Handling NULL or Missing Values in Pandas DataFrame
In a Pandas DataFrame NULL or Missing values appear as "NaN"
You can either drop the rows with the missing values OR you can replace missing values with representative values (median or average (mean) or mode) for the same column (feature)
For your reference, the Jupyter notebook and CSV file are uploaded to my github site at https://github.com/hemantkchitale/Dat...