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pythonpandasfillna

How to Pandas fillna() with mode of column?

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.

Solution

  • 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])