#0039

Filter Active High-Value Users

EasyPandas12 min10 XP

Problem

Given a DataFrame with user_id, is_active, and spend columns, return only active users whose spend is at least 100.

Why This Matters

Most dataframe work starts with "which rows do I actually want?" This problem builds the habit of writing readable masks.

Function Signature

def active_high_value_users(df):

Examples

Example 1

Inputusers: active/spend rows [(1, True, 120), (2, False, 200), (3, True, 80)]

Outputuser 1 only

User 2 spends enough but is inactive. User 3 is active but spends too little.

Constraints

Return only user_id and spend columns.
Reset the index in the returned DataFrame.
Do not mutate the original DataFrame.

CodePython

def active_high_value_users(df):
    """
    Input example: users: active/spend rows [(1, True, 120), (2, False, 200), (3, True, 80)]
    Return: user 1 only
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # df has columns: user_id, is_active, spend
    # write your code here
    return df

def active_high_value_users(df):
    """
    Input example: users: active/spend rows [(1, True, 120), (2, False, 200), (3, True, 80)]
    Return: user 1 only
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # df has columns: user_id, is_active, spend
    # write your code here
    return df

Visible browser tests run here when available.

Testcases1 visible / 4 hidden categories

Two conditions

Inputactive users and spend values

Expectedonly users satisfying both conditions

Both conditions must be true for a row to remain.

Hidden Test Categories

No matching rowsAll rows matchSpend exactly 100Original index not starting at zero