csv.reader(file)<\/p>\n # \u63d0\u53d6\u6570\u503c<\/p>\n numbers = [float(row[0]) for row in reader]<\/p>\n print(numbers)<\/p>\n <\/code><\/pre>\n<\/p>\n Pandas\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5e93\uff0c\u7279\u522b\u9002\u7528\u4e8e\u5904\u7406\u7ed3\u6784\u5316\u6570\u636e\uff0c\u5982\u8868\u683c\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528Pandas\u8bfb\u53d6\u6570\u636e\u96c6\u5e76\u63d0\u53d6\u6570\u503c\u7684\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n data = pd.read_csv('data.csv')<\/p>\n numbers = data['column_name'].values<\/p>\n print(numbers)<\/p>\n <\/code><\/pre>\n<\/p>\n data = pd.read_excel('data.xlsx')<\/p>\n numbers = data['column_name'].values<\/p>\n print(numbers)<\/p>\n <\/code><\/pre>\n<\/p>\n Numpy\u662f\u4e00\u4e2a\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u7ec4\u64cd\u4f5c\u529f\u80fd\u3002\u4f60\u53ef\u4ee5\u4f7f\u7528Numpy\u6765\u8bfb\u53d6\u548c\u5904\u7406\u6570\u636e\u96c6\u3002<\/p>\n<\/p>\n data = np.loadtxt('data.txt')<\/p>\n print(data)<\/p>\n <\/code><\/pre>\n<\/p>\n data = np.genfromtxt('data.csv', delimiter=',')<\/p>\n print(data)<\/p>\n <\/code><\/pre>\n<\/p>\n SQLite\u662f\u4e00\u4e2a\u8f7b\u91cf\u7ea7\u7684\u5173\u7cfb\u578b\u6570\u636e\u5e93\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528SQLite\u6765\u5b58\u50a8\u548c\u8bfb\u53d6\u6570\u636e\u96c6\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528SQLite\u8bfb\u53d6\u6570\u636e\u96c6\u5e76\u63d0\u53d6\u6570\u503c\u7684\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n conn = sqlite3.connect('data.db')<\/p>\n cursor = conn.cursor()<\/p>\n cursor.execute("SELECT column_name FROM table_name")<\/p>\n numbers = [row[0] for row in cursor.fetchall()]<\/p>\n print(numbers)<\/p>\n conn.close()<\/p>\n <\/code><\/pre>\n<\/p>\n JSON\u662f\u4e00\u79cd\u8f7b\u91cf\u7ea7\u7684\u6570\u636e\u4ea4\u6362\u683c\u5f0f\uff0c\u5e7f\u6cdb\u7528\u4e8e\u6570\u636e\u5b58\u50a8\u548c\u4f20\u8f93\u3002\u4f60\u53ef\u4ee5\u4f7f\u7528Python\u7684\u5185\u7f6e\u5e93json\u6765\u8bfb\u53d6JSON\u6587\u4ef6\u5e76\u63d0\u53d6\u6570\u503c\u3002<\/p>\n<\/p>\n with open('data.json', 'r') as file:<\/p>\n data = json.load(file)<\/p>\n numbers = data['key_name']<\/p>\n print(numbers)<\/p>\n <\/code><\/pre>\n<\/p>\n \u6709\u4e9b\u6570\u636e\u96c6\u662f\u901a\u8fc7API\u63a5\u53e3\u63d0\u4f9b\u7684\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528requests\u5e93\u6765\u53d1\u9001HTTP\u8bf7\u6c42\u5e76\u83b7\u53d6\u6570\u636e\u3002<\/p>\n<\/p>\n response = requests.get('https:\/\/api.example.com\/data')<\/p>\n data = response.json()<\/p>\n numbers = data['key_name']<\/p>\n print(numbers)<\/p>\n <\/code><\/pre>\n<\/p>\n \u6709\u65f6\u5019\u6570\u636e\u96c6\u53ef\u80fd\u5305\u542b\u590d\u6742\u7684\u6570\u636e\u7ed3\u6784\uff0c\u5982\u5d4c\u5957\u5217\u8868\u6216\u5b57\u5178\u3002\u4f60\u53ef\u4ee5\u4f7f\u7528\u9012\u5f52\u51fd\u6570\u6765\u63d0\u53d6\u6570\u503c\u3002<\/p>\n<\/p>\n numbers = []<\/p>\n if isinstance(data, dict):<\/p>\n for value in data.values():<\/p>\n numbers.extend(extract_numbers(value))<\/p>\n elif isinstance(data, list):<\/p>\n for item in data:<\/p>\n numbers.extend(extract_numbers(item))<\/p>\n elif isinstance(data, (int, float)):<\/p>\n numbers.append(data)<\/p>\n return numbers<\/p>\n data = {<\/p>\n 'a': 1,<\/p>\n 'b': [2, 3, {'c': 4}],<\/p>\n 'd': {'e': 5, 'f': [6, 7]}<\/p>\n }<\/p>\n numbers = extract_numbers(data)<\/p>\n print(numbers)<\/p>\n <\/code><\/pre>\n<\/p>\n \u5bf9\u4e8e\u5927\u6570\u636e\u96c6\uff0c\u5185\u5b58\u4f7f\u7528\u548c\u5904\u7406\u901f\u5ea6\u53ef\u80fd\u662f\u4e00\u4e2a\u95ee\u9898\u3002\u4f60\u53ef\u4ee5\u4f7f\u7528Pandas\u7684\u5206\u5757\u8bfb\u53d6\u529f\u80fd\u6216Dask\u5e93\u6765\u5904\u7406\u5927\u6570\u636e\u96c6\u3002<\/p>\n<\/p>\n chunk_size = 10000<\/p>\n chunks = pd.read_csv('large_data.csv', chunksize=chunk_size)<\/p>\n numbers = []<\/p>\n for chunk in chunks:<\/p>\n numbers.extend(chunk['column_name'].values)<\/p>\n print(numbers)<\/p>\n <\/code><\/pre>\n<\/p>\n data = dd.read_csv('large_data.csv')<\/p>\n numbers = data['column_name'].compute()<\/p>\n print(numbers)<\/p>\n <\/code><\/pre>\n<\/p>\n \u5728\u63d0\u53d6\u6570\u636e\u4e4b\u524d\uff0c\u901a\u5e38\u9700\u8981\u8fdb\u884c\u6570\u636e\u9884\u5904\u7406\u548c\u6e05\u6d17\uff0c\u5982\u5904\u7406\u7f3a\u5931\u503c\u3001\u6570\u636e\u8f6c\u6362\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u7528\u7684\u6570\u636e\u9884\u5904\u7406\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n data = pd.read_csv('data.csv')<\/p>\n data['column_name'].fillna(0, inplace=True)<\/p>\n numbers = data['column_name'].values<\/p>\n print(numbers)<\/p>\n <\/code><\/pre>\n<\/p>\n data = pd.read_csv('data.csv')<\/p>\n data['column_name'] = data['column_name'].astype(float)<\/p>\n numbers = data['column_name'].values<\/p>\n print(numbers)<\/p>\n <\/code><\/pre>\n<\/p>\n \u5728\u63d0\u53d6\u6570\u636e\u5e76\u8fdb\u884c\u5206\u6790\u540e\uff0c\u901a\u5e38\u9700\u8981\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u3002\u4f60\u53ef\u4ee5\u4f7f\u7528Matplotlib\u6216Seaborn\u5e93\u6765\u521b\u5efa\u56fe\u8868\u548c\u53ef\u89c6\u5316\u6570\u636e\u3002<\/p>\n<\/p>\n plt.plot(numbers)<\/p>\n plt.xlabel('Index')<\/p>\n plt.ylabel('Value')<\/p>\n plt.title('Data Visualization')<\/p>\n plt.show()<\/p>\n <\/code><\/pre>\n<\/p>\n sns.histplot(numbers, kde=True)<\/p>\n plt.xlabel('Value')<\/p>\n plt.ylabel('Frequency')<\/p>\n plt.title('Data Distribution')<\/p>\n plt.show()<\/p>\n <\/code><\/pre>\n<\/p>\n \u901a\u8fc7\u4ee5\u4e0a\u65b9\u6cd5\uff0c\u4f60\u53ef\u4ee5\u9ad8\u6548\u5730\u63d0\u53d6\u6570\u636e\u96c6\u91cc\u7684\u6570\uff0c\u5e76\u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u5206\u6790\u548c\u5904\u7406\u3002\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u53d6\u51b3\u4e8e\u4f60\u7684\u6570\u636e\u683c\u5f0f\u548c\u9700\u6c42\u3002\u65e0\u8bba\u662f\u7b80\u5355\u7684\u6587\u672c\u6587\u4ef6\u8bfb\u53d6\uff0c\u8fd8\u662f\u590d\u6742\u7684API\u6570\u636e\u83b7\u53d6\uff0cPython\u90fd\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u5de5\u5177\u548c\u5e93\u6765\u652f\u6301\u4f60\u7684\u6570\u636e\u5904\u7406\u5de5\u4f5c\u3002<\/p>\n<\/p>\n \u5982\u4f55\u4f7f\u7528Python\u63d0\u53d6\u6570\u636e\u96c6\u4e2d\u7684\u7279\u5b9a\u5217\uff1f<\/strong> \u5982\u4f55\u5904\u7406\u7f3a\u5931\u503c\u4ee5\u63d0\u53d6\u5e72\u51c0\u7684\u6570\u636e\uff1f<\/strong> \u5982\u4f55\u4ece\u5927\u578b\u6570\u636e\u96c6\u4e2d\u63d0\u53d6\u6837\u672c\u6570\u636e\u8fdb\u884c\u5206\u6790\uff1f<\/strong>\u4e00\u3001\u4f7f\u7528\u5185\u7f6e\u7684\u6587\u4ef6\u64cd\u4f5c\u51fd\u6570<\/h3>\n<\/p>\n
1\u3001\u8bfb\u53d6\u6587\u672c\u6587\u4ef6<\/h4>\n<\/p>\n
# \u6253\u5f00\u5e76\u8bfb\u53d6\u6587\u672c\u6587\u4ef6<\/p>\n2\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/h4>\n<\/p>\n
import csv<\/p>\n\u6253\u5f00\u5e76\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
\u4e8c\u3001\u4f7f\u7528Pandas\u5e93<\/h3>\n<\/p>\n
1\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/h4>\n<\/p>\n
import pandas as pd<\/p>\n\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
\u63d0\u53d6\u7279\u5b9a\u5217\u7684\u6570\u503c<\/strong><\/h2>\n
2\u3001\u8bfb\u53d6Excel\u6587\u4ef6<\/h4>\n<\/p>\n
import pandas as pd<\/p>\n\u8bfb\u53d6Excel\u6587\u4ef6<\/strong><\/h2>\n
\u63d0\u53d6\u7279\u5b9a\u5217\u7684\u6570\u503c<\/strong><\/h2>\n
\u4e09\u3001\u4f7f\u7528Numpy\u5e93<\/h3>\n<\/p>\n
1\u3001\u4ece\u6587\u672c\u6587\u4ef6\u8bfb\u53d6\u6570\u636e<\/h4>\n<\/p>\n
import numpy as np<\/p>\n\u4ece\u6587\u672c\u6587\u4ef6\u8bfb\u53d6\u6570\u636e<\/strong><\/h2>\n
\u63d0\u53d6\u6570\u503c<\/strong><\/h2>\n
2\u3001\u4eceCSV\u6587\u4ef6\u8bfb\u53d6\u6570\u636e<\/h4>\n<\/p>\n
import numpy as np<\/p>\n\u4eceCSV\u6587\u4ef6\u8bfb\u53d6\u6570\u636e<\/strong><\/h2>\n
\u63d0\u53d6\u6570\u503c<\/strong><\/h2>\n
\u56db\u3001\u4f7f\u7528SQLite\u6570\u636e\u5e93<\/h3>\n<\/p>\n
1\u3001\u8bfb\u53d6SQLite\u6570\u636e\u5e93<\/h4>\n<\/p>\n
import sqlite3<\/p>\n\u8fde\u63a5\u5230SQLite\u6570\u636e\u5e93<\/strong><\/h2>\n
\u6267\u884c\u67e5\u8be2\u5e76\u63d0\u53d6\u6570\u503c<\/strong><\/h2>\n
\u5173\u95ed\u8fde\u63a5<\/strong><\/h2>\n
\u4e94\u3001\u4f7f\u7528JSON\u6587\u4ef6<\/h3>\n<\/p>\n
1\u3001\u8bfb\u53d6JSON\u6587\u4ef6<\/h4>\n<\/p>\n
import json<\/p>\n\u8bfb\u53d6JSON\u6587\u4ef6<\/strong><\/h2>\n
\u63d0\u53d6\u7279\u5b9a\u952e\u7684\u6570\u503c<\/strong><\/h2>\n
\u516d\u3001\u4f7f\u7528API\u63a5\u53e3<\/h3>\n<\/p>\n
1\u3001\u4f7f\u7528API\u63a5\u53e3\u83b7\u53d6\u6570\u636e<\/h4>\n<\/p>\n
import requests<\/p>\n\u53d1\u9001HTTP\u8bf7\u6c42\u83b7\u53d6\u6570\u636e<\/strong><\/h2>\n
\u63d0\u53d6\u7279\u5b9a\u952e\u7684\u6570\u503c<\/strong><\/h2>\n
\u4e03\u3001\u5904\u7406\u590d\u6742\u6570\u636e\u7ed3\u6784<\/h3>\n<\/p>\n
1\u3001\u5904\u7406\u5d4c\u5957\u5217\u8868\u548c\u5b57\u5178<\/h4>\n<\/p>\n
def extract_numbers(data):<\/p>\n\u793a\u4f8b\u6570\u636e<\/strong><\/h2>\n
\u63d0\u53d6\u6570\u503c<\/strong><\/h2>\n
\u516b\u3001\u5904\u7406\u5927\u6570\u636e\u96c6<\/h3>\n<\/p>\n
1\u3001\u4f7f\u7528Pandas\u5206\u5757\u8bfb\u53d6<\/h4>\n<\/p>\n
import pandas as pd<\/p>\n\u5206\u5757\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
2\u3001\u4f7f\u7528Dask\u5e93<\/h4>\n<\/p>\n
import dask.dataframe as dd<\/p>\n\u8bfb\u53d6\u5927\u6570\u636e\u96c6<\/strong><\/h2>\n
\u63d0\u53d6\u7279\u5b9a\u5217\u7684\u6570\u503c<\/strong><\/h2>\n
\u4e5d\u3001\u6570\u636e\u9884\u5904\u7406\u548c\u6e05\u6d17<\/h3>\n<\/p>\n
1\u3001\u5904\u7406\u7f3a\u5931\u503c<\/h4>\n<\/p>\n
import pandas as pd<\/p>\n\u8bfb\u53d6\u6570\u636e<\/strong><\/h2>\n
\u586b\u5145\u7f3a\u5931\u503c<\/strong><\/h2>\n
\u63d0\u53d6\u6570\u503c<\/strong><\/h2>\n
2\u3001\u6570\u636e\u8f6c\u6362<\/h4>\n<\/p>\n
import pandas as pd<\/p>\n\u8bfb\u53d6\u6570\u636e<\/strong><\/h2>\n
\u6570\u636e\u8f6c\u6362<\/strong><\/h2>\n
\u63d0\u53d6\u6570\u503c<\/strong><\/h2>\n
\u5341\u3001\u6570\u636e\u53ef\u89c6\u5316<\/h3>\n<\/p>\n
1\u3001\u4f7f\u7528Matplotlib<\/h4>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n\u521b\u5efa\u56fe\u8868<\/strong><\/h2>\n
2\u3001\u4f7f\u7528Seaborn<\/h4>\n<\/p>\n
import seaborn as sns<\/p>\n\u521b\u5efa\u56fe\u8868<\/strong><\/h2>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u8f7b\u677e\u63d0\u53d6\u6570\u636e\u96c6\u4e2d\u7684\u7279\u5b9a\u5217\u3002\u9996\u5148\uff0c\u60a8\u9700\u8981\u5bfc\u5165Pandas\u5e76\u8bfb\u53d6\u6570\u636e\u96c6\u3002\u901a\u8fc7DataFrame<\/code>\u5bf9\u8c61\uff0c\u53ef\u4ee5\u4f7f\u7528\u5217\u540d\u76f4\u63a5\u8bbf\u95ee\u6240\u9700\u7684\u5217\u3002\u4f8b\u5982\uff0c\u5982\u679c\u60a8\u7684\u6570\u636e\u96c6\u5305\u542b\u540d\u4e3a\u201c\u5e74\u9f84\u201d\u7684\u5217\uff0c\u53ef\u4ee5\u4f7f\u7528data['\u5e74\u9f84']<\/code>\u6765\u63d0\u53d6\u8fd9\u4e00\u5217\u3002<\/p>\n
\u5728\u6570\u636e\u5206\u6790\u4e2d\uff0c\u7f3a\u5931\u503c\u662f\u5e38\u89c1\u7684\u95ee\u9898\u3002\u4f7f\u7528Pandas\u5e93\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7dropna()<\/code>\u65b9\u6cd5\u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c\uff0c\u6216\u8005\u4f7f\u7528fillna()<\/code>\u65b9\u6cd5\u7528\u7279\u5b9a\u503c\u66ff\u6362\u7f3a\u5931\u503c\u3002\u8fd9\u6837\u53ef\u4ee5\u786e\u4fdd\u60a8\u63d0\u53d6\u7684\u6570\u636e\u66f4\u52a0\u5e72\u51c0\u548c\u53ef\u9760\u3002<\/p>\n
\u5982\u679c\u60a8\u7684\u6570\u636e\u96c6\u975e\u5e38\u5927\uff0c\u63d0\u53d6\u6574\u4e2a\u6570\u636e\u96c6\u53ef\u80fd\u4f1a\u5bfc\u81f4\u6027\u80fd\u95ee\u9898\u3002\u53ef\u4ee5\u4f7f\u7528Pandas\u7684sample()<\/code>\u65b9\u6cd5\uff0c\u4ece\u6570\u636e\u96c6\u4e2d\u968f\u673a\u63d0\u53d6\u4e00\u4e2a\u6837\u672c\u3002\u4f8b\u5982\uff0cdata.sample(frac=0.1)<\/code>\u5c06\u4ece\u6570\u636e\u96c6\u4e2d\u968f\u673a\u63d0\u53d610%\u7684\u6570\u636e\u3002\u8fd9\u79cd\u65b9\u6cd5\u5bf9\u4e8e\u521d\u6b65\u5206\u6790\u548c\u6a21\u578b\u8bad\u7ec3\u975e\u5e38\u6709\u7528\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python \u5982\u4f55\u63d0\u53d6\u6570\u636e\u96c6\u91cc\u7684\u6570 \u5728Python\u4e2d\uff0c\u63d0\u53d6\u6570\u636e\u96c6\u91cc\u7684\u6570\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u6765\u5b9e\u73b0\uff0c\u4e3b\u8981\u5305\u62ec\u4f7f\u7528\u5185\u7f6e […]","protected":false},"author":3,"featured_media":1063469,"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\/1063463"}],"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=1063463"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1063463\/revisions"}],"predecessor-version":[{"id":1063474,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1063463\/revisions\/1063474"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1063469"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1063463"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1063463"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1063463"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}