Pakillo

# Install R latest version: https://cloud.r-project.org/
# For installing R on Linux, check out https://docs.rstudio.com/resources/install-r/
# Instructions: https://moderndive.netlify.app/1-getting-started.html

# Install RStudio latest version: https://www.rstudio.com/products/rstudio/download/#download

# Open RStudio and install some R packages using the code below:

install.packages(c(
  "tidyverse",

Pakillo

# Install R latest version: https://cloud.r-project.org/

# Install RStudio latest version: https://www.rstudio.com/products/rstudio/download/#download

# Install R packages below:

install.packages(c(
  "rmarkdown", 
  "knitr", 
  "dplyr", 

Pakillo

## Using {biscale} to plot bivariate raster maps

library(ggplot2)
library(biscale)
library(cowplot)
library(raster)
#> Loading required package: sp

Pakillo

# Install R latest version: https://cloud.r-project.org/

# Install RStudio latest version: https://www.rstudio.com/products/rstudio/download/#download

# Install R packages below:

install.packages("remotes")

install.packages("workflowr")
remotes::install_github("benmarwick/rrtools")

Pakillo

polygonizer <- function(x, outshape=NULL, gdalformat = 'ESRI Shapefile', 
                        pypath=NULL, readpoly=TRUE, quietish=TRUE) {
  # x: an R Raster layer, or the file path to a raster file recognised by GDAL
  # outshape: the path to the output shapefile (if NULL, a temporary file will be created)
  # gdalformat: the desired OGR vector format
  # pypath: the path to gdal_polygonize.py (if NULL, an attempt will be made to determine the location
  # readpoly: should the polygon shapefile be read back into R, and returned by this function? (logical)
  # quietish: should (some) messages be suppressed? (logical)
  if (isTRUE(readpoly)) require(rgdal)
  if (is.null(pypath)) {

Pakillo

library(ggplot2)

t <- 1:100  # create time sequence

# warming trend, constant variance
clima <- data.frame(t = t,
                    temp = rnorm(100, 15 + 0.03*t, sd = 1))

# warming trend + increasing variance
clima <- data.frame(t = t,

Pakillo

---
title: "Having separate reference lists in an Rmarkdown document"
author: "F. Rodriguez-Sanchez"
output:
  github_document:
    pandoc_args: --lua-filter=multiple-bibliographies.lua
bibliography_main: main.bib
bibliography_suppl: suppl.bib
---

Pakillo

https://stackoverflow.com/a/58679929

See also 

http://latex-beamer-class.10966.n7.nabble.com/Hiding-frames-td907.html

https://tex.stackexchange.com/questions/200151/remove-frame-from-presentation

https://tex.stackexchange.com/questions/200151/remove-frame-from-presentation

Pakillo

As far as I know Rstudio does not count words or characters at the moment, which would be useful particularly when writing Rmarkdown.

This is a quick shortcut using word_count and character_count functions from qdap package. See below for two wrapper functions that simplify their use.

library("qdap")

Just select and copy the text to the clipboard and then run in the console:

Pakillo

swatch <- function(x) {
  # x: a vector of colours (hex, numeric, or string)
  par(mai=c(0.2, max(strwidth(x, "inch") + 0.4, na.rm = TRUE), 0.2, 0.4))
  barplot(rep(1, length(x)), col=rev(x), space = 0.1, axes=FALSE, 
          names.arg=rev(x), cex.names=0.8, horiz=T, las=1)  
}

# Example:
# swatch(colours()[1:10])
# swatch(iwanthue(5))