Data Cleaner: Rescue a Real-World Mess
Take a dirty table full of missing values and text where numbers belong, and produce clean, analysis-ready data with imputation you can defend.
What you'll be able to build
Take a dirty table full of missing values and text where numbers belong, and produce clean, analysis-ready data with imputation you can defend. Along the way you pick up real, transferable R skills, not just this one project:
- type coercion with as.numeric and suppressWarnings
- detecting missing data with is.na()
- logical subsetting to target bad rows
- mean(..., na.rm = TRUE) and imputation
- summarizing data quality (counts of fixed rows)
- building a repeatable cleaning function
A course like this one
Yours is built from your own placement, so module count and depth will differ. This map shows what a intermediate-level R learner building Data Cleaner actually gets.
- Module 1: Vectors, values, and the shape of R5 lessons
Builds the vector for your data cleaner.
- Module 2: Data frames, factors, and tidy shapes5 lessons
Builds the apply pipeline workflow for your data cleaner.
- Module 3: Control flow and predicting vectorized output5 lessons
Builds the data frame that powers your data cleaner.
- Module 4: Functions, the apply family, and debugging5 lessons
Builds the reusable factor for your data cleaner.
- Module 5: Designing a statistical pipeline5 lessons
Builds the simulation for your data cleaner.
- Module 6: Shipping a reproducible analysis3 lessons
Builds the summary table for your data cleaner.
How the lessons actually work
Every lesson has you predict what a piece of R code will output before you run it, then run it for real in your browser and fix what you got wrong. Each module ends in a challenge gate with hidden tests, so you can't advance until your code actually works. The course closes with a capstone that assembles everything into Data Cleaner, and a runnable proof page tied to your own code.
Common questions
How long does the Data Cleaner: Rescue a Real-World Mess course take?
about 7 hours, across 6 modules and 28 lessons, at roughly 15 minutes per lesson. Your own course may run shorter or longer, since it's sized to your placement result, not a fixed template.
Do I need experience?
Some. This is an intermediate-tier R project, so it assumes you're comfortable with R basics and pushes past them.
How much does it cost?
$15 one-time, no subscription. The first module is free, so you can see exactly how the course teaches before you pay for the rest.