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.

Code for all script based tutorials can be downloaded at the end of the tutorial. Original files can also be found on GitHub.


Data Activity: Visualize Palmer Drought Severity Index Data in R to Better Understand the 2013 Colorado Floods

This tutorial walks through how to download and visualize Palmer Drought Severity Index data in R. The data specifically downloaded for this activity allows one to to better understand a driver of the 2013 Colorado floods.

Data Management using National Ecological Observatory Network’s (NEON) Small Mammal Data with Accompanying Lesson on Mark Recapture Analysis

In this lesson and accompanying teaching module, students use small mammal trapping data from the National Ecological Observatory Network to understand necessary steps of data management from field collected data to data analysis. Students explore this in the context of estimating small mammal population size using the Lincoln-Peterson model.

Open HDF5 files with Python Sample Code

This tutorial provides basic code for opening an HDF5 file in Python using the h5py, numpy, and matplotlib libraries.

Interactive Data Vizualization with R and Plotly

Learn the basics of how to use the plotly package to create interactive plots and use the Plotly API in R to share these plots.

Hierarchical Data Formats - What is HDF5?

0.25 - 0.5 Hours
An brief introduction to the Hierarchical Data Format 5 (HDF5) file/data model. Learn about how HDF5 is structured and the benefits of using HDF5.


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