Event - Workshop

NEON @ ESA: Working with Time Series in R using NEON Data Workshop

Aug 6, 2017

Hosted By:

ESA & NEON

The temporal scale of ecological research is expanding given increased continental and global availability of time series data coming from long term data collection efforts such as NEON, LTER and Fluxnet. Given increased data availability, there is a need to implement efficient, well-documented and reproducible workflows in tools like R.

This workshop will teach participants how to import, manipulate, format and plot time series data stored in .csv format in R while working with NEON data. We will work with temperature and phenology data to explore working with and visualizing data with different time scale intervals. Key skills learned will include:

  1. working with data.frames in R (dplyr package),
  2. converting timestamps stored as text strings to R date or datetime (e.g. POSIX) classes (lubridate package),
  3. aggregating data across different time scales (day vs month) and
  4. plotting time series data (ggplot2 package).

Required Prior Knowledge

The workshop will assume that participants have a basic level of familiarity with working with data in R, including installing and loading packages, and data import.

This 5-hr workshop will be taught at the 2017 meeting of the Ecological Society of America (ESA) in Portland, OR. You must be a registered attendee of the conference and register for this workshop with your ESA registration to participate in this workshop. For more information, visit the ESA 2017 annual meeting website.

Things You’ll Need For The Workshop

To participant in this workshop, you will need a laptop with the most current version of R, and preferably RStudio, loaded on your computer.

For details on setting up RStudio in Mac, PC, or Linux operating systems please see the instructions below.

Install R Packages

Please have these packages installed and updated prior to the start of the workshop.

  • dplyr: install.packages("dplyr")
  • ggplot2: install.packages("ggplot2")
  • lubridate: install.packages("lubridate")
  • scales: install.packages("scales")
  • tidyr: install.packages("tidyr")
  • gridExtra: install.packages("gridExtra")

Updating R Packages

In RStudio, you can go to Tools --> Check for package updates to update previously installed packages on your computer.

Or you can use update.packages() to update all packages that are installed in R automatically.

More on Packages in R

Download Data

NEON Teaching Data Subset: Plant Phenology & Single Aspirated Air Temperature

The data used in this lesson were collected at the National Ecological Observatory Network's Domain 02 field sites. This teaching data subset represent a small subset of the data NEON will collect over 30 years and at 20 domains across the United States. NEON data are available on the NEON data portal.

DOWNLOAD DATASET

 

Once you have downloaded the data, please set up a "data" directory as a parent directory to these three uncompressed directories. Set your R working directory to this "data" directory prior to the beginning of the workshop. If you would like further instruction please see the bottom of this page for detailed instructions.

Workshop Instructors

  • Megan A. Jones; @meganahjones, Staff Scientist/Science Educator; NEON program, Battelle
  • Natalie Robinson; Staff Scientist, Quantitative Ecologist; NEON program, Battelle
  • Lee Stanish; Staff Scientist, Microbial Ecologist; NEON program, Battelle

Please get in touch with the instructors prior to the workshop with any questions.

Twitter?

Please tweet using the hashtag #WorkWithData & @NEON_Sci during this workshop!

Charging Station

ESA has informed us there will not be power available at each table. However, there will be a charging station in the room. If you are concerned about battery during the workshop, consider reducing your screen brightness at the start of the workshop.

Before the Workshop

Prior to the workshop you should have R and, preferably, RStudio installed on your computer.

Setting Up R & RStudio

Windows R/RStudio Setup

Once R and RStudio are installed, click to open RStudio. If you don't get any error messages you are set. If there is an error message, you will need to re-install the program.

Mac R/RStudio Setup

  • Go to CRAN and click on Download R for (Mac) OS X
  • Select the .pkg file for the version of OS X that you have and the file will download.
  • Double click on the file that was downloaded and R will install
  • Go to the RStudio Download page
  • Under Installers select RStudio 0.98.1103 - Mac OS X XX.X (64-bit) to download it.
  • Once it's downloaded, double click the file to install it

Once R and RStudio are installed, click to open RStudio. If you don't get any error messages you are set. If there is an error message, you will need to re-install the program.

Linux R/RStudio Setup

  • R is available through most Linux package managers. You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R).
  • To install RStudio, go to the RStudio Download page
  • Under Installers select the version for your distribution.
  • Once it's downloaded, double click the file to install it

Once R and RStudio are installed, click to open RStudio. If you don't get any error messages you are set. If there is an error message, you will need to re-install the program.

 

Set Working Directory to Downloaded Data

1) Download Data

After clicking on the Download Data button, the data will automatically download to the computer.

2) Locate .zip file

Second, find the downloaded .zip file. Many browsers save downloaded files to your computer’s Downloads directory. If you have previously specified a specific directory (folder) for downloaded files, the .zip file will download there.

3) Move to **data** directory

Third, move the downloaded file to a directory called data within the Documents directory on your computer. You can choose to place the data in other locations, however, you will need to remember to set your R Working Directory to that location and not as we demonstrate in the workshop.

4) Unzip/uncompress

Fourth, we need to unzip/uncompress the file so that the data files can be accessed. Use your favorite tool that can unpackage/open .zip files (e.g., winzip, Archive Utility, etc). The files will now be accessible in three directories:

These directories contain all of the subdirectories and files that we will use in this workshop.

5) Set working directory

Fifth, we need to set the working directory in R to this data directory that is parent to the directories containing the data we want. For complete directions, on how to do that check out the Set A Working Directory in R tutorial.

Location:

Portland, OR
United States