30 March 2021 GC, R code to plot beeswarm
library("readxl")
library('data.table')
library("beeswarm")
library(tidyverse)
── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ── ✔ ggplot2 3.3.3 ✔ purrr 0.3.4 ✔ tibble 3.1.0 ✔ dplyr 1.0.5 ✔ tidyr 1.1.3 ✔ stringr 1.4.0 ✔ readr 1.4.0 ✔ forcats 0.5.1 ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ── ✖ dplyr::between() masks data.table::between() ✖ dplyr::filter() masks stats::filter() ✖ dplyr::first() masks data.table::first() ✖ dplyr::lag() masks stats::lag() ✖ dplyr::last() masks data.table::last() ✖ purrr::transpose() masks data.table::transpose()
read_usage <- function(path_in) {
dt <- read_excel(path_in)
dt <- dt[ -c(1, 2, 5)]
#names(dt)[2] <- 'BCD'
#names(dt)[3] <- 'CROS'
dt <- na.omit(dt)
return(dt)
}
path1 <- '/media/guido/LACIE/Cingle_Guido/Master/Headband/Usage_BCD_CROS.xlsx'
usage <- read_usage(path1)
usage
New names: * `` -> ...1
Device | Average_use_BCD |
---|---|
<chr> | <dbl> |
BP110 | 0.1 |
BP110 | 1.4 |
BP110 | 0.4 |
BP110 | 1.0 |
BP110 | 1.4 |
BP110 | 7.1 |
BP110 | 3.2 |
BP110 | 0.7 |
BP110 | 4.0 |
BP110 | 3.7 |
BP110 | 0.2 |
BP110 | 0.3 |
BP110 | 0.2 |
BP110 | 3.3 |
BP110 | 0.1 |
BP110 | 5.6 |
BP110 | 0.6 |
BP110 | 0.3 |
BP110 | 1.6 |
BP110 | 4.1 |
BP110 | 0.3 |
BP110 | 0.1 |
BP110 | 0.1 |
BP110 | 0.5 |
BP110 | 1.8 |
BP110 | 0.3 |
BP110 | 3.3 |
BP110 | 0.2 |
BP110 | 5.2 |
BP110 | 8.4 |
⋮ | ⋮ |
BAHA5P | 4.6 |
BAHA5P | 3.3 |
BAHA5P | 11.9 |
BAHA5P | 0.2 |
BAHA5P | 3.1 |
BAHA5P | 4.2 |
BAHA5P | 1.1 |
BAHA5P | 0.2 |
BAHA5P | 1.2 |
BAHA5P | 4.8 |
BAHA5P | 4.3 |
BAHA5P | 0.2 |
BAHA5P | 1.8 |
BAHA5P | 0.1 |
BAHA5P | 2.3 |
BAHA5P | 4.1 |
BAHA5P | 1.0 |
BAHA5P | 0.8 |
BAHA5P | 3.5 |
BAHA5P | 5.8 |
BAHA5P | 3.0 |
BAHA5P | 7.1 |
BAHA5P | 0.4 |
BAHA5P | 0.1 |
BAHA5P | 0.5 |
BAHA5P | 3.9 |
BAHA5P | 0.6 |
BAHA5P | 0.3 |
BAHA5P | 1.1 |
BAHA5P | 0.0 |
bt <- usage
bt[bt$Device == 'BP110', "Device"] <- "Both types"
bt[bt$Device == 'BAHA5P', "Device"] <- "Both types"
bp110 <- usage %>% filter(Device == 'BP110')
bh5 <- usage %>% filter(Device == 'BAHA5P')
all <- rbind(bp110, bh5, bt)
all
Device | Average_use_BCD |
---|---|
<chr> | <dbl> |
BP110 | 0.1 |
BP110 | 1.4 |
BP110 | 0.4 |
BP110 | 1.0 |
BP110 | 1.4 |
BP110 | 7.1 |
BP110 | 3.2 |
BP110 | 0.7 |
BP110 | 4.0 |
BP110 | 3.7 |
BP110 | 0.2 |
BP110 | 0.3 |
BP110 | 0.2 |
BP110 | 3.3 |
BP110 | 0.1 |
BP110 | 5.6 |
BP110 | 0.6 |
BP110 | 0.3 |
BP110 | 1.6 |
BP110 | 4.1 |
BP110 | 0.3 |
BP110 | 0.1 |
BP110 | 0.1 |
BP110 | 0.5 |
BP110 | 1.8 |
BP110 | 0.3 |
BP110 | 3.3 |
BP110 | 0.2 |
BP110 | 5.2 |
BP110 | 8.4 |
⋮ | ⋮ |
Both types | 4.6 |
Both types | 3.3 |
Both types | 11.9 |
Both types | 0.2 |
Both types | 3.1 |
Both types | 4.2 |
Both types | 1.1 |
Both types | 0.2 |
Both types | 1.2 |
Both types | 4.8 |
Both types | 4.3 |
Both types | 0.2 |
Both types | 1.8 |
Both types | 0.1 |
Both types | 2.3 |
Both types | 4.1 |
Both types | 1.0 |
Both types | 0.8 |
Both types | 3.5 |
Both types | 5.8 |
Both types | 3.0 |
Both types | 7.1 |
Both types | 0.4 |
Both types | 0.1 |
Both types | 0.5 |
Both types | 3.9 |
Both types | 0.6 |
Both types | 0.3 |
Both types | 1.1 |
Both types | 0.0 |
clm = colnames(usage)
sp = clm[-1]
ttl = "Average BCD daily use"
ttl = ""
ColorBlind3 <- c("#E69F00", "#56B4E9", "#009E73")
all$Device <- factor(all$Device,c("BP110","BAHA5P", "Both types"))
p <- boxplot(Average_use_BCD ~ Device, data = all, outline = FALSE,
ylab = "Average Daily Use [hours]",
xlab = "", cex.lab=1.4, main = ttl,
ylim=c(0, 14))
b <- beeswarm(Average_use_BCD ~ Device, data = all, pch = 16, col = ColorBlind3, add = TRUE)
tiff("/home/guido/R/cingle/figures/BCDusage.tiff", units="in", width=7, height=7, res=300)
ColorBlind3 <- c("#E69F00", "#56B4E9", "#009E73")
all$Device <- factor(all$Device,c("BP110","BAHA5P", "Both types"))
p <- boxplot(Average_use_BCD ~ Device, data = all, outline = FALSE,
ylab = "Average Daily Use [hours]",
xlab = "", cex.lab=1.4, main = ttl,
ylim=c(0, 14))
b <- beeswarm(Average_use_BCD ~ Device, data = all, pch = 16, col = ColorBlind3, add = TRUE)
dev.off()