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Project 14: Subscriber Age Corrector

Data Analyst

Builds on these lessons

Current Task

Objective

.loc[] with a boolean condition lets you overwrite only the rows that match — the standard way to correct out-of-range values in place.

Task: replace any age over 120 or under 0 with NaN using .loc, and print the result.

index.py
import pandas as pd import numpy as np subscribers = pd.DataFrame({'age': [25, 150, 34, -5]}) subscribers.loc[subscribers['age'] > 120, 'age'] = np.nan subscribers.loc[subscribers['age'] < 0, 'age'] = np.nan print(subscribers)

* Hint: Correct characters turn green, incorrect ones turn red.

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