Swapping index levels in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does swapping index levels mean in pandas?

Swapping index levels means changing the order of the levels in a MultiIndex, so the level that was first becomes second, and vice versa.

beginner

Which pandas method is used to swap index levels?

The method used is swaplevel(). It switches the positions of two index levels in a MultiIndex.

beginner

How do you swap the first and second index levels of a DataFrame named df?

Use df.swaplevel(0, 1). This swaps the index levels at position 0 and 1.

intermediate

What happens if you swap index levels but do not sort the index afterwards?

The index order might look unordered or confusing. Sorting with sort_index() after swapping helps keep the data organized.

intermediate

Can you swap index levels on both rows and columns in pandas?

Yes. You can swap index levels on rows (index) or columns (columns MultiIndex) by specifying the axis in swaplevel().

What does df.swaplevel(0, 1) do in pandas?

A Swaps the first and second index levels of df

B Swaps the first and second columns of df

C Sorts the index of df

D Resets the index of df

The swaplevel() method swaps two index levels. Here, levels 0 and 1 are swapped.

Which method should you use after swapping index levels to keep the index ordered?

A reset_index()

B sort_index()

C drop_duplicates()

D groupby()

After swapping index levels, sort_index() helps reorder the index for clarity.

If a DataFrame has a MultiIndex on columns, how do you swap its levels?

A Use <code>swaplevel()</code> with <code>axis=0</code>

B Use <code>sort_values()</code>

C Use <code>reset_index()</code>

D Use <code>swaplevel()</code> with <code>axis=1</code>

Columns are on axis 1, so swapping their index levels requires axis=1.

What type of index must a DataFrame have to use swaplevel()?

A MultiIndex with at least two levels

B Single-level index

C No index

D DatetimeIndex only

swaplevel() works only if there are at least two index levels to swap.

What is the default axis for swaplevel() in pandas?

A axis=2

B axis=1 (columns)

C axis=0 (rows)

D axis=None

By default, swaplevel() swaps index levels on rows (axis=0).

Explain how to swap two index levels in a pandas DataFrame and why you might want to do this.

Think about changing the order of row labels in a table.

Describe the steps to swap column index levels in a pandas DataFrame with a MultiIndex on columns.

Remember columns are on axis 1.

Practice

1. What does the swaplevel() function do in a pandas DataFrame with a multi-level index?

easy

A. It deletes one of the index levels permanently.

B. It switches the positions of two index levels without changing the data.

C. It sorts the DataFrame by the index levels.

D. It converts the multi-level index into columns.

Solution

1. Step 1: Understand the purpose of swaplevel()

   The swaplevel() function is designed to reorder the levels of a multi-level index by swapping two specified levels.

2. Step 2: Confirm it does not alter data values

   Swapping index levels changes only the order of the index labels, not the underlying data or its values.

3. Final Answer:

   It switches the positions of two index levels without changing the data. -> Option B

4. Quick Check:

   swaplevel() swaps index levels [OK]

Hint: Remember: swaplevel() only changes index order, not data [OK]

Common Mistakes:

• Thinking swaplevel() deletes index levels
• Confusing swaplevel() with sorting functions
• Assuming swaplevel() changes data values

2. Which of the following is the correct syntax to swap the first and second levels of a DataFrame's multi-level index named df?

easy

A. df.swaplevel()

B. df.swaplevel(1, 2)

C. df.swaplevel('level1', 'level3')

D. df.swaplevel(0, 1)

Solution

1. Step 1: Identify index levels by position

   Index levels are zero-based, so the first level is 0 and the second is 1.

2. Step 2: Use swaplevel() with correct positions

   Calling df.swaplevel(0, 1) swaps the first and second levels correctly.

3. Final Answer:

   df.swaplevel(0, 1) -> Option D

4. Quick Check:

   swaplevel(0, 1) swaps first two levels [OK]

Hint: Use zero-based positions to swap levels: 0 and 1 for first two [OK]

Common Mistakes:

• Using incorrect level numbers like 1 and 2 for first two levels
• Calling swaplevel() without arguments
• Using level names that don't exist

3. Given the following DataFrame df with a multi-level index:

import pandas as pd
index = pd.MultiIndex.from_tuples([('A', 1), ('A', 2), ('B', 1), ('B', 2)], names=['letter', 'number'])
df = pd.DataFrame({'value': [10, 20, 30, 40]}, index=index)
print(df.swaplevel('letter', 'number'))

What will be the first row's index after swapping?

medium

A. (1, 'A')

B. ('A', 1)

C. ('number', 'letter')

D. (10, 20)

Solution

1. Step 1: Understand original index order

   The original index is [('A',1), ('A',2), ('B',1), ('B',2)] with levels 'letter' then 'number'.

2. Step 2: Swap levels 'letter' and 'number'

   After swapping, the order becomes 'number' then 'letter'. So the first index becomes (1, 'A').

3. Final Answer:

   (1, 'A') -> Option A

4. Quick Check:

   Swapped index order changes ('A',1) to (1,'A') [OK]

Hint: Swapping levels flips their order in the index tuple [OK]

Common Mistakes:

• Assuming index values stay in same order
• Confusing index values with column values
• Mixing up level names and positions

4. You try to swap index levels in a DataFrame using df.swaplevel('first', 'second') but get a KeyError. What is the most likely cause?

medium

A. The level names 'first' and 'second' do not exist in the index.

B. swaplevel() requires integer positions, not names.

C. The DataFrame has no multi-level index.

D. You must reset the index before swapping levels.

Solution

1. Step 1: Check index level names

   swaplevel() accepts level names, but if the names given do not exist, a KeyError occurs.

2. Step 2: Confirm cause of KeyError

   The error means 'first' and 'second' are not valid level names in the DataFrame's index.

3. Final Answer:

   The level names 'first' and 'second' do not exist in the index. -> Option A

4. Quick Check:

   KeyError means invalid level names [OK]

Hint: Verify level names exist before swapping [OK]

Common Mistakes:

• Assuming swaplevel() only accepts integers
• Not checking if DataFrame has multi-level index
• Resetting index unnecessarily

5. You have a DataFrame df with a multi-level index named ['city', 'year', 'month']. You want to swap the 'city' and 'month' levels and then sort the DataFrame by the new index order. Which code snippet correctly does this?

hard

A. df_swapped = df.swaplevel('year', 'month').sort_index()

B. df_swapped = df.swaplevel(0, 1).sort_values()

C. df_swapped = df.swaplevel('city', 'month').sort_index()

D. df_swapped = df.swaplevel('city', 'month').reset_index()

Solution

1. Step 1: Identify correct levels to swap

   The levels to swap are 'city' and 'month', which are the first and third levels.

2. Step 2: Use swaplevel() with level names and sort_index()

   Calling swaplevel('city', 'month') swaps these levels. Then sort_index() sorts the DataFrame by the new index order.

3. Final Answer:

   df_swapped = df.swaplevel('city', 'month').sort_index() -> Option C

4. Quick Check:

   Swap specified levels then sort index [OK]

Hint: Swap by names, then sort_index() to reorder rows [OK]

Common Mistakes:

• Swapping wrong levels by position
• Using sort_values() instead of sort_index()
• Resetting index instead of sorting