map() for element-wise transformation in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the map() function do in pandas?

The map() function applies a given function or mapping to each element of a pandas Series, transforming the data element-wise.

beginner

How can you use map() to replace values in a pandas Series?

You can pass a dictionary to map() where keys are original values and values are replacements. The Series elements are replaced accordingly.

intermediate

What happens if map() encounters a value not in the dictionary when mapping?

Values not found in the dictionary are replaced with NaN (missing value) in the resulting Series.

beginner

Can map() accept a function? How does it work?

Yes, map() can take a function that is applied to each element of the Series, returning a transformed Series.

intermediate

Difference between map() and apply() in pandas?

map() works element-wise on Series only, while apply() can work on Series or DataFrames and can apply functions row-wise or column-wise.

What type of pandas object does map() work on?

A Index

B DataFrame

C Panel

D Series

map() is designed to work on pandas Series for element-wise transformations.

What will map() return if a value is not found in the mapping dictionary?

A Original value

B NaN

C Error

D Empty string

Values not found in the dictionary are replaced with NaN in the output Series.

Which of the following can be passed to map()?

A A dictionary

B A list

C A DataFrame

D A scalar value

map() accepts a dictionary or a function for element-wise mapping.

If you want to apply a function to each element of a Series, which method can you use?

A merge()

B groupby()

C map()

D pivot()

map() applies a function element-wise to a Series.

Which method is more flexible for applying functions to DataFrames or Series?

A apply()

B concat()

C replace()

D map()

apply() works on Series and DataFrames and can apply functions row-wise or column-wise.

Explain how you can use map() to replace values in a pandas Series using a dictionary.

Think about how each element is matched to dictionary keys.

Describe the difference between using a function and a dictionary with map() in pandas.

Consider how the input changes depending on what you pass to map.