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  3. Tutorials

Tutorials

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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.

All materials are freely available for you to use and reuse. We suggest the following citation for tutorials: 
[AUTHOR(S), NEON (National Ecological Observatory Network)]. Data Tutorial: [TUTORIAL NAME]. [URL] (accessed [DATE OF ACCESS]). See Citation Guidelines for examples, and for guidance in citing data and code.

Tutorials

Start Tutorial

Work With NEON's Plant Phenology Data

1 hour
Learn to work with NEON plant phenology observation data (NEON.DP1.10055).
Start Tutorial

Work with NEON's Single-Aspirated Air Temperature Data

1 hour
This tutorial demonstrates how to work with NEON single-aspirated air temperature data. Specific tasks include conversion to POSIX date/time class, subsetting by date, and plotting the data.
Start Tutorial

Working With Raster Time Series Data in R

This series covers how to open, work with and plot with multi-band raster data and raster time series data in R using both plot and rasterVis levelPlot.
Series
3 part series
Start Tutorial

Working With Time Series Data Within a Nested HDF5 File in R

1.0 - 1.5 Hours
Explore, extract and visualize temporal temperature data collected from a NEON flux tower from multiple sites and sensors in R. Learn how to extract metadata and how to use nested loops and dplyr to perform more advanced queries and data manipulation.

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Copyright © Battelle, 2019-2020

The National Ecological Observatory Network is a major facility fully funded by the National Science Foundation.

Any opinions, findings and conclusions or recommendations expressed in this material do not necessarily reflect the views of the National Science Foundation.