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Focussing on greta

Nicholas Tierney njtierney

Focussing on greta
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rxaviers / gist:7360908
Last active May 18, 2021
Complete list of github markdown emoji markup
View gist:7360908


:bowtie: :bowtie: 😄 :smile: 😆 :laughing:
😊 :blush: 😃 :smiley: ☺️ :relaxed:
😏 :smirk: 😍 :heart_eyes: 😘 :kissing_heart:
😚 :kissing_closed_eyes: 😳 :flushed: 😌 :relieved:
😆 :satisfied: 😁 :grin: 😉 :wink:
😜 :stuck_out_tongue_winking_eye: 😝 :stuck_out_tongue_closed_eyes: 😀 :grinning:
😗 :kissing: 😙 :kissing_smiling_eyes: 😛 :stuck_out_tongue:
santisbon /
Last active May 13, 2021
Deploying from Git branches adds flexibility. Bring your feature branch up to date with master and deploy it to make sure everything works. If everything looks good the branch can be merged. Otherwise, you can deploy your master branch to return production to its stable state.

Updating a feature branch

First we'll update your local master branch. Go to your local project and check out the branch you want to merge into (your local master branch)

$ git checkout master

Fetch the remote, bringing the branches and their commits from the remote repository. You can use the -p, --prune option to delete any remote-tracking references that no longer exist in the remote. Commits to master will be stored in a local branch, remotes/origin/master

tylermorganwall / india_historical_map.R
Last active Apr 13, 2021
Historical Map of India with 3D elevation
View india_historical_map.R
#Load QGIS georeference image (see
testindia = raster::stack("1870_southern-india_modified.tif")
#Set bounding box for final map (cut off edges without data, introduced via reprojection)
india_bb = raster::extent(c(68,92,1,20))
cropped_india = raster::crop(testindia, india_bb)
#Convert to RGB array
Pakillo / Rmarkdown-fontsize.Rmd
Created Jan 22, 2015
Changing font sizes of HTML ouput in Rmarkdown
View Rmarkdown-fontsize.Rmd
title: "Untitled"
author: "Francisco Rodriguez-Sanchez"
date: "Thursday, January 22, 2015"
output: html_document
<style type="text/css">
body, td {
jennybc / twee-demo.Rmd
Last active Oct 15, 2020
twee(): emulating the tree directory listing command
View twee-demo.Rmd
title: "twee demo"
author: "Jenny Bryan"
date: "17 August, 2014"
toc: TRUE
keep_md: TRUE
nstrayer / simulate_mnar_data.R
Created Jan 21, 2020
R Script to simulate missing not at random data and look at performance of different imputation strategies.
View simulate_mnar_data.R
n <- 150
sensitivity_threshold <- 5
data <- tibble(
a = rgamma(n = n, shape = 5, rate = 0.5),
b = rgamma(n = n, shape = a/2, rate = 0.5)
generate_missing_data <- function(i){
hadley /
Created Feb 13, 2015
Advise for teaching an R workshop

I think the two most important messages that people can get from a short course are:

a) the material is important and worthwhile to learn (even if it's challenging), and b) it's possible to learn it!

For those reasons, I usually start by diving as quickly as possible into visualisation. I think it's a bad idea to start by explicitly teaching programming concepts (like data structures), because the pay off isn't obvious. If you start with visualisation, the pay off is really obvious and people are more motivated to push past any initial teething problems. In stat405, I used to start with some very basic templates that got people up and running with scatterplots and histograms - they wouldn't necessary understand the code, but they'd know which bits could be varied for different effects.

Apart from visualisation, I think the two most important topics to cover are tidy data (i.e. + tidyr) and data manipulation (dplyr). These are both important for when people go off and apply

View css.R
#' Create a CSS ruleset
#' Create a CSS ruleset consisting of a selector and one-or-more property declarations,
#' or, if no \code{.selector} is given, create an inline style string
#' The list of included properties is not a complete list, but rather an
#' abbreviated list from
#' \url{}
View fools_five.R
f <- function(...) {
function(df) with(df, ...)
footate <- function(.data, ...) {
dots <- list(...)
for (column in names(dots)) {
.data[[column]] <- dots[[column]](.data)
markdly / html-multiple-choice.Rmd
Last active Jun 13, 2019
Multiple choice quiz question Rmarkdown
View html-multiple-choice.Rmd
theme: cerulean
### Example html multiple choice question using Rmarkdown
<!-- Render this Rmarkdown doc to html to make an interactive html / js multiple choice question -->