https://w.electrodragon.com/w/index.php?action=history&feed=atom&title=Pandas 2026-07-24T03:57:15Z Revision history for this page on the wiki MediaWiki 1.37.2 https://w.electrodragon.com/w/index.php?title=Pandas&diff=26274&oldid=prev 2020-05-02T15:27:00Z

<p></p> <p><b>New page</b></p><div>apt-get install python-pandas<br /> &lt;br&gt;<br /> <br /> dependencies: [[numpy]], [[versioneer]]<br /> * pip install pandas==0.24.2<br /> <br /> <br /> == Pandas MYSQL ==<br /> * https://segmentfault.com/a/1190000014210743<br /> <br /> # -*- coding: utf-8 -*-<br /> <br /> # 导入必要模块<br /> import pandas as pd<br /> from sqlalchemy import create_engine<br /> <br /> # 初始化数据库连接，使用pymysql模块<br /> # MySQL的用户：root, 密码:147369, 端口：3306,数据库：mydb<br /> engine = create_engine('mysql+pymysql://root:147369@localhost:3306/mydb')<br /> <br /> # 查询语句，选出employee表中的所有数据<br /> sql = '''<br /> select * from employee;<br /> '''<br /> <br /> # read_sql_query的两个参数: sql语句， 数据库连接<br /> df = pd.read_sql_query(sql, engine)<br /> <br /> # 输出employee表的查询结果<br /> print(df)<br /> <br /> # 新建pandas中的DataFrame, 只有id,num两列<br /> df = pd.DataFrame({'id':[1,2,3,4],'num':[12,34,56,89]})<br /> <br /> # 将新建的DataFrame储存为MySQL中的数据表，不储存index列<br /> df.to_sql('mydf', engine, index= False)<br /> <br /> print('Read from and write to Mysql table successfully!')<br /> <br /> == Pandas HTML ==<br /> * https://www.cjavapy.com/article/209/<br /> <br /> * df.to_html<br /> <br /> [[category: Python]]</div>

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