List with attributes of persons loaded into pandas dataframe df2
. For cleanup I want to replace value zero (0
or '0'
) by np.nan
.
df2.dtypes
ID object
Name object
Weight float64
Height float64
BootSize object
SuitSize object
Type object
dtype: object
Working code to set value zero to np.nan
:
df2.loc[df2['Weight'] == 0,'Weight'] = np.nan
df2.loc[df2['Height'] == 0,'Height'] = np.nan
df2.loc[df2['BootSize'] == '0','BootSize'] = np.nan
df2.loc[df2['SuitSize'] == '0','SuitSize'] = np.nan
Believe this can be done in a similar/shorter way:
df2[["Weight","Height","BootSize","SuitSize"]].astype(str).replace('0',np.nan)
However the above does not work. The zero's remain in df2. How to tackle this?