In this project, we'll learn data visualization and data cleaning using Microsoft Power BI. We'll cover DAX, the M language, the Power Query editor, and visualization. This is a great companion to Dataquest Power BI courses.
In this project, you'll gain an understanding of:
- What Power BI is and why you'd use it
- How to import data into Power BI
- How to transform and clean data using Power Query and the M language
- How to model relations
- How to calculate columns using DAX
You can find the Power BI report for this project here.
File overview:
Olympics.pbix- a Power BI report that mirrors what we'll do in this session
To follow this project, please install Power BI. These instructions can help you figure out how.
You'll need to download three files to follow this project:
- athlete_events.csv - contains information on athletes who competed in the Olympics.
- noc_regions.csv - contains information on how national olympic committee codes map to country names.
- country_population.csv - contains information on the population of each country.
The Olympic and NOC data is originally from Kaggle. The population data is from the World Bank.
- Data exploration - load the data in and explore it by creating visualizations
- Importing NOC data - load in information matching NOC codes to the actual country name. We'll then model the relationship.
- Add in medal columns - use Power Query editor to add some additional columns with medal information.
- Creating a filled map - create a map that shows the number of medals each country earned.
- Creating an animated map - make a map that shows how Olympic participation changed over time.
- Combine population data - load in population data and match it to our existing data.
- Create rolling medal counts - show a rolling total of medals earned by country.