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@goldingn
goldingn / parallel_zoon.R
Created Oct 31, 2017
example of executing a zoon workflow in parallel (using experimental branch)
View parallel_zoon.R
# install the experimental parallel branch
# remotes::install_github("zoonproject/zoon@parallel")
library (zoon)
# example workflow for 4 independent models that may take a while to run
run_wf <- function () {
workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKBioclim,
process = Replicate(Background(n = 1000), 4),
model = GBM(max.trees = 10000),
@viciana
viciana / DatosClimaAndalucia.R
Created Apr 4, 2017
Ejemplo de descarga de datos climaticos
View DatosClimaAndalucia.R
# require(devtools)
# install_github('SevillaR/Andaclima')
require(Andaclima)
rm(list = ls())
stations <- getAndalusia_ACS()
metainfo <- getMetaData(provincia = stations$province.code,
estacion = stations$station.code ,
View building_a_module_examples.R
install.packages('zoon')
library(zoon)
vignette('Building_a_module')
#############
## Simples ##
#############
@jhollist
jhollist / beamer_two_col.Rmd
Created Feb 3, 2016
This .Rmd shows how to use two (or more) columns in a Beamer Presentation from RStudio
View beamer_two_col.Rmd
---
title: "Untitled"
author: "Jeff W. Hollister"
date: "2/2/2016"
output: beamer_presentation
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
@jesperronn
jesperronn / docx2md.md
Last active Jun 21, 2019 — forked from aembleton/docx2md.md
Convert a Word Document into MD
View docx2md.md

Converting a Word Document to Markdown in One Move

The Problem

A lot of important government documents are created and saved in Microsoft Word (*.docx). But Microsoft Word is a proprietary format, and it's not really useful for presenting documents on the web. So, I wanted to find a way to convert a .docx file into markdown.

Installing Pandoc

On a mac you can use homebrew by running the command brew install pandoc.

The Solution

View question.csv
belief y2015 y2014
Improves the security posture of my organization 0.75 0.71
Improves the security posture of the nations critical infrastructure 0.63 0.64
Reduces the cost of detecting and preventing cyber attacks 0.22 0.21
Improves situational awareness 0.60 0.54
Fosters collaboration among peers and industry groups 0.48 0.51
Enhances the timeliness of threat data 0.11 0.16
Makes threat data more actionable 0.21 0.24
@danlwarren
danlwarren / thin.max.R
Last active May 21, 2019
thin.max.R, a function for rarefying point data in any number of dimensions
View thin.max.R
# Function to rarefy point data in any number of dimensions. The goal here is to
# take a large data set and reduce it in size in such a way as to approximately maximize the
# difference between points. For instance, if you have 2000 points but suspect a lot of
# spatial autocorrelation between them, you can pass in your data frame, the names (or indices)
# of the lat/lon columns, and the number 200, and you get back 200 points from your original data
# set that are chosen to be as different from each other as possible given a randomly chosen
# starting point
# Input is:
#
@benmarwick
benmarwick / tables.Rmd
Last active Dec 31, 2017
Methods for tables with rmarkdown
View tables.Rmd
---
title: "A few methods for making tables in rmarkdown"
output: html_document
---
Updates:
Packages that have appeared since my original look into this, and seem great:
https://github.com/yihui/printr
@sckott
sckott / crossref_alm.md
Created Feb 24, 2014
Get alm data for DOIs via Crossref using the alm R package
View crossref_alm.md

load alm

library(alm)

Define vector of DOIs, and search

Remember to get your api key, pass it in in the key parameter. Notice that we are passing the base url for the Crossref API, whereas the default is for the PLOS url http://alm.plos.org/api/v3/articles

@leeper
leeper / update_github.R
Last active Oct 23, 2015
Update packages if a newer version is available from GitHub
View update_github.R
library('devtools')
library('utils')
library('httr')
update_github <-
function(ask = TRUE, ...){
installed <- installed.packages()
oldVersion <- installed[,'Version']
urls <- sapply(names(oldVersion), function(x){
d <- packageDescription(x)
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