Adding and removing categories in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of adding a new category to a pandas Categorical

What is the output of this code snippet?

Pandas

import pandas as pd
cat = pd.Categorical(['apple', 'banana'], categories=['apple', 'banana'])
cat = cat.add_categories(['cherry'])
print(cat.categories.tolist())

A ['apple', 'banana', 'cherry']

B ['apple', 'banana']

C ['cherry']

D ['apple', 'banana', 'cherry', 'date']

💡 Hint

Think about what add_categories does to the categories list.

The add_categories method adds new categories to the existing categories without changing the current values. So the categories list will include the original plus the new one.

❓ data_output

intermediate

Result of removing a category from a pandas Categorical

What is the output of this code?

Pandas

import pandas as pd
cat = pd.Categorical(['apple', 'banana', 'cherry'], categories=['apple', 'banana', 'cherry'])
cat = cat.remove_categories(['banana'])
print(cat.categories.tolist())

A ['apple', 'cherry']

B ['apple', 'banana']

C ['banana']

D ['apple', 'banana', 'cherry']

💡 Hint

Removing a category deletes it from the categories list.

The remove_categories method removes the specified categories from the categories list. So 'banana' is removed.

🔧 Debug

advanced

Behavior when removing a non-existent category

What happens when running this code?

Pandas

import pandas as pd
cat = pd.Categorical(['apple', 'banana'], categories=['apple', 'banana'])
cat = cat.remove_categories(['cherry'])

A ValueError because 'cherry' is not in the categories

B TypeError because remove_categories expects a string, not a list

C No error, code runs fine

D KeyError because 'cherry' is missing

💡 Hint

remove_categories ignores categories that do not exist.

No error is raised. remove_categories only removes categories present in the current categories list; others are ignored.

🚀 Application

advanced

Effect of removing a category on data values

Given this code, what is the output of the print statement?

Pandas

import pandas as pd
cat = pd.Categorical(['apple', 'banana', 'cherry', 'banana'], categories=['apple', 'banana', 'cherry'])
cat = cat.remove_categories(['banana'])
print(cat.tolist())

A ['apple', 'cherry', 'cherry', 'cherry']

B ['apple', nan, 'cherry', nan]

C ['apple', 'banana', 'cherry', 'banana']

D ['apple', None, 'cherry', None]

💡 Hint

Removing a category replaces its values with NaN in the data.

When a category is removed, any data values with that category become NaN (missing).

🧠 Conceptual

expert

Why use add_categories instead of directly assigning new categories?

Why is it better to use add_categories to add new categories instead of assigning a new categories list directly?

A Direct assignment automatically updates data values to new categories

B Direct assignment is faster and safer than add_categories

C add_categories removes old categories automatically

D add_categories preserves existing data values and only adds new categories, avoiding errors

💡 Hint

Think about what happens to existing data when categories change.

add_categories safely adds new categories without changing existing data values, preventing errors or data loss.