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.

CodePudding user response：

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])