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

cols = ['Measure1','Measure2']
df[cols] = df[cols].applymap(lambda x: x if not isinstance(x, str) else np.nan)

or

df[cols] = df[cols].applymap(lambda x: np.nan if isinstance(x, str) else x)

Result:

In [22]: df
Out[22]:
  Country Name  Measure1  Measure2
0          nBl      10.0       9.0
1          Ayp       8.0       NaN
2          diz       4.0       1.0
3          aad       7.0       3.0
4          JYI       NaN      10.0
5          BJO       9.0       8.0