How to set a cell to NaN in a pandas dataframe

Question

I\'d like to replace bad values in a column of a dataframe by NaN\'s.

mydata = {\'x\' : [10, 50, 18, 32, 47, 20], \'y\' : [\'12\', \'11\', \'N/A\', \'13\', \         


        

Answer 1

You can use replace:

df['y'] = df['y'].replace({'N/A': np.nan})

Also be aware of the inplace parameter for replace. You can do something like:

df.replace({'N/A': np.nan}, inplace=True)

This will replace all instances in the df without creating a copy.

Similarly, if you run into other types of unknown values such as empty string or None value:

df['y'] = df['y'].replace({'': np.nan})

df['y'] = df['y'].replace({None: np.nan})

Reference: Pandas Latest - Replace