Difference between map, applymap and apply methods in Pandas
applymap()method only works on a pandas dataframe where function is applied on every element individually.
apply()method can be applied both to series and dataframes where function can be applied both series and individual elements based on the type of function provided.
map()method only works on a pandas series where type of operation to be applied depends on argument passed as a function, dictionary or a list.
Note that the type of Output totally depends on the type of function used as an argument with the given method.
This method which can be used on both on a pandas dataframe and series. The function passed as an argument typically works on rows/columns. Code below illustrates how
apply() method works on Pandas dataframe.
Below Code illustrates how
apply() method on Pandas series:
applymap() method :
This method can be used on a pandas dataframe. The function passed as an argument typically works on elements of the dataframe
applymap() is typically used for elementwise operations. Code below illustrates how
applymap method works on pandas dataframe:
map() method :
This method is used on series function, list and dictionary passed as an argument. This method is generally used to map values from two series having one column same. Code below illustrates how
map method works on pandas series:
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course