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

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?

Solution 1:

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

Solution 2:

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