pandas dataframe replace blanks with NaN

Question

I have a dataframe with empty cells and would like to replace these empty cells with NaN. A solution previously proposed at this forum works, but only if the cell contains a space:

df.replace(r'\s+',np.nan,regex=True)

This code does not work when the cell is empty. Has anyone a suggestion for a panda code to replace empty cells.

Answer 1

I think the easiest thing here is to do the replace twice:

In [117]:
df = pd.DataFrame({'a':['',' ','asasd']})
df

Out[117]:
       a
0       
1       
2  asasd

In [118]:
df.replace(r'\s+',np.nan,regex=True).replace('',np.nan)

Out[118]:
       a
0    NaN
1    NaN
2  asasd

Answer 2

Both other answers do not take in account all characters in a string. This is better:

df.replace(r'\s+( +\.)|#',np.nan,regex=True).replace('',np.nan))

More docs on: Replacing blank values (white space) with NaN in pandas