Swapping index levels in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

What is the output after swapping index levels?

Given a pandas DataFrame with a MultiIndex, what will be the index order after swapping the two levels using df.swaplevel()?

Pandas

import pandas as pd

index = pd.MultiIndex.from_tuples([('A', 1), ('A', 2), ('B', 1)])
df = pd.DataFrame({'value': [10, 20, 30]}, index=index)
swapped = df.swaplevel()

A [('A', 1), ('A', 2), ('B', 1)]

B [('B', 1), ('A', 2), ('A', 1)]

C [(1, 'B'), (2, 'A'), (1, 'A')]

D [(1, 'A'), (2, 'A'), (1, 'B')]

💡 Hint

Think about what swapping index levels means: the first level becomes second and the second becomes first.

The swaplevel() method switches the positions of the two index levels. So the original index [('A',1), ('A',2), ('B',1)] becomes [(1,'A'), (2,'A'), (1,'B')].

📝 Syntax

intermediate

Which code correctly swaps index levels in pandas?

Identify the correct syntax to swap the two levels of a MultiIndex in a pandas DataFrame named df.

A df.swaplevel(0, 1)

B df.swaplevel(level1=0, level2=1)

C df.swaplevel(levels=(0,1))

D df.swap_level(0, 1)

💡 Hint

Check the exact method name and parameter names in pandas documentation.

The correct method is swaplevel with positional arguments for the two levels to swap. The other options use incorrect method names or parameter names.

❓ optimization

advanced

How to efficiently swap index levels and sort the DataFrame?

You want to swap the two levels of a MultiIndex in a DataFrame df and then sort the DataFrame by the new index order. Which option achieves this efficiently?

A df.swaplevel(levels=(1,0)).sort_values()

B df.sort_index().swaplevel()

C df.swaplevel().sort_index()

D df.sort_values().swaplevel()

💡 Hint

Remember that sorting by index should happen after swapping the index levels.

Swapping the levels first and then sorting by index ensures the DataFrame is ordered by the new index. Sorting before swapping does not sort by the new index order.

🔧 Debug

advanced

Why does this swaplevel call raise an error?

Consider this code snippet:

df.swaplevel(level=0, level=1)

Why does it raise a SyntaxError or TypeError?

Pandas

df.swaplevel(level=0, level=1)

A Because swaplevel requires positional arguments, not keywords.

B Because the method does not accept keyword arguments named 'level' twice.

C Because the index levels do not exist in the DataFrame.

D Because swaplevel only works on single-level indexes.

💡 Hint

Check the function call syntax and parameter names carefully.

The code uses the same keyword argument 'level' twice, which is invalid syntax in Python. The correct way is to use positional arguments or keywords i=0 and j=1.

🧠 Conceptual

expert

What happens to the index names after swapping levels?

If a MultiIndex has names ['first', 'second'], what will be the names after calling df.swaplevel() without arguments?

Pandas

import pandas as pd
index = pd.MultiIndex.from_tuples([('x', 1), ('y', 2)], names=['first', 'second'])
df = pd.DataFrame({'val': [5, 10]}, index=index)
swapped = df.swaplevel()

A ['second', 'first']

B ['first', 'second']

C ['first_second', 'second_first']

D [None, None]

💡 Hint

Swapping index levels also swaps their names in the same order.

The swaplevel() method swaps both the index levels and their names. So the names change from ['first', 'second'] to ['second', 'first'].