Introduction to Shiny

Introduction to Shiny

Access the GitHub repository for this presentation (with the presentation pdf and code for examples) at https://github.com/ufrmeetup/shiny-example.

Wildlife tracking data in R

Simona’s presentation can be found here: http://www.r-gators.com/pdf/wildlife-tracking-data.pdf The RData file and RMarkdown file (used to make the rest of this post) can be downloaded at the GitHub repository here https://github.com/ufrmeetup/picardi. If you’re unfamiliar GitHub, you can download a zipped file by pressing the green “Clone or download” button on the right of that page. From there just unzip the folder and click on the .Rproj file (requires RStudio to be installed).

Introduction to Dataframes in R

link to pdf Reading CSV datafiles into R We often store our data in comma seperated value (CSV) files, which can be read into R using the read.csv() function: # Download example .csv file download.file("https://ndownloader.figshare.com/files/2292169", "data/portal_data_joined.csv") # Save into variable surveys <- read.csv('data/portal_data_joined.csv') Note: this code requires having a data/ folder in your project Functions for characterizing dataframe We can run the name of the variable to view the dataframe, but often there will be too much information to display in the console