{"id":1036966,"date":"2024-12-31T12:11:16","date_gmt":"2024-12-31T04:11:16","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1036966.html"},"modified":"2024-12-31T12:11:18","modified_gmt":"2024-12-31T04:11:18","slug":"python%e4%b8%ad%e5%a6%82%e4%bd%95%e5%af%b9%e5%ba%93%e8%a1%a8%e6%a0%bc%e6%95%b0%e6%8d%ae%e6%93%8d%e4%bd%9c","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1036966.html","title":{"rendered":"python\u4e2d\u5982\u4f55\u5bf9\u5e93\u8868\u683c\u6570\u636e\u64cd\u4f5c"},"content":{"rendered":"

\"python\u4e2d\u5982\u4f55\u5bf9\u5e93\u8868\u683c\u6570\u636e\u64cd\u4f5c\"<\/p>\n

\u5728Python\u4e2d\uff0c\u5bf9\u5e93\u8868\u683c\u6570\u636e\u7684\u64cd\u4f5c\u6709\u51e0\u79cd\u65b9\u6cd5\uff1a\u4f7f\u7528Pandas\u5e93\u3001\u4f7f\u7528SQLite\u6570\u636e\u5e93\u3001\u4f7f\u7528SQLAlchemy\u8fdb\u884cORM\u64cd\u4f5c\u3002<\/strong>\u5176\u4e2d\uff0cPandas\u5e93\u662f\u6700\u5e38\u7528\u7684\uff0c\u56e0\u4e3a\u5b83\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u529f\u80fd\u3002\u63a5\u4e0b\u6765\u6211\u4eec\u8be6\u7ec6\u4ecb\u7ecd\u4e00\u4e0b\u5982\u4f55\u4f7f\u7528Pandas\u5e93\u5bf9\u5e93\u8868\u683c\u6570\u636e\u8fdb\u884c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5b89\u88c5\u548c\u5bfc\u5165Pandas\u5e93<\/h3>\n<\/p>\n

\u8981\u4f7f\u7528Pandas\u5e93\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5Pandas\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165Pandas\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u8bfb\u53d6\u548c\u5199\u5165\u6570\u636e<\/h3>\n<\/p>\n
Pandas\u652f\u6301\u591a\u79cd\u683c\u5f0f\u7684\u6570\u636e\u8bfb\u53d6\u548c\u5199\u5165\uff0c\u5305\u62ecCSV\u3001Excel\u3001SQL\u6570\u636e\u5e93\u3001JSON\u7b49\u3002<\/p>\n<\/p>\n
1\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/h4>\n<\/p>\n
df = pd.read_csv('data.csv')<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5199\u5165CSV\u6587\u4ef6<\/h4>\n<\/p>\n
df.to_csv('output.csv', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u8bfb\u53d6Excel\u6587\u4ef6<\/h4>\n<\/p>\n
df = pd.read_excel('data.xlsx', sheet_name='Sheet1')<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u5199\u5165Excel\u6587\u4ef6<\/h4>\n<\/p>\n
df.to_excel('output.xlsx', index=False, sheet_name='Sheet1')<\/p>\n
<\/code><\/pre>\n<\/p>\n
5\u3001\u8bfb\u53d6SQL\u6570\u636e\u5e93<\/h4>\n<\/p>\n
import sqlite3<\/p>\n
conn = sqlite3.connect('example.db')<\/p>\n
df = pd.read_sql_query("SELECT * FROM table_name", conn)<\/p>\n
<\/code><\/pre>\n<\/p>\n
6\u3001\u5199\u5165SQL\u6570\u636e\u5e93<\/h4>\n<\/p>\n
df.to_sql('table_name', conn, if_exists='replace', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u6570\u636e\u64cd\u4f5c<\/h3>\n<\/p>\n
Pandas\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u636e\u64cd\u4f5c\u65b9\u6cd5\uff0c\u5305\u62ec\u9009\u62e9\u3001\u8fc7\u6ee4\u3001\u6392\u5e8f\u3001\u5206\u7ec4\u3001\u5408\u5e76\u7b49\u3002<\/p>\n<\/p>\n
1\u3001\u9009\u62e9\u6570\u636e<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7\u5217\u540d\u3001\u884c\u7d22\u5f15\u7b49\u9009\u62e9\u6570\u636e\u3002<\/p>\n<\/p>\n
# \u9009\u62e9\u7279\u5b9a\u5217<\/p>\n
df['column_name']<\/p>\n
\u9009\u62e9\u591a\u5217<\/strong><\/h2>\n
df[['column1', 'column2']]<\/p>\n
\u9009\u62e9\u7279\u5b9a\u884c<\/strong><\/h2>\n
df.iloc[0]  # \u7b2c\u4e00\u884c<\/p>\n
df.loc[0]   # \u7d22\u5f15\u4e3a0\u7684\u884c<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8fc7\u6ee4\u6570\u636e<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7\u6761\u4ef6\u8868\u8fbe\u5f0f\u8fdb\u884c\u6570\u636e\u8fc7\u6ee4\u3002<\/p>\n<\/p>\n
# \u8fc7\u6ee4\u51fa\u67d0\u5217\u5927\u4e8e\u67d0\u503c\u7684\u884c<\/p>\n
df_filtered = df[df['column_name'] > value]<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u6392\u5e8f\u6570\u636e<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7\u67d0\u5217\u503c\u8fdb\u884c\u6392\u5e8f\u3002<\/p>\n<\/p>\n
# \u6309\u67d0\u5217\u5347\u5e8f\u6392\u5e8f<\/p>\n
df_sorted = df.sort_values(by='column_name')<\/p>\n
\u6309\u591a\u5217\u6392\u5e8f<\/strong><\/h2>\n
df_sorted = df.sort_values(by=['column1', 'column2'], ascending=[True, False])<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u5206\u7ec4\u6570\u636e<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7\u67d0\u5217\u503c\u8fdb\u884c\u5206\u7ec4\uff0c\u5e76\u8fdb\u884c\u805a\u5408\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
# \u6309\u67d0\u5217\u5206\u7ec4\u5e76\u8ba1\u7b97\u5747\u503c<\/p>\n
df_grouped = df.groupby('column_name').mean()<\/p>\n
\u6309\u591a\u5217\u5206\u7ec4\u5e76\u8ba1\u7b97\u603b\u548c<\/strong><\/h2>\n
df_grouped = df.groupby(['column1', 'column2']).sum()<\/p>\n
<\/code><\/pre>\n<\/p>\n
5\u3001\u5408\u5e76\u6570\u636e<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7\u5408\u5e76\u64cd\u4f5c\u5c06\u591a\u4e2aDataFrame\u5408\u5e76\u5728\u4e00\u8d77\u3002<\/p>\n<\/p>\n
# \u6309\u5217\u5408\u5e76<\/p>\n
df_merged = pd.merge(df1, df2, on='key_column')<\/p>\n
\u6309\u884c\u5408\u5e76<\/strong><\/h2>\n
df_concat = pd.concat([df1, df2], axis=0)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u6570\u636e\u6e05\u6d17<\/h3>\n<\/p>\n
\u6570\u636e\u6e05\u6d17\u662f\u6570\u636e\u5206\u6790\u7684\u91cd\u8981\u6b65\u9aa4\uff0cPandas\u63d0\u4f9b\u4e86\u591a\u79cd\u6570\u636e\u6e05\u6d17\u65b9\u6cd5\u3002<\/p>\n<\/p>\n
1\u3001\u5904\u7406\u7f3a\u5931\u503c<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7\u5220\u9664\u6216\u586b\u5145\u7f3a\u5931\u503c\u6765\u5904\u7406\u3002<\/p>\n<\/p>\n
# \u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c<\/p>\n
df.dropna()<\/p>\n
\u586b\u5145\u7f3a\u5931\u503c<\/strong><\/h2>\n
df.fillna(value)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5904\u7406\u91cd\u590d\u503c<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7\u5220\u9664\u91cd\u590d\u503c\u6765\u5904\u7406\u3002<\/p>\n<\/p>\n
# \u5220\u9664\u91cd\u590d\u884c<\/p>\n
df.drop_duplicates()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u6570\u636e\u7c7b\u578b\u8f6c\u6362<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7\u7c7b\u578b\u8f6c\u6362\u51fd\u6570\u6765\u5904\u7406\u3002<\/p>\n<\/p>\n
# \u8f6c\u6362\u6570\u636e\u7c7b\u578b<\/p>\n
df['column_name'] = df['column_name'].astype('int')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u6570\u636e\u53ef\u89c6\u5316<\/h3>\n<\/p>\n
Pandas\u4e0eMatplotlib\u5e93\u96c6\u6210\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5\u548c\u5bfc\u5165Matplotlib\u5e93<\/h4>\n<\/p>\n
pip install matplotlib<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165Matplotlib\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u7ed8\u5236\u6298\u7ebf\u56fe<\/h4>\n<\/p>\n
df.plot(x='column1', y='column2')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u7ed8\u5236\u67f1\u72b6\u56fe<\/h4>\n<\/p>\n
df.plot(kind='bar', x='column1', y='column2')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u7ed8\u5236\u76f4\u65b9\u56fe<\/h4>\n<\/p>\n
df['column_name'].plot(kind='hist')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u4f7f\u7528SQLite\u6570\u636e\u5e93<\/h3>\n<\/p>\n
SQLite\u662f\u4e00\u4e2a\u8f7b\u91cf\u7ea7\u7684\u5173\u7cfb\u578b\u6570\u636e\u5e93\uff0c\u9002\u5408\u5d4c\u5165\u5230\u5e94\u7528\u7a0b\u5e8f\u4e2d\u3002\u53ef\u4ee5\u901a\u8fc7SQLite\u6570\u636e\u5e93\u5bf9\u8868\u683c\u6570\u636e\u8fdb\u884c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5\u548c\u5bfc\u5165SQLite\u5e93<\/h4>\n<\/p>\n
SQLite\u662fPython\u6807\u51c6\u5e93\u7684\u4e00\u90e8\u5206\uff0c\u65e0\u9700\u989d\u5916\u5b89\u88c5\uff0c\u76f4\u63a5\u5bfc\u5165\u5373\u53ef\uff1a<\/p>\n<\/p>\n
import sqlite3<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u521b\u5efa\u6570\u636e\u5e93\u548c\u8868<\/h4>\n<\/p>\n
conn = sqlite3.connect('example.db')<\/p>\n
cursor = conn.cursor()<\/p>\n
cursor.execute('''<\/p>\n
CREATE TABLE IF NOT EXISTS table_name (<\/p>\n
    id INTEGER PRIMARY KEY,<\/p>\n
    column1 TEXT,<\/p>\n
    column2 INTEGER<\/p>\n
)<\/p>\n
''')<\/p>\n
conn.commit()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u63d2\u5165\u6570\u636e<\/h4>\n<\/p>\n
cursor.execute('''<\/p>\n
INSERT INTO table_name (column1, column2)<\/p>\n
VALUES ('value1', 123)<\/p>\n
''')<\/p>\n
conn.commit()<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u67e5\u8be2\u6570\u636e<\/h4>\n<\/p>\n
cursor.execute('SELECT * FROM table_name')<\/p>\n
rows = cursor.fetchall()<\/p>\n
for row in rows:<\/p>\n
    print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
5\u3001\u66f4\u65b0\u6570\u636e<\/h4>\n<\/p>\n
cursor.execute('''<\/p>\n
UPDATE table_name<\/p>\n
SET column2 = 456<\/p>\n
WHERE column1 = 'value1'<\/p>\n
''')<\/p>\n
conn.commit()<\/p>\n
<\/code><\/pre>\n<\/p>\n
6\u3001\u5220\u9664\u6570\u636e<\/h4>\n<\/p>\n
cursor.execute('''<\/p>\n
DELETE FROM table_name<\/p>\n
WHERE column1 = 'value1'<\/p>\n
''')<\/p>\n
conn.commit()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e03\u3001\u4f7f\u7528SQLAlchemy\u8fdb\u884cORM\u64cd\u4f5c<\/h3>\n<\/p>\n
SQLAlchemy\u662f\u4e00\u4e2aPython SQL\u5de5\u5177\u5305\u548c\u5bf9\u8c61\u5173\u7cfb\u6620\u5c04\uff08ORM\uff09\u5e93\uff0c\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u5e93\u64cd\u4f5c\u65b9\u6cd5\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5SQLAlchemy<\/h4>\n<\/p>\n
pip install sqlalchemy<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5bfc\u5165SQLAlchemy<\/h4>\n<\/p>\n
from sqlalchemy import create_engine, Column, Integer, String<\/p>\n
from sqlalchemy.ext.declarative import declarative_base<\/p>\n
from sqlalchemy.orm import sessionmaker<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u521b\u5efa\u6570\u636e\u5e93\u8fde\u63a5\u548c\u8868<\/h4>\n<\/p>\n
engine = create_engine('sqlite:\/\/\/example.db')<\/p>\n
Base = declarative_base()<\/p>\n
class TableName(Base):<\/p>\n
    __tablename__ = 'table_name'<\/p>\n
    id = Column(Integer, primary_key=True)<\/p>\n
    column1 = Column(String)<\/p>\n
    column2 = Column(Integer)<\/p>\n
Base.metadata.create_all(engine)<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u521b\u5efa\u4f1a\u8bdd<\/h4>\n<\/p>\n
Session = sessionmaker(bind=engine)<\/p>\n
session = Session()<\/p>\n
<\/code><\/pre>\n<\/p>\n
5\u3001\u63d2\u5165\u6570\u636e<\/h4>\n<\/p>\n
new_row = TableName(column1='value1', column2=123)<\/p>\n
session.add(new_row)<\/p>\n
session.commit()<\/p>\n
<\/code><\/pre>\n<\/p>\n
6\u3001\u67e5\u8be2\u6570\u636e<\/h4>\n<\/p>\n
rows = session.query(TableName).all()<\/p>\n
for row in rows:<\/p>\n
    print(row.column1, row.column2)<\/p>\n
<\/code><\/pre>\n<\/p>\n
7\u3001\u66f4\u65b0\u6570\u636e<\/h4>\n<\/p>\n
row = session.query(TableName).filter_by(column1='value1').first()<\/p>\n
row.column2 = 456<\/p>\n
session.commit()<\/p>\n
<\/code><\/pre>\n<\/p>\n
8\u3001\u5220\u9664\u6570\u636e<\/h4>\n<\/p>\n
row = session.query(TableName).filter_by(column1='value1').first()<\/p>\n
session.delete(row)<\/p>\n
session.commit()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u5728Python\u4e2d\u5bf9\u5e93\u8868\u683c\u6570\u636e\u8fdb\u884c\u5404\u79cd\u64cd\u4f5c\uff0c\u5305\u62ec\u8bfb\u53d6\u3001\u5199\u5165\u3001\u9009\u62e9\u3001\u8fc7\u6ee4\u3001\u6392\u5e8f\u3001\u5206\u7ec4\u3001\u5408\u5e76\u3001\u6570\u636e\u6e05\u6d17\u3001\u6570\u636e\u53ef\u89c6\u5316\u3001\u4ee5\u53ca\u4f7f\u7528SQLite\u6570\u636e\u5e93\u548cSQLAlchemy\u8fdb\u884c\u6570\u636e\u5e93\u64cd\u4f5c\u3002\u8fd9\u4e9b\u65b9\u6cd5\u4e0d\u4ec5\u4e30\u5bcc\u4e86\u6570\u636e\u5904\u7406\u7684\u624b\u6bb5\uff0c\u4e5f\u63d0\u9ad8\u4e86\u6570\u636e\u5206\u6790\u7684\u6548\u7387\u548c\u51c6\u786e\u6027\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5728Python\u4e2d\uff0c\u5982\u4f55\u8bfb\u53d6\u548c\u5bfc\u5165\u5e93\u8868\u683c\u6570\u636e\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u6765\u8bfb\u53d6\u548c\u5bfc\u5165\u5e93\u8868\u683c\u6570\u636e\u3002\u901a\u8fc7pd.read_csv()<\/code>\u51fd\u6570\u53ef\u4ee5\u8bfb\u53d6CSV\u6587\u4ef6\uff0c\u4f7f\u7528pd.read_excel()<\/code>\u6765\u5904\u7406Excel\u6587\u4ef6\u3002\u786e\u4fdd\u5b89\u88c5\u4e86\u76f8\u5e94\u7684\u5e93\uff0c\u5982openpyxl<\/code>\u6216xlrd<\/code>\uff0c\u4ee5\u4fbf\u652f\u6301Excel\u683c\u5f0f\u7684\u6587\u4ef6\u3002\u8bfb\u53d6\u7684\u6570\u636e\u5c06\u4ee5DataFrame\u7684\u5f62\u5f0f\u5448\u73b0\uff0c\u65b9\u4fbf\u540e\u7eed\u7684\u5206\u6790\u548c\u64cd\u4f5c\u3002<\/p>\n
\u5982\u4f55\u5728Python\u4e2d\u5bf9\u5e93\u8868\u683c\u6570\u636e\u8fdb\u884c\u57fa\u672c\u64cd\u4f5c\uff1f<\/strong>
Pandas\u5e93\u63d0\u4f9b\u4e86\u591a\u79cd\u51fd\u6570\u6765\u5904\u7406\u6570\u636e\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528df.head()<\/code>\u67e5\u770b\u524d\u51e0\u884c\u6570\u636e\uff0c\u4f7f\u7528df.describe()<\/code>\u83b7\u53d6\u6570\u636e\u7684\u7edf\u8ba1\u6458\u8981\u3002\u6b64\u5916\uff0c\u6570\u636e\u7b5b\u9009\u548c\u6392\u5e8f\u540c\u6837\u7b80\u5355\uff0c\u4f7f\u7528df[df['column_name'] > value]<\/code>\u8fdb\u884c\u7b5b\u9009\uff0c\u4f7f\u7528df.sort_values(by='column_name')<\/code>\u8fdb\u884c\u6392\u5e8f\u3002\u901a\u8fc7\u8fd9\u4e9b\u57fa\u672c\u64cd\u4f5c\uff0c\u7528\u6237\u53ef\u4ee5\u8f7b\u677e\u63a2\u7d22\u548c\u5206\u6790\u6570\u636e\u3002<\/p>\n
\u5728Python\u4e2d\u5982\u4f55\u5bf9\u5e93\u8868\u683c\u6570\u636e\u8fdb\u884c\u6570\u636e\u6e05\u6d17\uff1f<\/strong>
\u6570\u636e\u6e05\u6d17\u662f\u6570\u636e\u5904\u7406\u4e2d\u7684\u91cd\u8981\u73af\u8282\u3002\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u6765\u5904\u7406\u7f3a\u5931\u503c\u3001\u91cd\u590d\u6570\u636e\u7b49\u95ee\u9898\u3002\u901a\u8fc7df.dropna()<\/code>\u53ef\u4ee5\u5220\u9664\u542b\u6709\u7f3a\u5931\u503c\u7684\u884c\uff0cdf.fillna(value)<\/code>\u53ef\u4ee5\u7528\u7279\u5b9a\u503c\u586b\u5145\u7f3a\u5931\u503c\u3002\u5bf9\u4e8e\u91cd\u590d\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528df.drop_duplicates()<\/code>\u6765\u53bb\u9664\u3002\u6570\u636e\u6e05\u6d17\u7684\u8fc7\u7a0b\u786e\u4fdd\u6570\u636e\u7684\u8d28\u91cf\uff0c\u4e3a\u540e\u7eed\u5206\u6790\u5960\u5b9a\u57fa\u7840\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u5bf9\u5e93\u8868\u683c\u6570\u636e\u7684\u64cd\u4f5c\u6709\u51e0\u79cd\u65b9\u6cd5\uff1a\u4f7f\u7528Pandas\u5e93\u3001\u4f7f\u7528SQLite\u6570\u636e\u5e93\u3001\u4f7f\u7528SQLAlch […]","protected":false},"author":3,"featured_media":1036979,"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\/1036966"}],"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=1036966"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1036966\/revisions"}],"predecessor-version":[{"id":1036984,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1036966\/revisions\/1036984"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1036979"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1036966"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1036966"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1036966"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}