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

Assign only columns of interest:

cols = ['Measure1','Measure2']
mask = df[cols].applymap(lambda x: isinstance(x, (int, float)))

df[cols] = df[cols].where(mask)
print (df)
  Country Name Measure1 Measure2
0          uFv        7        8
1          vCr        5      NaN
2          qPp        2        6
3          QIC       10       10
4          Suy      NaN        8
5          eFS        6        4

A meta-question, Is it normal that it takes me more than 3 hours to formulate a question here (including research) ?

In my opinion yes, create good question is really hard.