Mastering Time Series Visualization for Epidemiology
Understanding time series data is crucial in epidemiology—it helps uncover trends, detect disease outbreaks, and drive data-informed decisions for better health outcomes.
In my latest learning journey, I explored how to leverage ggplot2 and the tidyverse to visualize time series data effectively.
Key Skills Gained
Reshaping time series data using
pivot_longer()for better plotting.Creating clear and insightful line graphs in
ggplot2.Enhancing visualization aesthetics with custom labels, color palettes, and annotations.
Ability to use
geom_ribbon()to display confidence intervals.Applying smoothing techniques to highlight patterns in noisy data.
Comparing multiple time series using dual axes with
sec_axis()
For a step-by-step guide with practical examples, visit this site.