Importing and Cleaning Data
Apply your importing and data cleaning skills to real-world soccer data.
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10 tasks
105 participants
1,500 XP
Project Description
Note: this Project is soft launched, which means you may experience bugs. Please click "Report an Issue" in the top-right corner of the Project interface to provide feedback.
Your boss at Crunching Numbers needs you to determine which match and stadium had the highest attendance during the 2019 FIFA Women's World Cup. Use your data import and cleaning skills to dig through the dirty data, clean it up, and present your boss with polished graphs.
This project lets you apply your skills from Introduction to the Tidyverse, Importing Data in R (Part 1), and Cleaning Data in R. We recommend that you take these courses before starting this project.
These data come from the online 2019 FIFA Women's World Cup match reports.
Project Tasks
- 1Importing data part 1
- 2Importing data part 2
- 3Removing rows of NA
- 4Replacing NA
- 5separate() and replace_na()
- 6Plotting for outliers
- 7What to do with the outlier?
- 8A pretty boxplot
- 9A pretty line plot
- 10Wrap up
Erin LaBrecque
Instructor at DataCamp
Erin is a marine geospatial research ecologist who combines physical and biological spatiotemporal data to understand marine ecosystems. She received her Ph.D. in Marine Science and Conservation from Duke University and is passionate about science communication and data visualization. When she is not playing with environmental and species datasets, Erin can be found hiking with her dog.
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R