Setting a column as index in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does setting a column as an index in pandas do?

It makes that column the row labels, which helps to identify rows uniquely and access data more easily.

beginner

How do you set a column named 'ID' as the index in a pandas DataFrame called df?

Use df.set_index('ID', inplace=True) to set the 'ID' column as the index and change df directly.

intermediate

What happens if you set a column as index without inplace=True?

The method returns a new DataFrame with the column set as index, but the original DataFrame stays unchanged.

intermediate

Can you set multiple columns as a multi-level index in pandas?

Yes, by passing a list of column names to set_index(), like df.set_index(['col1', 'col2']).

beginner

Why might you want to reset the index after setting a column as index?

To turn the index back into a regular column, making it easier to manipulate or export the data.

Which pandas method sets a column as the index of a DataFrame?

A set_index()

B set_column()

C make_index()

D index_column()

The correct method to set a column as index is set_index().

What does inplace=True do when used with set_index()?

A Deletes the DataFrame

B Returns a new DataFrame without changing the original

C Modifies the original DataFrame directly

D Creates a copy of the index

inplace=True changes the original DataFrame instead of returning a new one.

How do you set multiple columns as a multi-level index?

A Call <code>set_index()</code> multiple times

B Pass a list of column names to <code>set_index()</code>

C Use <code>multi_index()</code> method

D Set index on one column only

Passing a list like ['col1', 'col2'] to set_index() creates a multi-level index.

What type of object is returned by set_index() if inplace=False?

A A new DataFrame with the index set

B A Series

C None

D The original DataFrame unchanged

Without inplace=True, set_index() returns a new DataFrame with the index set.

Why is setting a column as index useful?

A It sorts the DataFrame automatically

B It deletes the column permanently

C It converts the DataFrame to a list

D It helps identify rows uniquely and speeds up data access

Setting an index helps label rows uniquely and can make data access faster and clearer.

Explain how to set a column as the index in a pandas DataFrame and why you might want to do this.

Think about how row labels help you find data quickly.

Describe how to create a multi-level index using multiple columns in pandas.

Imagine organizing data by two or more categories at once.