pandas equivalent of R's cbind (concatenate/stack vectors vertically)

Question

suppose I have two dataframes:

import pandas
....
....
test1 = pandas.DataFrame([1,2,3,4,5])
....
....
test2 = pandas.DataFrame([4,2,1,3,7])
....

I tried test1.append(test2) but it is the equivalent of R's rbind.

How can I combine the two as two columns of a dataframe similar to the cbind function in R?

have you considered changing which answer is accepted? I think Feng Mai's answer is far more complete. — cphlewis, Aug 23 '22 at 16:51
Sorry, I needed the answer in 2015, not in 2021 !!! Not fair to change the answer - particularly not fair to the person who responded to me 7 years ago when I needed the answer — uday, Sep 07 '22 at 02:22
I don’t like to go back 7 years ago. I appreciate you answering the question back then, but it’s no point in getting an answer 7 years later when I have long left Python for C# / Java and not interested in the answer anymore — uday, Sep 07 '22 at 02:24

cphlewis · Accepted Answer · 2022-09-07T23:33:55.620

80

test3 = pd.concat([test1, test2], axis=1)
test3.columns = ['a','b']

(But see the detailed answer by @feng-mai, below)

edited Sep 07 '22 at 23:33

answered Feb 18 '15 at 23:11

cphlewis

15,759
4
46
55

8

I did this, and it's adding rows, as if it's a join -- which is not what I want at all. – one_observation Nov 07 '16 at 19:30
Is `axis=2` what you want? – cphlewis Nov 07 '16 at 19:31
2

Just for completeness: http://stackoverflow.com/questions/33088010/pandas-column-bind-cbind-two-data-frames – Gaurav Taneja Dec 06 '16 at 00:22
2

axis = 0 is what you want. – Jack Armstrong Apr 07 '20 at 15:53
@one_observation the answer from Feng Mai addresses this crucial issue and is superior, in my estimation as it more faithfully behaves like R cbind. https://stackoverflow.com/a/69874400/122792 – Thomas Browne Aug 21 '22 at 21:26

Feng Mai · Answer 2 · 2021-11-29T22:58:30.717

There is a key difference between concat(axis = 1) in pandas and cbind() in R:

concat attempts to merge/align by index. There is no concept of index in a R dataframe. If the two pandas dataframes' indexes are misaligned, the results are different from cbind (even if they have the same number of rows). You need to either make sure the indexes align or drop/reset the indexes.

Example:

import pandas as pd

test1 = pd.DataFrame([1,2,3,4,5])
test1.index = ['a','b','c','d','e']
test2 = pd.DataFrame([4,2,1,3,7])
test2.index = ['d','e','f','g','h']

pd.concat([test1, test2], axis=1)

     0    0
a  1.0  NaN
b  2.0  NaN
c  3.0  NaN
d  4.0  4.0
e  5.0  2.0
f  NaN  1.0
g  NaN  3.0
h  NaN  7.0

pd.concat([test1.reset_index(drop=True), test2.reset_index(drop=True)], axis=1)

   0  1
0  1  4
1  2  2
2  3  1
3  4  3
4  5  7

pd.concat([test1.reset_index(), test2.reset_index(drop=True)], axis=1)      

  index  0  0
0     a  1  4
1     b  2  2
2     c  3  1
3     d  4  3
4     e  5  7

This index issue is absolutely central and yours should for that reason be the accepted answer. Anybody coming from R, looking for cbind, will need to know this. — Thomas Browne, Aug 21 '22 at 21:24

pandas equivalent of R's cbind (concatenate/stack vectors vertically)

2 Answers2