Writing functions make your analyses more readable and more repeatable. In this project, you'll perform an analysis of food prices in Rwanda, then wrap your code into functions in order to apply your analysis to other food types. Throughout the project, the ability to import, wrangle, manipulate, and forecast data will come in handy.
- 1Importing important price data
- 2Once more, with feeling
- 3Spring cleaning
- 4Potatoes are not a balanced diet
- 5Plotting the price of potatoes
- 6What a lotta plots
- 7Preparing to predict the future (part 1)
- 8Preparing to predict the future (part 2)
- 9Another day, another function to write
- 10The future of potato prices
- 11The final function
- 12Do it all over again
Curriculum Architect at DataCamp
Richie runs the Content Quality team at DataCamp. He has been using R since 2004, in the fields of proteomics, debt collection, and chemical health and safety. He has released almost 30 R packages on CRAN and Bioconductor – most famously the assertive suite of packages – as well as creating and contributing to many others. He also has written two books on R programming, Learning R and Testing R Code.