The Forking GitHub Workflow
Last modified: May 26, 2016This page describes how to contribute to this repo through the forking workflow.
Source:
National Ecological Observatory Network (NEON)
Devoted to open data and open source in science and education.
This site contains the DEVELOPMENT lessons for the NEON Data Skills website.
This page describes how to contribute to this repo through the forking workflow.
This is a sample post to document and explore available styles. Description should be fully in PLAIN TEXT -- no code text
This page overviews the tag and category structure on the NDS site.
This lesson will walk through the basic purpose and structure of metadata stored in EML (Ecological Metadata Language) format. We will work with an EML file created for an atmospheric dataset by the Harvard Forest LTER, using the R/OpenSci EML library for R.
This lesson walks through the steps need to download and visualize Palmer Drought Index Data in R to better understand the Drivers and Impacts of the 2013 Colorado floods.
This lesson walks through the steps need to download and visualize Precipitation Data and USGS Stream Discharge data in R to better understand the Drivers and Impacts of the 2013 Colorado floods.
This page provides and overview and introductory materials on the 2013 Colorado floods.
About description here.
This page provides materials on ecological disturbances, the 2013 Colorado floods, disturbance return intervals, and the basics of LiDAR. This material will prepare students to learn about and discuss how data can be used to increase our understanding of the causes and effects of a disturbance event.
About description here.
About description here.
The overview page I used at CU 3 Dec 2015.
About the boulder flood.
A nice step by step walk through of customizing plots in R GGPLOT2.
This cheatsheet covers the basics of using python to perform shell (operating system) commands (make director, rename files, etc).
This Python cheatsheet covers the basics of string and numeric operators and datatypes in Python.
Rstudio has developed a series of cheat sheets that are pretty nice. My favorite is the data wrangling cheat sheet!
Nic Webber shared this R-Python-Matlab cheat sheet.