AG真人百家乐官方网站

Skip to main content
NSF NEON, Operated by Battelle

Main navigation

  • AG真人百家乐官方网站 Us
    • Overview
      • Spatial and Temporal Design
      • History
    • Vision and Management
    • Advisory Groups
      • Science, Technology & Education Advisory Committee
      • Technical Working Groups (TWGs)
    • FAQ
    • Contact Us
      • Contact NEON Biorepository
      • Field Offices
    • User Accounts
    • Staff
    • Code of Conduct

    AG真人百家乐官方网站 Us

  • Data & Samples
    • Data Portal
      • Spatial Data & Maps
    • Data Themes
      • Biogeochemistry
      • Ecohydrology
      • Land Cover and Processes
      • Organisms, Populations, and Communities
    • Samples & Specimens
      • Discover and Use NEON Samples
        • Sample Types
        • Sample Repositories
        • Megapit and Distributed Initial Characterization Soil Archives
      • Sample Processing
      • Sample Quality
    • Collection Methods
      • Protocols & Standardized Methods
      • Airborne Remote Sensing
        • Flight Box Design
        • Flight Schedules and Coverage
        • Daily Flight Reports
          • AOP Flight Report Sign Up
        • Camera
        • Imaging Spectrometer
        • Lidar
      • Automated Instruments
        • Site Level Sampling Design
        • Sensor Collection Frequency
        • Instrumented Collection Types
          • Meteorology
          • Phenocams
          • Soil Sensors
          • Ground Water
          • Surface Water
      • Observational Sampling
        • Site Level Sampling Design
        • Sampling Schedules
        • Observation Types
          • Aquatic Organisms
            • Aquatic Microbes
            • Fish
            • Macroinvertebrates & Zooplankton
            • Periphyton, Phytoplankton, and Aquatic Plants
          • Terrestrial Organisms
            • Birds
            • Ground Beetles
            • Mosquitoes
            • Small Mammals
            • Soil Microbes
            • Terrestrial Plants
            • Ticks
          • Hydrology & Geomorphology
            • Discharge
            • Geomorphology
          • Biogeochemistry
          • DNA Sequences
          • Pathogens
          • Sediments
          • Soils
            • Soil Descriptions
        • Optimizing the Observational Sampling Designs
    • Data Notifications
    • Data Guidelines and Policies
      • Acknowledging and Citing NEON
      • Publishing Research Outputs
      • Usage Policies
    • Data Management
      • Data Availability
      • Data Formats and Conventions
      • Data Processing
      • Data Quality
      • Data Product Bundles
      • Data Product Revisions and Releases
        • Release 2021
        • Release 2022
        • Release 2023
        • Release 2024
        • Release-2025
      • NEON and Google
      • Externally Hosted Data

    Data & Samples

  • Field Sites
    • AG真人百家乐官方网站 Field Sites and Domains
    • Explore Field Sites

    Field Sites

  • Impact
    • Observatory Blog
    • Case Studies
    • Papers & Publications
    • Newsroom
      • NEON in the News
      • Newsletter Archive
      • Newsletter Sign Up

    Impact

  • Resources
    • Getting Started with NEON Data & Resources
    • Documents and Communication Resources
      • Papers & Publications
      • Outreach Materials
    • Code Hub
      • Code Resources Guidelines
      • Code Resources Submission
    • Learning Hub
      • Science Videos
      • Tutorials
      • Workshops & Courses
      • Teaching Modules
    • Research Support Services
      • Field Site Coordination
      • Letters of Support
      • Mobile Deployment Platforms
      • Permits and Permissions
      • AOP Flight Campaigns
      • Research Support FAQs
      • Research Support Projects
    • Funding Opportunities

    Resources

  • Get Involved
    • Advisory Groups
      • Science, Technology & Education Advisory Committee
      • Technical Working Groups
    • Upcoming Events
    • NEON Ambassador Program
      • Exploring NEON-Derived Data Products Workshop Series
    • Research and Collaborations
      • Environmental Data Science Innovation and Inclusion Lab
      • Collaboration with DOE BER User Facilities and Programs
      • EFI-NEON Ecological Forecasting Challenge
      • NEON Great Lakes User Group
      • NEON Science Summit
      • NCAR-NEON-Community Collaborations
        • NCAR-NEON Community Steering Committee
    • Community Engagement
      • How Community Feedback Impacts NEON Operations
    • Science Seminars and Data Skills Webinars
      • Past Years
    • Work Opportunities
      • Careers
      • Seasonal Fieldwork
      • Internships
        • Intern Alumni
    • Partners

    Get Involved

  • My Account
  • Search

Search

Learning Hub

  • Science Videos
  • Tutorials
  • Workshops & Courses
  • Teaching Modules

Breadcrumb

  1. Resources
  2. Learning Hub
  3. Tutorials
  4. Publish Code - From R Markdown to HTML with knitr

Tutorial

Publish Code - From R Markdown to HTML with knitr

Authors:

Last Updated: Apr 8, 2021

In this tutorial, we will cover the R knitr package that is used to convert R Markdown into a rendered document (HTML, PDF, etc).

Learning Objectives

At the end of this activity, you will:

  • Be able to produce (鈥榢nit鈥�) an HTML file from a R Markdown file.
  • Know how to modify chunk options to change the output in your HTML file.

Things You鈥檒l Need To Complete This Tutorial

You will need the most current version of R and, preferably, RStudio loaded on your computer to complete this tutorial.

Install R Packages

  • knitr: install.packages("knitr")
  • rmarkdown: install.packages("rmarkdown")

Share & Publish Results Directly from Your Code!

The knitr package allow us to:

  • Publish & share preliminary results with collaborators.
  • Create professional reports that document our workflow and results directly from our code, reducing the risk of accidental copy and paste or transcription errors.
  • Document our workflow to facilitate reproducibility.
  • Efficiently change code outputs (figures, files) given changes in the data, methods, etc.

Publish from Rmd files with knitr

To complete this tutorial you need:

  1. The R knitr package to complete this tutorial. If you need help installing packages, visit the R packages tutorial.
  2. An R Markdown document that contains a YAML header, code chunks and markdown segments. If you don't have an .Rmd file, visit the R Markdown tutorial to create one.
**When To Knit**: Knitting is a useful exercise throughout your scientific workflow. It allows you to see what your outputs look like and also to test that your code runs without errors. The time required to knit depends on the length and complexity of the script and the size of your data.

How to Knit

RStudio window with R Markdown template of new document and 'Knit HTML' button 
circled.
Location of the knit button in RStudio in Version 0.99.486. Source: National Ecological Observatory Network (NEON)

To knit in RStudio, click the knit pull down button. You want to use the
knit HTML for this lesson.

When you click the Knit HTML button, a window will open in your console titled R Markdown. This pane shows the knitting progress. The output (HTML in this case) file will automatically be saved in the current working directory. If there is an error in the code, an error message will appear with a line number in the R Console to help you diagnose the problem.

**Data Tip:** You can run `knitr` from the command prompt using: `render(鈥渋nput.Rmd鈥�, 鈥渁ll鈥�)`.

Activity: Knit Script

Knit the .Rmd file that you built in the last tutorial. What does it look like?

View the Output

RStudio windows of R Markdown file, with activity content added, 
and HTML document with text, code, output and Digital Surface Model plot figure.
R Markdown (left) and the resultant HTML (right) after knitting. Source: National Ecological Observatory Network (NEON)

When knitting is complete, the new HTML file produced will automatically open.

Notice that information from the YAML header (title, author, date) is printed at the top of the HTML document. Then the HTML shows the text, code, and results of the code that you included in the RMD document.

Data Institute Participants: Complete Week 2 Assignment

  • Read this week鈥檚 assignment closely.
  • Be sure to carefully check your knitr output to make sure it is rendering the way you think it should!
  • When you are complete, submit your .Rmd and .html files to the NEON Institute participants GitHub repository (NEONScience/DI-NEON-participants).
  • The files will have automatically saved to your R working directory, you will need to transfer the files to the /participants/pre-institute3-rmd/ directory and submitted via a pull request.

Questions?

If you have questions or comments on this content, please contact us.

Contact Us
NSF NEON, Operated by Battelle

Follow Us:

Join Our Newsletter

Get updates on events, opportunities, and how NEON is being used today.

Subscribe Now

Footer

  • AG真人百家乐官方网站 Us
  • Newsroom
  • Contact Us
  • Terms & Conditions
  • Careers
  • Code of Conduct

Copyright © Battelle, 2025

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

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