pd.concat

import numpy as np
import pandas as pd
df1=pd.DataFrame(np.ones((3,4))*0,columns=['a','b','c','d'])
df2=pd.DataFrame(np.ones((3,4))*1,columns=['a','b','c','d'])
df3=pd.DataFrame(np.ones((3,4))*2,columns=['a','b','c','d'])

     a    b    c    d
0  0.0  0.0  0.0  0.0
1  0.0  0.0  0.0  0.0
2  0.0  0.0  0.0  0.0
     a    b    c    d
0  1.0  1.0  1.0  1.0
1  1.0  1.0  1.0  1.0
2  1.0  1.0  1.0  1.0
     a    b    c    d
0  2.0  2.0  2.0  2.0
1  2.0  2.0  2.0  2.0
2  2.0  2.0  2.0  2.0

frame1 = pd.concat([df1,df2,df3],axis=0)#0为纵向，1为横向   一般合并都是选取1

print(frame1)

pd.concat([df1,df2],axis=1)  #进行纵向合并

a	b	c	d	a	b	c	d
0	0.0	0.0	0.0	0.0	1.0	1.0	1.0	1.0
1	0.0	0.0	0.0	0.0	1.0	1.0	1.0	1.0
2	0.0	0.0	0.0	0.0	1.0	1.0	1.0	1.0

res=pd.concat([df1,df2,df3],axis=0)#0为纵向，1为横向 
print(res)
    a    b    c    d
0  0.0  0.0  0.0  0.0
1  0.0  0.0  0.0  0.0
2  0.0  0.0  0.0  0.0
0  1.0  1.0  1.0  1.0
1  1.0  1.0  1.0  1.0
2  1.0  1.0  1.0  1.0
0  2.0  2.0  2.0  2.0
1  2.0  2.0  2.0  2.0
2  2.0  2.0  2.0  2.0

但是上面的结果有索引重复，去除索引重复可以采用ignore_index属性

res=pd.concat([df1,df2,df3],axis=0,ignore_index=True)#0为纵向，1为横向
print(res)

     a    b    c    d
0  0.0  0.0  0.0  0.0
1  0.0  0.0  0.0  0.0
2  0.0  0.0  0.0  0.0
3  1.0  1.0  1.0  1.0
4  1.0  1.0  1.0  1.0
5  1.0  1.0  1.0  1.0
6  2.0  2.0  2.0  2.0
7  2.0  2.0  2.0  2.0
8  2.0  2.0  2.0  2.0