Interweave two dataframes

Question

Suppose I have two dataframes d1 and d2

d1 = pd.DataFrame(np.ones((3, 3), dtype=int), list('abc'), [0, 1, 2])

d2 = pd.DataFrame(np.zeros((3, 2), dtype=int), list('abc'), [3, 4])

d1

   0  1  2

a  1  1  1

b  1  1  1

c  1  1  1

d2

   3  4

a  0  0

b  0  0

c  0  0

What is an easy and generalized way to interweave two dataframes' columns? We can assume that the number of columns in d2 is always one less than the number of columns in d1. And, the indices are the same.

I want this:

pd.concat([d1[0], d2[3], d1[1], d2[4], d1[2]], axis=1)

   0  3  1  4  2

a  1  0  1  0  1

b  1  0  1  0  1

c  1  0  1  0  1

Answer 1

Just use the pd.concat to consolidate the DataFrames, and toolz.interleave reorder the columns:

from toolz import interleave

pd.concat([d1, d2], axis=1)[list(interleave([d1, d2]))]

The resulting output is as expected:

   0  3  1  4  2

a  1  0  1  0  1

b  1  0  1  0  1

c  1  0  1  0  1

Refer to the following links for more information regarding the same:

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.concat.html

https://toolz.readthedocs.io/en/latest/api.html#toolz.itertoolz.interleave

If you are interested in learning Pandas and want to become an expert in Python Programming, then check out this Python Course and upskill yourself.