I'm importing a df and then running hist() on the df:
df <- read.table("https://leicester.figshare.com/ndownloader/files/23581310", sep = ",", header = TRUE, stringsAsFactors = FALSE)
hist(df)
but it doesn't show the histograms of all 124 columns - only a subset. I'm not sure why? How do I get a histogram of all the columns in a df? I want to be able to run hist() on the entire data frame because it also shows the number of values/missing values at the bottom of each histogram.
I wonder how you could at all use hist in a data frame without Vectorizeing it. Best would be you use a different device such as the png.
png('foo.png', 2560, 1440)
par(mfrow=c(12, 11))
Vectorize(hist)(df)
dev.off()
Update
We can get nice titles and labels with nobs and missings using lapply and a misfun for convenience.
misfun <- \(z) paste(
paste(c('n', 'm'), table(factor(as.double(is.na(z)), levels=0:1)), sep=':'),
collapse=' ')
png('foo2.png', 2560, 1440)
par(mfrow=c(12, 11))
lapply(names(df), \(x) hist(df[[x]], main=x, xlab=misfun(df[x])))
dev.off()
Data:
df <- read.table("https://leicester.figshare.com/ndownloader/files/23581310", sep = ",", header = TRUE, stringsAsFactors = FALSE)
If all you are only looking for are the number of missing values in each column but don't really need the histograms, you can do:
colSums(sapply(df, is.na))
If you need this as an image, then it will be much clearer to draw it with text rather than hist:
df2 <- data.frame(col = paste(names(df), colSums(sapply(df, is.na)),
sep = '\n \nMissing = '),
x = (seq(ncol(df)) - 1) %% 12,
y = 12 - (seq(ncol(df)) - 1) %/% 12)
plot(df2$x, df2$y, type = 'n', xaxt = 'n', yaxt = 'n', xlab = '', ylab = '',
bty = 'n')
text(df2$x, df2$y, label = df2$col, cex = 0.5)
Related
I am trying to make plots using a function in which arguments are values of dataframes.
seniorPlot <- function(validityDate, seniorTotal, color){
par(new = T)
plot(validityDate,seniorTotal,
type = "l",
lwd = 2.5,
xlim = c(date_debut$validityDate,date_fin$validityDate),
ylim = c(1,nmax$seniorTotal),
col = color,
xlab = "",
ylab = "",
xaxt = "n",
yaxt = "n",
bty = "n",
)
}
For the purpose, the threee arguments of the function are results several dataframes 'seniorList' and the seniors df named with the senior initials ('AM', 'FB', 'GM'…)
To describe, you can see the senior dataframes below:
seniorList <- data.frame(seniorValidation=c('AM', 'FB', 'GM'),seniorTotal=c(72, 154, 137))
AM <- data.frame(validationDate=c('2022-01-25', '2022-01-26'), color=c('brown','brown')
FB <- data.frame(validationDate=c('2022-01-20', '2022-01-30'), color=c('green','green')
GM <- data.frame(validationDate=c('2022-01-24', '2022-01-28'), color=c('blue','blue')
Obviously, there is more than 3 lines in the seniorList, so I want to do a loop, using the value of the first column of seniorList (ie. the senior name) to call the write dataframe.
And, here is the issue : how can I convert the result of noquote(paste(noquote(seniorList[i,1]),'$validityDate', sep = '')) to the result '2022-01-25' (if i = 1)
for (i in 1:nrow(seniorList)) {
seniorPlot(validityDate = noquote(paste(noquote(seniorList[i,1]),'$validityDate', sep = '')),
seniorTotal = noquote(paste(noquote(seniorList[i,1]),'$seniorTotal', sep = '')),
color = noquote(paste(noquote(seniorList[i,1]),'$color', sep = '')))
}
Thank you for your help, I hope my english is easy to understand.
noquote(paste(noquote(seniorList[i,1]),'$validityDate', sep = '')) give AM$validityDate and not its result
It's unclear what exactly the plot should look like but this shows how use "tidy" data easily with ggplot2.
DF <- rbind(cbind(AM, data.frame(seniorTotal = 72, seniorValidation = "AM")),
cbind(FB, data.frame(seniorTotal = 154, seniorValidation = "GB")),
cbind(GM, data.frame(seniorTotal = 137, seniorValidation = "GM")))
DF$validationDate <- as.Date(DF$validationDate)
#this is how your data should look like:
print(DF)
library(ggplot2)
ggplot(data = DF, aes(x = validationDate, y = seniorTotal, color = seniorValidation)) +
geom_line()
I am using plot_roc_components function from rmda package. The definition of it has plot_generic() function. But, I am not able to find definition of this function. Why is it so?
The reason for it to see if there is an option for legend.size(). plot_roc_components gives me figure, however, I want to change the legend size. There is an option for legend.position, but not for its font size.
Could you please explain?
Thanks!
https://github.com/mdbrown/rmda/blob/57553a4cf5b6972176a0603b412260e367147619/R/plot_functions_sub.R
You were looking in one file but it was defined in another file.
plot_generic<- function(xx, predictors, value, plotNew,
standardize, confidence.intervals,
cost.benefit.axis = TRUE, cost.benefits, n.cost.benefits,
cost.benefit.xlab, xlab, ylab,
col, lty, lwd,
xlim, ylim, legend.position,
lty.fpr = 2, lty.tpr = 1,
tpr.fpr.legend = FALSE,
impact.legend = FALSE,
impact.legend.2 = FALSE,
population.size = 1000,
policy = policy, ...){
## xx is output from get_DecisionCurve,
## others are directly from the function call
#save old par parameters and reset them once the function exits.
old.par<- par("mar"); on.exit(par(mar = old.par))
xx.wide <- reshape::cast(xx, thresholds~model, value = value, add.missing = TRUE, fill = NA)
xx.wide$thresholds <- as.numeric(as.character(xx.wide$thresholds))
if(is.numeric(confidence.intervals)){
val_lower <- paste(value, "lower", sep = "_")
val_upper <- paste(value, "upper", sep = "_")
xx.lower <- cast(xx, thresholds~model, value = val_lower, add.missing = TRUE, fill = NA)
xx.upper <- cast(xx, thresholds~model, value = val_upper, add.missing = TRUE, fill = NA)
xx.lower$thresholds <- as.numeric(as.character(xx.lower$thresholds))
xx.upper$thresholds <- as.numeric(as.character(xx.upper$thresholds))
}
# adjust margins to add extra x-axis
if(cost.benefit.axis) par(mar = c(7.5, 4, 3, 2) + 0.1)
#set default ylim if not provided
#initial call to plot and add gridlines
I have made a loop for making multiply plots, however i have no way of saving them, my code looks like this:
#----------------------------------------------------------------------------------------#
# RING data: Mikkel
#----------------------------------------------------------------------------------------#
# Set working directory
setwd()
#### Read data & Converting factors ####
dat <- read.table("Complete RING.txt", header =TRUE)
str(dat)
dat$Vial <- as.factor(dat$Vial)
dat$Line <- as.factor(dat$Line)
dat$Fly <- as.factor(dat$Fly)
dat$Temp <- as.factor(dat$Temp)
str(dat)
datSUM <- summaryBy(X0.5_sec+X1_sec+X1.5_sec+X2_sec+X2.5_sec+X3_sec~Vial_nr+Concentration+Sex+Line+Vial+Temp,data=dat, FUN=sum)
fl<-levels(datSUM$Line)
colors = c("#e41a1c", "#377eb8", "#4daf4a", "#984ea3")
meltet <- melt(datSUM, id=c("Concentration","Sex","Line","Vial", "Temp", "Vial_nr"))
levels(meltet$variable) <- c('0,5 sec', '1 sec', '1,5 sec', '2 sec', '2,5 sec', '3 sec')
meltet20 <- subset(meltet, Line=="20")
meltet20$variable <- as.factor(meltet20$variable)
AllConcentrations <- levels(meltet20$Concentration)
for (i in AllConcentrations) {
meltet.i <- meltet20[meltet20$Concentration ==i,]
quartz()
print(dotplot(value~variable|Temp, group=Sex, data = meltet.i ,xlab="Time", ylab="Total height pr vial [mm above buttom]", main=paste('Line 20 concentration ', meltet.i$Concentration[1]),
key = list(points = list(col = colors[1:2], pch = c(1, 2)),
text = list(c("Female", "Male")),
space = "top"), col = colors, pch =c(1, 2))) }
I have tried with the quartz.save function, but that just overwrites the files. Im using a mac if that makes any difference.
When I want to save multiple plots in a loop I tend to do something like...
for(i in AllConcentrations){
meltet.i <- meltet20[meltet20$Concentration ==i,]
pdf(paste("my_filename", i, ".pdf", sep = ""))
dotplot(value~variable|Temp, group=Sex, data = meltet.i ,xlab="Time", ylab="Total height pr vial [mm above buttom]", main=paste('Line 20 concentration ', meltet.i$Concentration[1]),
key = list(points = list(col = colors[1:2], pch = c(1, 2)),
text = list(c("Female", "Male")),
space = "top"), col = colors, pch =c(1, 2))
dev.off()
}
This will create a pdf file for every level in AllConcentrations and save it in your working directory. It will paste together my_filename, the number of the iteration i, and then .pdf together to make each file unique. Of course, you will want to adjust height and width in the pdf function.
I want to do some box plots, but I have data with a different number of rows for each column.
My data looks like:
OT1 OT2 OT3 OT4 OT5 OT6
22,6130653 16,6666667 20,259481 9,7431602 0,2777778 16,0678643
21,1122919 32,2946176 11,396648 10,9458023 4,7128509 10,8938547
23,5119048 19,5360195 23,9327541 39,5634921 0,6715507 12,2591613
16,9880885 39,5365943 7,7568134 22,7453205 3,6410445 11,7610063
32,768937 25,2897351 9,6288027 4,1629535 3,7251656
40,7819933 15,6320021 5,9171598
23,7961828 14,3728125 2,1887585
I'd like to have a box plot for each column (OT1, OT2…), but with the first three and the last three grouped together.
I tried:
>mydata <- read.csv('L5.txt', header = T, sep = "\t")
>mydata_t <- t(mydata)
>boxplot(mydata_t, ylab = "OTU abundance (%)",las=2, at=c(1,2,3 5,6,7))
But it didn't work…
How can I do?
Thanks!
Combining both answers and extenting Henrik's answer, you can also group the OT's together in boxplot() as well:
dat <- read.table(text='OT1 OT2 OT3 OT4 OT5 OT6
22,6130653 16,6666667 20,259481 9,7431602 0,2777778 16,0678643
21,1122919 32,2946176 11,396648 10,9458023 4,7128509 10,8938547
23,5119048 19,5360195 23,9327541 39,5634921 0,6715507 12,2591613
16,9880885 39,5365943 7,7568134 22,7453205 3,6410445 11,7610063
32,768937 25,2897351 9,6288027 4,1629535 3,7251656
40,7819933 15,6320021 5,9171598
23,7961828 14,3728125 2,1887585',header=TRUE,fill=TRUE)
dat <- sapply(dat,function(x)as.numeric(gsub(',','.',x)))
dat.m <- melt(dat)
dat.m <- transform(dat.m,group=ifelse(grepl('1|2|3','4|5|6'),
'group1','group2'))
as.factor(dat.m$X2)
boxplot(dat.m$value~dat.m$X2,data=dat.m,
axes = FALSE,
at = 1:6 + c(0.2, 0, -0.2),
col = rainbow(6))
axis(side = 1, at = c(2, 5), labels = c("Group_1", "Group_2"))
axis(side = 2, at = seq(0, 40, by = 10))
legend("topright", legend = c("OT1", "OT2", "OT3", "OT4", "OT5", "OT6"), fill = rainbow(6))
abline(v = 3.5, col = "grey")
box()
Not easy to group boxplots using R basic plots, better to use ggplot2 here. Whatever the difficulty here is how to reformat your data and reshape them in the long format.
dat <- read.table(text='OT1 OT2 OT3 OT4 OT5 OT6
22,6130653 16,6666667 20,259481 9,7431602 0,2777778 16,0678643
21,1122919 32,2946176 11,396648 10,9458023 4,7128509 10,8938547
23,5119048 19,5360195 23,9327541 39,5634921 0,6715507 12,2591613
16,9880885 39,5365943 7,7568134 22,7453205 3,6410445 11,7610063
32,768937 25,2897351 9,6288027 4,1629535 3,7251656
40,7819933 15,6320021 5,9171598
23,7961828 14,3728125 2,1887585',header=TRUE,fill=TRUE)
dat = sapply(dat,function(x)as.numeric(gsub(',','.',x)))
dat.m <- melt(dat)
dat.m <- transform(dat.m,group=ifelse(grepl('1|2|3',Var2),
'group1','group2'))
ggplot(dat.m)+
geom_boxplot(aes(x=group,y=value,fill=Var2))
Or with boxplot, using #agstudy's 'dat':
df <- melt(dat)
boxplot(value ~ Var2, data = df, at = 1:6 + c(0.2, 0, -0.2))
As the above screenshot showed, I used the function heatmap.2() here.
how can I change 'Value' in the color coded bar to any other name?
One can just use the data from gplots package:
library(gplots)
data(mtcars)
x <- as.matrix(mtcars)
rc <- rainbow(nrow(x), start=0, end=.3)
cc <- rainbow(ncol(x), start=0, end=.3)
heatmap.2(x, key=TRUE)
Many thanks :-)
The function heatmap.2 may have changed since #BondedDust answered, but its now possible to easily change the heatmap.2 key labels via:
key.xlab="New value"
First, your code from above (using the standard colors):
library(gplots)
data(mtcars)
x <- as.matrix(mtcars)
heatmap.2(x,key=TRUE)
Now replace the x and y labels:
library(gplots)
data(mtcars)
x <- as.matrix(mtcars)
heatmap.2(x, key=TRUE , key.xlab="New value", key.ylab="New count")
It's hard-coded. You will need to change it in the code. It appears about midway down the section that draws the key and the line is:
else mtext(side = 1, "Value", line = 2)
This is the section of the heatmap.2 code that creates the key (at least up to the point where the word "Value" appears) :
if (key) {
par(mar = c(5, 4, 2, 1), cex = 0.75)
tmpbreaks <- breaks
if (symkey) {
max.raw <- max(abs(c(x, breaks)), na.rm = TRUE)
min.raw <- -max.raw
tmpbreaks[1] <- -max(abs(x), na.rm = TRUE)
tmpbreaks[length(tmpbreaks)] <- max(abs(x), na.rm = TRUE)
}
else {
min.raw <- min(x, na.rm = TRUE)
max.raw <- max(x, na.rm = TRUE)
}
z <- seq(min.raw, max.raw, length = length(col))
image(z = matrix(z, ncol = 1), col = col, breaks = tmpbreaks,
xaxt = "n", yaxt = "n")
par(usr = c(0, 1, 0, 1))
lv <- pretty(breaks)
xv <- scale01(as.numeric(lv), min.raw, max.raw)
axis(1, at = xv, labels = lv)
if (scale == "row")
mtext(side = 1, "Row Z-Score", line = 2)
else if (scale == "column")
mtext(side = 1, "Column Z-Score", line = 2)
else mtext(side = 1, "Value", line = 2)
.... lots more code below
You should type heatmap.2 , then copy the source code to an editor and then use the search function to find "Value". Change "Value" to something else (in quotes) and then type heatmap.2 <- and paste in the code and hit return. (Unless you save this it will only persist as long as the session continues.)
Just come across same task recently. Now there is an option "key.title" to set the title for scale inlet:
library(gplots)
data(mtcars)
x <- as.matrix(mtcars)
heatmap.2(x, key.title = "New Title", key.xlab="New value", key.ylab="New count")
Unfortunately, it do not propagate properly if there is no histogram in inlet:
library(gplots)
data(mtcars)
x <- as.matrix(mtcars)
heatmap.2(x, key.title = "New Title", key.xlab="New value", key.ylab="New count")
Well, key.xlab working as expected and can be used instead.
I've checked the source code on github and it is already fixed there.