How to replace 'any strings' with nan in pandas DataFrame using a boolean mask?

Question

I have a 227x4 DataFrame with country names and numerical values to clean (wrangle ?).

Here\'s an abstraction of the DataFrame:

import pandas as pd
i         


        

Answer 1

Use numeric with errors coerce i.e

cols = ['Measure1','Measure2']
df[cols] = df[cols].apply(pd.to_numeric,errors='coerce')

 Country Name  Measure1  Measure2
0          PuB       7.0       6.0
1          JHq       2.0       NaN
2          opE       4.0       3.0
3          pxl       3.0       6.0
4          ouP       NaN       4.0
5          qZR       4.0       6.0