Pandas Fillna Mode

问题

I have a data set in which there is a column known as Native Country which contain around 30000 records. Some are missing represented by NaN so I thought to fill it with mode() value. I wrote something like this:

data['Native Country'].fillna(data['Native Country'].mode(), inplace=True)

However when I do a count of missing values:

for col_name in data.columns: 
    print ("column:",col_name,".Missing:",sum(data[col_name].isnull()))

It is still coming up with the same number of NaN values for the column Native Country.

回答1:

Just call first element of series:

data['Native Country'].fillna(data['Native Country'].mode()[0], inplace=True)

or you can do the same with assisgnment:

data['Native Country'] = data['Native Country'].fillna(data['Native Country'].mode()[0])

回答2:

Be careful, NaN may be the mode of your dataframe: in this case, you are replacing NaN with another NaN.

来源：https://stackoverflow.com/questions/42789324/pandas-fillna-mode