Data Tutorials

Looking to improve your data skills using tools like R or Python? Want to learn more about working with a specific NEON data product? NEON develops online tutorials to help you improve your research. These self-paced tutorials are designed for you to used as standalone help on a single topic or as a series to learn new techniques.

Please note this section is currently under development, to explore additional tutorials in the interim, visit our older NEON Data Skills portal.

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Time Series 04: Subset and Manipulate Time Series Data with dplyr

In this tutorial, we will use the group_by, summarize and mutate functions in the `dplyr` package to efficiently manipulate atmospheric data collected at the NEON Harvard Forest Field Site. We will use pipes to efficiently perform multiple tasks within a single chunk of code.

Time Series 03: Cleaning & Subsetting Time Series Data in R - NoData Values & Subset by Date

This tutorial explores how to deal with NoData values encountered in a time series dataset, in R. It also covers how to subset large data files by date and export the results to a csv (text format) file.

Time Series 01: Why Metadata Are Important: How to Work with Metadata in Text & EML Format

This tutorial covers what metadata are, and why we need to work with metadata. It covers the 3 most common metadata formats: text file format, web page format and Ecological Metadata Language (EML).

Time Series 06: Create Plots with Multiple Panels, Grouped by Time Using ggplot Facets

This tutorial covers how to plot subsetted time series data (e.g., plot by season) using facets() and ggplot2. It also covers how to plot multiple metrics in one display panel.

Convert to Julian Day

This tutorial explains why Julian days are useful and teaches how to create a Julian day variable from a Date or Data/Time class variable.

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