#0060

Keep Latest Event Per User

MediumPandas20 min20 XP

Problem

Given a pandas DataFrame with user_id, timestamp, and value columns, return a DataFrame containing the latest row for each user_id. Sort the result by user_id ascending and reset the index.

Why This Matters

Real event tables often contain many rows per entity. Latest-row extraction is used in churn labels, user profiles, fraud features, and dashboards.

Function Signature

def latest_event_per_user(events):

Examples

Example 1

Inputevents has two rows for user 1 and one row for user 2

Outputlatest user 1 row and user 2 row

Sorting by timestamp before deduplication makes keep="last" meaningful.

Constraints

Do not mutate the input DataFrame.
Sort final output by user_id.
Reset the final index.

CodePython

import pandas as pd

def latest_event_per_user(events):
    """
    Input example: events has two rows for user 1 and one row for user 2
    Return: latest user 1 row and user 2 row
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return events

import pandas as pd

def latest_event_per_user(events):
    """
    Input example: events has two rows for user 1 and one row for user 2
    Return: latest user 1 row and user 2 row
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return events

Visible browser tests run here when available.

Testcases1 visible / 3 hidden categories

Latest row per user

InputDataFrame with repeated users

Expectedone latest row per user

The later timestamp wins for each user.

Hidden Test Categories

Already unique usersInput sorted in reverse timeThree events for the same user