Coding Grandmaster · project 33 of 46 · premium, free for now

Cleaning messy data

Write fill_missing(values) that replaces each None with the mean of the other values rounded to 1 decimal place, and remove_duplicates(values) that keeps only the first of each repeated value in order. Print both results for the readings.

Learn

Real data has gaps and repeats. Before analysing it you decide how to fix it. A common choice for numbers is to fill each gap with the mean of the values you do have; for lists of items you may need to drop duplicates while keeping the first occurrence in order. Writing each fix as its own small function keeps the cleaning clear and testable.

Your task

Stretch challenge

Use the median instead of the mean to fill gaps. When is that better?

← Group by: totals per region Draw a bar chart →

Python

Press Run to see what your program prints.

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Records, filters and rankings

Keep the students whose score is at least cutoff, sort them by highest score (ties by name), print how many qualified, and print the first top of them as a numbered list.

Start →32

Group by: totals per region

For every sale of at least minimum, add it to its region. Print one line per region (alphabetical) like east: total 360, average 180.0, orders 2.

Start →34

Draw a bar chart

Draw one filled bar for each value, 40 wide and 15 times the value tall, 50 apart, starting at x = -150 along the line y = -100, using a different colour from the list for each.

Start →35

Draw a line chart

Draw an x axis and a y axis from the origin at (-150, -100), then plot the sales as dots (50 apart across, 5 times the value up) joined by lines.

Start →36

Capstone: a report table

Write grade(score) (A for 80 or more, B for 70 or more, otherwise C) and print the ranking, highest first, as an aligned table with a header, then the average (2 decimal places) and the name of the top scorer.

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Practise the idea

🐞 Play Bug Hunter

A Python program prints the wrong answer. Find the one line with the bug, then see the fix and why it was wrong.

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FAQ

Cleaning messy data: common questions

I am stuck. What can I do?

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