0x90Lesson 10 of 10

Capstone: analyze a bike-share dataset

Take a messy export from raw rows to a short, honest report.

35 min 5-question quiz 2 code exercises

By the end of this lesson you can

Clean a raw dataset with explicit, counted rules
Summarize groups and patterns that answer a question
Write findings that state scope and limits

The question: the city’s bike-share team asks, “How do members and casual riders use the bikes differently, and when is demand highest?” They’ve sent a raw export.

You’ll work like a data scientist would:

Clean the export, counting how many rows each rule removes - those counts go in the report, because they affect the conclusions.
Analyze the clean data: compare the rider groups, find the peak hour, and describe trip lengths.
Report what you found, with sample sizes and caveats.

title_case.py

stations = [" Main St", "park ave", "HARBOR "]
print([station.strip().title() for station in stations])

Output

['Main St', 'Park Ave', 'Harbor']

Key takeaways

Clean with explicit rules and report how many rows each removed.
Answer the question with group comparisons and clear summaries.
State sample size, period and limitations alongside the findings.

Lesson quiz

5 questions · pass with 4 correct · up to 50 XP

Passing this quiz completes the lesson and keeps your streak going. Questions you miss come back in review sessions later.

Practice: write Python

Write Python in the editor and run it against sample inputs. Python runs locally in your browser using a WebAssembly runtime.

Exercise 1

Step 1: clean the export

+25 XP

Read the CSV (trip_id,start_hour,minutes,member,station). Apply, in order, counting removed rows:

drop duplicate trip_ids (keep the first) → duplicates: N;
treat minutes of −1 as missing, then drop rows with missing minutes → missing minutes: N;
drop rows with minutes above 600 → impossible minutes: N.

Then print kept K of T trips, clean station (strip spaces, title case) and print stations: NAME COUNT, ... alphabetically.

Raw export

main.py

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Python runs in a sandboxed browser worker with a 60 second time limit. Its runtime loads from the Pyodide CDN; your code stays in this browser.

Exercise 2

Step 2: write the numbers for the report

+25 XP

Read a clean CSV (member,start_hour,minutes) and print:

1casual: n=N median=M min        (one line per rider type, alphabetically; median to 1 decimal)
2member: n=N median=M min
3busiest hour: H (N trips)       (the earliest hour if tied)
4short trips (<15 min): P%       (whole percent)

Ten trips

main.py

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Python runs in a sandboxed browser worker with a 60 second time limit. Its runtime loads from the Pyodide CDN; your code stays in this browser.

Questions about this lesson

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