Difference between map, applymap and apply methods in Pandas
Probably simplest explanation the difference between apply and applymap:
apply takes the whole column as a parameter and then assign the result to this column
applymap takes the separate cell value as a parameter and assign the result back to this cell.
NB If apply returns the single value you will have this value instead of the column after assigning and eventually will have just a row instead of matrix.
Can you tell me when to use these vectorization methods with basic examples? 
I see that map is a Series method whereas the rest are DataFrame methods. I got confused about apply and applymap methods though. Why do we have two methods for applying a function to a DataFrame? Again, simple examples which illustrate the usage would be great!