Python -- Function 以 Pandas dataframe 作为参数

Question

I have to create a function that takes a Pandas dataframe as an argument and returns a copy of the dataframe after replacing the null values in each column with the most frequent value in the column.

Cannot use FOR or WHILE loops.

Answer 1

Well, to create a copy you can simply use df.copy(deep = True) (note that deep = True creates a new dataframe-object, otherwise you get a reference to the copied dataframe). To replace the null values with the most frequent values, you can use the mode method for Series and DataFrames ( https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.mode.html ).

An example would be: df = df.fillna(df.mode().iloc[0])