Which group has the higher average?

The question

Compare mean activity duration between Morning and Evening groups using known durations only.

df Mean comparison

Your inputs

`df`

Each row is one Morning or Evening activity session. Duration text may be invalid; all other sessions remain eligible.

Field meanings and units

record_id: Activity-observation identifier.
group: Comparison group.
date: Calendar date supplied as YYYY-MM-DD text unless the task states it is invalid.
steps: Recorded step count, additive across observations.
minutes: Elapsed duration in minutes; unknown is not zero.
week: Current or Previous reporting week.

`df` · first 5 of 20 rows
`record_id`	`group`	`date`	`steps`	`minutes`	`week`
A001	Morning	2026-04-01	2500	20	Previous
A002	Evening	2026-04-01	3070	27	Previous
A003	Morning	2026-04-02	3640	34	Previous
A004	Evening	2026-04-02	4210	41	Previous
A005	Morning	2026-04-03	4780	bad	Previous

View all 20 rows

`df` · complete input
`record_id`	`group`	`date`	`steps`	`minutes`	`week`
A001	Morning	2026-04-01	2500	20	Previous
A002	Evening	2026-04-01	3070	27	Previous
A003	Morning	2026-04-02	3640	34	Previous
A004	Evening	2026-04-02	4210	41	Previous
A005	Morning	2026-04-03	4780	bad	Previous
A006	Evening	2026-04-03	5350	55	Previous
A007	Morning	2026-04-04	5920	21	Previous
A008	Evening	2026-04-04	2640	28	Previous
A009	Morning	2026-04-05	3210	35	Previous
A010	Evening	2026-04-05	3780	42	Previous
A011	Morning	2026-04-06	4350	49	Previous
A012	Evening	2026-04-06	4920	56	Previous
A013	Morning	2026-04-07	5490	22	Previous
A014	Evening	2026-04-07	6060	29	Previous
A015	Morning	2026-04-08	2780	36	Current
A016	Evening	2026-04-08	3350	43	Current
A017	Morning	2026-04-09	3920	50	Current
A018	Evening	2026-04-09	4490	57	Current
A019	Morning	2026-04-10	5060	23	Current
A020	Evening	2026-04-10	5630	30	Current

The editable setup in Your Python creates these inputs when you run it.

Your task · Which group has the higher average?

Compare mean activity duration between Morning and Evening groups using known durations only.

meansSeriesfigFigure

Deliverables

Make the outputs listed below. Use each name exactly as shown. Then choose Check answer.

Python name key

Teal outlines name table columns. Violet left rules name Python objects. Dotted rules mark syntax, functions and parameters. Use each name exactly as shown.

Group meansOutputmeansSeries
1. Store the mean parsed minutes for each group in means.
2. Omit invalid durations, not entire groups.
FigureOutputfigFigure
1. Create fig comparing the group means.
2. Choose labelled bars or individual points; either orientation is valid.
3. Bars must start at zero.
4. Add a meaningful title and measure labels
5. Display the figure.
Identify Group and Minutes on the appropriate axes; extra wording is welcome.

Data policy Keep all supplied source tables unchanged. Work on separate outputs.

Help Hints & explained solution

Choose the amount of help you need. Opening one hint does not reveal the others.

Hint 1 — Think

Does an unknown duration belong in the denominator of an observed mean?

Hint 2 — Tools

to_numeric(), groupby(), mean(), Axes.bar() or Axes.barh(), or Axes.scatter() for a labelled point comparison

Revisit: Convert numeric text · Summarise groups · Compare averages · Avoid misleading charts · Scatter plot

Hint 3 — Approach

Parse durations, calculate each group’s observed mean and compare the values on a fair zero-based axis.

Explained solution

Add these lines below # Your work in the editor. The supplied input setup is already there.

work = df.copy()
work['minutes'] = pd.to_numeric(work.minutes, errors='coerce')
means = work.groupby('group').minutes.mean()
fig, ax = plt.subplots()
ax.bar(means.index, means.values)
ax.set(title='Mean activity duration', xlabel='Group', ylabel='Minutes')
fig.tight_layout()
plt.show()

View supplied setup

This code is already at the top of the editor.

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# Supplied input: df (20 rows)
df = pd.DataFrame(
    [
        ('A001', 'Morning', '2026-04-01', 2500, '20', 'Previous'),
        ('A002', 'Evening', '2026-04-01', 3070, '27', 'Previous'),
        ('A003', 'Morning', '2026-04-02', 3640, '34', 'Previous'),
        ('A004', 'Evening', '2026-04-02', 4210, '41', 'Previous'),
        ('A005', 'Morning', '2026-04-03', 4780, 'bad', 'Previous'),
        ('A006', 'Evening', '2026-04-03', 5350, '55', 'Previous'),
        ('A007', 'Morning', '2026-04-04', 5920, '21', 'Previous'),
        ('A008', 'Evening', '2026-04-04', 2640, '28', 'Previous'),
        ('A009', 'Morning', '2026-04-05', 3210, '35', 'Previous'),
        ('A010', 'Evening', '2026-04-05', 3780, '42', 'Previous'),
        ('A011', 'Morning', '2026-04-06', 4350, '49', 'Previous'),
        ('A012', 'Evening', '2026-04-06', 4920, '56', 'Previous'),
        ('A013', 'Morning', '2026-04-07', 5490, '22', 'Previous'),
        ('A014', 'Evening', '2026-04-07', 6060, '29', 'Previous'),
        ('A015', 'Morning', '2026-04-08', 2780, '36', 'Current'),
        ('A016', 'Evening', '2026-04-08', 3350, '43', 'Current'),
        ('A017', 'Morning', '2026-04-09', 3920, '50', 'Current'),
        ('A018', 'Evening', '2026-04-09', 4490, '57', 'Current'),
        ('A019', 'Morning', '2026-04-10', 5060, '23', 'Current'),
        ('A020', 'Evening', '2026-04-10', 5630, '30', 'Current'),
    ],
    columns=['record_id', 'group', 'date', 'steps', 'minutes', 'week'],
)

Why these steps exist

Each group mean uses only its known durations; zero-filled unknowns would pull it downward.
A shared zero baseline makes the represented group means comparable without exaggerating their difference.

Another valid approach

Labelled individual points are also valid for comparing these summaries. Vertical and horizontal orientations are accepted; bars must use a zero baseline.