Dataset Cleaning Project
A project in which the learner cleans a real dataset, documents every change, and writes a short findings note.
Data Literacy Foundations
Learn to read charts critically, clean a real dataset, and write up what it shows, with free tools and open data.
- Domain
- Data Literacy
- Estimated time
- About 10 hours
- Formats
- reading, interactive, project
- Cost
- Free
- Status
- draft · v0.1.0
- License
- CC BY-SA 4.0
Outcomes you will reach
- Read and interpret a chart foundation
- Clean a small tabular dataset intermediate
- Summarize a dataset and communicate findings intermediate
Resources
| Resource | Kind | Cost | Provider |
|---|---|---|---|
| Our World in Data | dataset | free | Our World in Data |
| Khan Academy, Statistics and Probability | video | free | Khan Academy |
| OpenIntro Statistics (open textbook) | book | free | OpenIntro |
| Kaggle Learn, Data Cleaning | interactive | free | Kaggle |
| Google Sheets | tool | free |
Plan
Step 1: Read charts critically
Outcome: Read and interpret a chart.
Pick three charts from Our World in Data. For each, write what the axes measure, what one mark represents, one claim the chart supports, and one it does not. Then find a chart in the news and look for a truncated axis, a missing baseline, or an unlabeled unit.
Step 2: Clean a dataset
Outcome: Clean a small tabular dataset.
Download a small dataset (a few hundred to a few thousand rows). In a spreadsheet, or following Kaggle’s data cleaning lessons, handle missing values, inconsistent formats, and duplicates. Keep a change log as you go: every row you remove or alter gets a line.
Step 3: Summarize and communicate
Outcome: Summarize a dataset and communicate findings.
Compute mean, median, range, and counts by category. Choose one chart that answers a real question about the data. Write a one-page findings note that a friend outside the field could follow.
Project
Complete the Dataset Cleaning Project: raw file, cleaned file, change log, and findings note.