pandas学习-pandas读取数据库、csv、excel

一、连接mysql

1.事前准备

我们准备一个数据库，数据库一张表user，字段如下，乱起的名字不要在意哈

上代码，代码比较简单，不用注释也能看懂

import pandas as pd
from sqlalchemy import create_engine

engine = create_engine('mysql+pymysql://root:root@localhost:3306/test')
sql = "select * from user"
df = pd.read_sql_query(sql, engine)
print(df)

打印结果

 比较大小

import pandas as pd
from sqlalchemy import create_engine

engine = create_engine('mysql+pymysql://root:root@localhost:3306/test')
sql = "select * from user"
df = pd.read_sql_query(sql, engine)
print(df)
print("筛选")
#print(df[df.id>2])
print(df[(df.id>2) & (df.age >1000)]) #and
print(df[(df.id>3) | (df.age<50)])   #or

 

当你需要将一列作为变量的时候，就像下面这样就可以

import pandas as pd
from sqlalchemy import create_engine

engine = create_engine('mysql+pymysql://root:kWYM6%pnbVnvsR4K@localhost:3306/citystudy')
sql = "select * from t_user"
df = pd.read_sql_query(sql, engine)
print(df)
tmp = 'id'
print(df[df[tmp]>2])

 字符串也可以筛选

print(df[df[tmp].str.contains('ER')])              #包含ER的字符串
print(df[df[tmp].str.contains('ER')==False])       #不包含ER的字符串