The difference between concat (), merge () is

The difference between concat, merge the

In [154]:

data1=pd.DataFrame(np.arange(6).reshape(2,3),columns=list('abc'))

data2=pd.DataFrame(np.arange(20,26).reshape(2,3),columns=list('ayz'))

 

In [155]:

data1

 

 

Out[155]:

	a	b	c
0	0	1	2
1	3	4	5

In [170]:

dd=pd.DataFrame(np.arange(6).reshape(2,3),columns=list('acb'))

 

 

In [171]:

 

dd

 

 

Out[171]:

	a	c	b
0	0	1	2
1	3	4	5

In [172]:

 

PD. the concat ([ DATAl, dd]) ## column variables can automatically align the concat

Out[172]:

	a	b	c
0	0	1	2
1	3	4	5
0	0	2	1
1	3	5	4

In [156]:

data2

 

 

Out[156]:

	a	Y	with
0	20	21	22
1	23	24	25

In [164]:

  data3 =pd.concat([data1,data2],axis=0)

data3

 

Out[164]:

	a	b	c	Y	with
0	0	1.0	2.0	NaN	NaN
1	3	4.0	5.0	NaN	NaN
0	20	NaN	NaN	21.0	22.0
1	23	NaN	NaN	24.0	25.0

In [160]:

 

data4=pd.concat([data1,data2],axis=1)

data4

 

 

Out[160]:

	a	b	c	a	Y	with
0	0	1	2	20	21	22
1	3	4	5	23	24	25

In [162]:

  data5 =pd.concat([data1,data2],axis=1,join='inner')

data5

 

 

Out[162]:

	a	b	c	a	Y	with
0	0	1	2	20	21	22
1	3	4	5	23	24	25

In [167]:

 

data01=pd.merge(data1,data2,on='a')

Date01

 

 

Out[167]:

	a	b	c	Y	with

In [169]:

  data02 =pd.merge(data1,data2,on='a',how='outer')

Date02

 

 

Out[169]:

	a	b	c	Y	with
0	0	1.0	2.0	NaN	NaN
1	3	4.0	5.0	NaN	NaN
2	20	NaN	NaN	21.0	22.0
3	23	NaN	NaN	24.0	25.0