Category codes and labels in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of category codes after reordering categories

What is the output of the following code snippet?

Pandas

import pandas as pd
cats = pd.Categorical(['apple', 'banana', 'apple', 'orange'], categories=['banana', 'apple', 'orange'], ordered=True)
print(cats.codes)

A [1 0 1 2]

B [0 1 0 2]

C [1 2 1 0]

D [2 1 2 0]

💡 Hint

Remember that codes correspond to the position of each category in the categories list.

The categories are ordered as ['banana', 'apple', 'orange']. 'apple' is at index 1, 'banana' at 0, and 'orange' at 2. So the codes for ['apple', 'banana', 'apple', 'orange'] are [1, 0, 1, 2].

❓ data_output

intermediate

Number of unique categories after removing unused categories

Given the following categorical series, how many categories remain after removing unused categories?

Pandas

import pandas as pd
s = pd.Series(pd.Categorical(['red', 'blue', 'red', 'green'], categories=['red', 'blue', 'green', 'yellow']))
s = s.cat.remove_unused_categories()
print(len(s.cat.categories))

A 3

B 1

C 2

D 4

💡 Hint

Unused categories are those not present in the data values.

The original categories are ['red', 'blue', 'green', 'yellow']. The data contains 'red', 'blue', and 'green' but not 'yellow'. After removing unused categories, 'yellow' is dropped, leaving 3 categories.

🔧 Debug

advanced

Identify the error in category assignment

What error does the following code raise?

Pandas

import pandas as pd
cats = pd.Categorical(['cat', 'dog', 'bird'], categories=['cat', 'dog'])
print(cats.codes)

A IndexError: list index out of range

B No error, output: [0 1 -1]

C ValueError: 'bird' is not in categories

D TypeError: unsupported operand type(s)

💡 Hint

Check how pandas handles values not in categories.

Pandas assigns code -1 to values not in the categories list. So 'bird' gets code -1, no error is raised.

🚀 Application

advanced

Mapping category codes to labels

You have a categorical series with codes [2, 0, 1, 2] and categories ['small', 'medium', 'large']. Which code produces the correct list of labels?

Pandas

import pandas as pd
codes = [2, 0, 1, 2]
categories = ['small', 'medium', 'large']
cats = pd.Categorical.from_codes(codes, categories)
print(list(cats))

A ['small', 'medium', 'large', 'small']

B ['medium', 'large', 'small', 'medium']

C ['large', 'medium', 'small', 'large']

D ['large', 'small', 'medium', 'large']

💡 Hint

Codes map to categories by index position.

Code 2 maps to 'large', 0 to 'small', and 1 to 'medium'. So the list is ['large', 'small', 'medium', 'large'].

🧠 Conceptual

expert

Effect of changing categories order on codes

If you change the order of categories in a pandas Categorical object, what happens to the codes attribute?

A Codes become invalid and raise an error

B Codes remain the same, but category labels change

C Codes are recalculated to match the new category order

D Codes are reset to zero for all entries

💡 Hint

Think about how codes represent category positions.

Codes represent the index of each value in the categories list. Changing the order changes indices, so codes are recalculated accordingly.