python pandas to_sql import excel data into MySQL database or how mysql to excel is the easiest way

Use excle table to import mysql data

 

import pandas as pd
from  sqlalchemy import  create_engine


r=pd.read_excel('python.xlsx')
engine =create_engine('mysql+pymysql://username:user password@database address')#database database name, password user password
r.to_sql('python',con =engine,if_exists='replace',index=False)#The name of the table in the database,
print("Successfully imported into the database!")

Just a few sentences, but there may be many problems. Let me talk about the url format of create_engine first. Needless to say the user name and password, address:port is the ip address and port number to connect to MySQL (default localhost:3306), the database name is the database to be connected to, the character encoding is very important, if you want to insert Chinese, use utf8

Several parameters of to_sql:

  • name is the table name
  • con is connection
  • if_exists: What to do if the table exists
    • append: append
    • replace: delete the original table, create a new table and add
    • fail: do nothing
  • index=False: Do not insert index index

Use mysql to export execle

import pandas as pd
from sqlalchemy import create_engine

connect=create_engine('mysql+pymysql://username:user password@database address')
sql = "SELECT * FROM user "
data = pd.read_sql(sql,connect)

writer = pd.ExcelWriter("hello_data.xlsx")
data.to_excel(writer,sheet_name = "data",index=None) #导出成excel
writer.save()

print("Successfully imported excle form!")

 

Prerequisites must install project components

Guess you like

Origin blog.csdn.net/youyouxiong/article/details/109735768