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geospatial_data_manipulation's Introduction

Data Science Repo

Containing code snippets for niche topics, workflows and common design patterns.

RshinyHelpers

  • Check out the RshinyHelpers package for #rstats users that accumulates shiny functions and css helpers that I use only once or twice per shiny app. Also contains misc data functions that I find intuitive but don't fit any tidy workflow.

  • It is not available on CRAN. Install using devtools

  if(!require(devtools)) install.packages('devtools')
    devtools::install_github('aarong1/RshinyHelpers')

and attach the package into global namespace

  library(RShinyHelpers)

Personal sites

Not really being a developer, extensive use of static rendered sites helped for web apps and documentation. They were really easy to use with a low overhead, to both simplify html, js interactivity, and in deployment to Github Pages and Netlify. Full credit goes to the maintainers of the Hugo Themes

Hugo and GatsbyJS were popular options and would recommend either, both having a selection of theming options out of the box.

Gatsby in particular had a steep learning curve, being based on reactjs, but had the greatest reward.

Table of Contents

Itemised list

Repo What is it Tech Site
RshinyHelpers R package R, shiny, js, html, css Documentation
TCD Ising Model Ferromagnetic simulation Python
Geospatial NI PC Shapefiles R
Covid ABM Agent based Epi model Python
Persistent Storage Fullstack Shiny w/aws backend R, AWS, mysql Site
Epidemiology model Bayesian Epi Model R,stan Documentation
aarong1.github.io GH pages site Gatsbyjs, reactjs, html, css, js Personal Site
Academic Professional Site Hugo, netlify CV

Aaron

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