使用 MySQL 的 Pandas 0.20.2 to_sql()
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Pandas 0.20.2 to_sql() using MySQL
提问by elPastor
I'm trying to write a dataframe to a MySQL table but am getting a (111 Connection refused)error.
我正在尝试将数据帧写入 MySQL 表，但出现(111 Connection refused)错误。
I followed the accepted answer here: Writing to MySQL database with pandas using SQLAlchemy, to_sql
我按照这里接受的答案进行操作： 使用 SQLAlchemy, to_sql 使用 Pandas 写入 MySQL 数据库
Answer's code:
答案的代码：
import pandas as pd
import mysql.connector
from sqlalchemy import create_engine
engine = create_engine('mysql+mysqlconnector://[user]:[pass]@[host]:[port]/[schema]', echo=False)
data.to_sql(name='sample_table2', con=engine, if_exists = 'append', index=False)
...and the create_engine()line worked without error, but the to_sql()line failed with this error:
...并且该create_engine()行没有错误地工作，但该to_sql()行因此错误而失败：
(mysql.connector.errors.InterfaceError) 2003: Can't connect to MySQL server on 'localhost:3306' (111 Connection refused)
How I connect to my MySQL database / table is not really relevant, so completely different answers are appreciated, but given the deprecation of the MySQL 'flavor' in pandas 0.20.2, what is the proper way to write a dataframe to MySQL?
我如何连接到我的 MySQL 数据库/表并不是真正相关的，所以完全不同的答案值得赞赏，但鉴于Pandas 0.20.2 中 MySQL 'flavor'的弃用，将数据帧写入 MySQL 的正确方法是什么？
回答by elPastor
Thanks to a tip from @AndyHayden, this answerwas the trick. Basically replacing mysqlconnectorwith mysqldbwas the linchpin.
感谢@AndyHayden 的提示，这个答案就是诀窍。基本上取代mysqlconnector的mysqldb是关键。
engine = create_engine('mysql+mysqldb://[user]:[pass]@[host]:[port]/[schema]', echo = False)
df.to_sql(name = 'my_table', con = engine, if_exists = 'append', index = False)
Where [schema]is the database name, and in my particular case, :[port]is omitted with [host]being localhost.
哪里[schema]是数据库名称，并在我的具体情况，:[port]省略与[host]是localhost。
