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.


Vector 03: When Vector Data Don't Line Up - Handling Spatial Projection & CRS in R

This tutorial will cover how to identify the CRS of a spatial vector object in R. It will also explore differences in units associated with different projections and how to reproject data using spTransform in R. Spatial data need to be in the same projection in order to successfully map and process them in non-gui tools such as R.

Time Series 00: Intro to Time Series Data in R - Managing Date/Time Formats & Simple Plots using ggplot2

This tutorial will demonstrate how to import a time series data set stored in .csv format into R. It will explore data classes and will walk through how to convert date data, stored as a character string, into a date class that R can recognize and plot efficiently.

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 Culmination Activity: Plot using Facets & Plot NDVI with Time Series Data

This tutorial is a data integration wrap-up culmination activity for the spatio-temporal time series tutorials.

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.


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