Is there a library function or correct way of stacking two Pandas data frame columns on top of each other?
For example make 4 columns into 2:
a1 b1 a2 b2
1 2 3 4
5 6 7 8
to
c d
1 2
5 6
3 4
7 8
The documentation for Pandas Data Frames that I read for the most part only deal with concatenating rows and doing row manipulation, but I'm sure there has to be a way to do what I described and I am sure it's very simple.
Any help would be great.
You can select the first two and second two columns using pandas.DataFrame.iloc
. Then, change the column name of both parts to c
and d
. Afterwards, you can just join them using pandas.concat
.
import pandas as pd
import numpy as np
df = pd.DataFrame(np.arange(1, 9).reshape((2, 4)),
columns=["a1", "b1", "a2", "b2"])
part1 = df.iloc[:,0:2]
part2 = df.iloc[:,2:4]
new_columns = ["c", "d"]
part1.columns = new_columns
part2.columns = new_columns
print pd.concat([part1, part2], ignore_index=True)
This gives you:
c d
0 1 2
1 5 6
2 3 4
3 7 8