This presentation covered the use of the "anomalize" package to detect outliers in time-series data, along with a brief introduction to the “plotly” package to create interactive charts and graphs. Learn how to make interactive charts to visually examine your data for possible errors or outliers, and then how to automate the process of outlier detection for large datasets (such as a year's worth of hourly air quality measurements). These tools can help tribal environmental professionals streamline the work of data analysis and cleanup prior to reporting it to the EPA or other agencies.
Files can be found in the Attachments tab.
