aurielfournier

library(sjPlot)
library(sjmisc)
library(lme4)
# load sample data set.
data(efc)

efc$scale_c12hour <- scale(efc$c12hour)
efc$scale_e15reat <- scale(efc$e15relat)

m <- glmer(c175empl ~ scale_c12hour + scale_e15reat + (1|resttotn), data=efc, family=binomial(link = "logit"))

aurielfournier

dat <- data.frame(A=c(1,2,3,4,5,6), B=c("Dog","Cat","Bird"))

dat2 <- dat[dat$B!="Bird",]

uni <- unique(dat2$B)

dat2$B <- factor(dat2$B, levels=uni)

aurielfournier

dfa <- data.frame(a=1, b=2, c=3)
dfb <- data.frame(a=1, b=2, c=3)
dfc <- data.frame(a=1, b=2, c=3)

dflist <- list()

dflist[["dfa"]] <- dfa
dflist[["dfb"]] <- dfb
dflist[["dfc"]] <- dfc

aurielfournier

library(ggplot2)
library(tidyverse)

faithful$group <- factor(ifelse(faithful$eruptions>3, 1, 0))

subfaith <- faithful %>% filter(group=="1")

ggplot(data=faithful,aes(waiting, eruptions, color = group)) +
  geom_point() +
  stat_ellipse(data=subfaith,aes(waiting, eruptions, color = group))

aurielfournier

library(maptools)

## --- from http://www.naturalearthdata.com/downloads/10m-physical-vectors/
srange <- readShapePoly("gis/ne_10m_lakes") 

## --- Only the largest lakes
srange <- srange[srange$scalerank==0,]

aurielfournier

library(tidyverse)

data(iris)

sub_iris <- iris %>% 
              filter(Species != "setosa") 
              
model <- t.test(Sepal.Length ~ Species, data=sub_iris)

aurielfournier

Please cite all software and versions of those software which you use in your methods section, this includes R packages. If you are using R, you can find the citation for your R version with >citation() and for a particular package by using the >citation(“packagename”) function.

Roughly 8% of men, and 1 in 200 women are red-green color blind, so likely will be some of the readers of your paper. Please select a color-blind friendly color scheme for any figures where you use color. http://colorbrewer2.org/ is a great resource for this. If you are using R to make your figures, the RColorBrewer package can be used to easily bring those color schemes into R and apply them to your figures.

aurielfournier

library(purrr)
library(repurrrsive)

data(sw_films)
data(sw_people)
# here is the list
swfilms <- map(sw_films, "characters") %>% 
  set_names(map_chr(sw_films, "title"))
# 
character_df <- map_df(sw_people, `[`, 

aurielfournier

library(ggplot2)

dat <- data.frame(bars = rep(c("a","b","c","d"), each=3),
                  stacks = rep(c("a","b","c"), times=4),
                  value = c(20,60,20,10,70,20,70,10,20,40,40,20))

dat$stacks <- as.character(dat$stacks)

ggplot(data=dat, aes(x=bars, y=value, fill=stacks))+
  geom_bar(stat="identity")

aurielfournier

world_map <- rworldmap::getMap()

world_map@data$id = rownames(world_map@data)

world_map.points <- ggplot2::fortify(world_map, region="id")
# Error: IllegalArgumentException: Points of LinearRing do not form a closed linestring