stack() and unstack() in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the stack() function do in pandas?

stack() moves the columns of a DataFrame into the row index, turning columns into a new level of the row index. It "compresses" the DataFrame horizontally into a Series with a MultiIndex.

beginner

What is the purpose of the unstack() function in pandas?

unstack() does the opposite of stack(). It moves a level of the row index into columns, "widening" the DataFrame or Series back to a wider shape.

intermediate

If you have a DataFrame with a MultiIndex on rows, how can you convert one index level into columns?

You can use unstack(level) where level is the index level you want to move to columns.

beginner

What happens if you call stack() on a DataFrame with no missing values?

The DataFrame columns become a new inner level of the row index, and the data is returned as a Series with a MultiIndex.

intermediate

How do stack() and unstack() help in reshaping data?

They help by changing the shape of data between 'wide' and 'long' formats, making it easier to analyze or visualize data depending on the task.

What does stack() do to a DataFrame?

A Sorts the DataFrame

B Moves rows into columns

C Deletes missing values

D Moves columns into the row index

stack() moves columns into the row index, creating a MultiIndex Series.

Which function reverses the effect of stack()?

A unstack()

B groupby()

C melt()

D pivot()

unstack() moves a level of the row index back into columns, reversing stack().

If a DataFrame has a MultiIndex on rows, which method moves one index level to columns?

A reset_index()

B stack()

C unstack()

D set_index()

unstack() moves a row index level to columns.

What type of object does stack() return when applied to a DataFrame?

A DataFrame

B Series with MultiIndex

C List

D Dictionary

stack() returns a Series with a MultiIndex.

Why use stack() and unstack() in data analysis?

A To reshape data between wide and long formats

B To remove duplicates

C To sort data alphabetically

D To merge datasets

They reshape data, making it easier to analyze or visualize.

Explain in your own words what stack() does to a DataFrame and give a simple example.

Think about turning columns into rows.

Describe how unstack() can be used to reshape data and why this might be useful.

Consider the opposite of stacking.