pandas module - the difference between map(), apply() and applymap() methods

1. map()
   • Apply a custom function to each element of the Series object
   • The map() method can only be used on Series objects, and the DataFrame object does not have a map() method
2. apply()
   • Apply a custom function to each element of any axis (specified by the axis parameter, any one or more rows, any one or more columns)
   • Using apply() on a column has the same effect as map(), because a column of a DataFrame object is a Series object
   • Only apply() can be used on multiple columns or rows
   • The apply() method can be used on both Series objects and DataFrame objects
3. applymap()
   • The first custom function acts on each element of the DataFrame object, and cannot specify rows or columns
   • The applymap() method can only be used on the DataFrame object, there is no applymap() method in the Series object