How can I calculate pct_change() in pandas across two columns, row by row?

Question

I have this:

df['new'] = df[['col1', 'col2']].pct_change(axis=1)

I want the percent change across rows in col1 and col2. However I am getting the error:

ValueError: Wrong number of items passed 2, placement implies 1

What am I doing wrong?

Answer 1

The percent change function is returning a pandas DataFrame object with two columns! This is why you see the ValueError where 1 item is expected instead of two.

import numpy as np
x = np.range(1,11)
y = x*3
df = pd.DataFrame()
df['col1'] = x
df['col2'] = y
df
   col1  col2
0     1     3
1     2     6
2     3     9
3     4    12
4     5    15
5     6    18
6     7    21
7     8    24
8     9    27
9    10    30

df.pct_change(axis=1)
   col1  col2
0   NaN   2.0
1   NaN   2.0
2   NaN   2.0
3   NaN   2.0
4   NaN   2.0
5   NaN   2.0
6   NaN   2.0
7   NaN   2.0
8   NaN   2.0
9   NaN   2.0

The percent change across rows that you want is stored in the last column ('col2' in this case) so just choose that last column to populate the 'new' column. In this case we compute a 200% change for every row.

df['new'] = df.pct_change(axis=1)['col2']
    col1  col2  new
0     1     3  2.0
1     2     6  2.0
2     3     9  2.0
3     4    12  2.0
4     5    15  2.0
5     6    18  2.0
6     7    21  2.0
7     8    24  2.0
8     9    27  2.0
9    10    30  2.0