Handle infinity values in Python

# Import libraries
import pandas as pd
import numpy as np
from numpy.random import randint

# Create sample dataframe
df = (
    pd.DataFrame({'clicks': randint(1, 20, 5), 
                  'impressions': list(randint(1000, 3000, 4)) + [0]})
    .assign(ctr=lambda x: x['clicks']/x['impressions'])
)
df

	clicks	impressions	ctr
0	7	2850	0.002456
1	11	1896	0.005802
2	9	1457	0.006177
3	9	1698	0.005300
4	4	0	inf

In some cases where a float is divided by zero, you may encounter infinity values, negative or positive: np.inf or -np.inf.

Replace infinity values

To replace those infinity values, you can use replace():

# Replace infinity with 0
df.replace([np.inf, -np.inf], 0)

	clicks	impressions	ctr
0	7	2850	0.002456
1	11	1896	0.005802
2	9	1457	0.006177
3	9	1698	0.005300
4	4	0	0.000000

Drop rows

If you want to drop the rows, replace infinity values with NaN and follow with dropna():

# Replace with NaN and drop rows
df.replace([np.inf, -np.inf], np.nan).dropna()

	clicks	impressions	ctr
0	7	2850	0.002456
1	11	1896	0.005802
2	9	1457	0.006177
3	9	1698	0.005300