#0202

Fill Missing Values by Group Median

MediumPandas25 min20 XP

Problem

Fill missing score values with the median score of the same department.

Why This Matters

Group-aware imputation is more realistic than one global average when segments behave differently.

Function Signature

def fill_score_by_department_median(df):

Examples

Example 1

Inputsales: 10, missing, 20; support: 7

Outputsales missing becomes 15

The sales median is (10 + 20) / 2 = 15.

Constraints

Return the exact requested result.
Handle common edge cases.
Keep the solution readable before optimizing.

CodePython

import pandas as pd

def fill_score_by_department_median(df):
    """
    Input example: sales: 10, missing, 20; support: 7
    Return: sales missing becomes 15
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return df

import pandas as pd

def fill_score_by_department_median(df):
    """
    Input example: sales: 10, missing, 20; support: 7
    Return: sales missing becomes 15
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return df

Visible browser tests run here when available.

Testcases1 visible / 3 hidden categories

Core example

Inputsales: 10, missing, 20; support: 7

Expectedsales missing becomes 15

The sales median is (10 + 20) / 2 = 15.

Hidden Test Categories

empty or minimal inputrepeated valueslarger realistic input