To complete this project, I will first import the three wide-format datasets from GitHub into R. I will then use the tidyr and dplyr packages to reshape each dataset from wide format to tidy (long) format using functions such as pivot_longer(). After tidying the data, I will standardize column names, convert variables to appropriate data types, and remove or handle any missing values. Once the data is in tidy format, I will perform summary analyses and create visualizations to better understand trends in the data.
One potential challenge is ensuring that the wide-format columns are correctly reshaped into tidy format without losing information. Another challenge may be handling inconsistent variable types or missing values during the transformation process. Additionally, since some column names represent categories such as months or age groups, careful renaming and restructuring will be required to ensure the data follows tidy data principles and can be easily analyzed.