So I've created a loop that makes 10 individual plots:
for (k in 1:nrow(sites)) {
temp_title <- paste("site",k, "county", sites[k,2],"site",sites[k,3])
l <- which(hourly_nj_table$County.Code==sites[k,2]&hourly_nj_table$Site.Num==sites[k,3])#grab data for each site individually
temp_filename <- paste("/filepath",temp_title,".pdf")
PM_site <- hourly_nj_table[l,]
PM_site$realTime <- as.numeric(PM_site$Time.Local)
PM_mean_site <- aggregate(PM_site, by=list(PM_site$Time.Local),FUN="mean",na.rm=TRUE)
plot(PM_mean_site$realTime,PM_mean_site$Sample.Measurement, type="l",lwd=10,main=paste(temp_title),xlab="LocalTime",ylab="Ozone (ppm)")#,ylim=c(0,0.05))
}
But I would like to see how they compare on the same axis. Normally (if i'm just hardcoding it) I would add a new parameter and then create the next plot, but i'm unsure how to incorporate that into a loop.
The data all comes from one csv file if that helps..
Thanks!
You're really very close. Plot() gets the ball rolling, lines() will allow you to draw inside the plot:
for (k in 1:nrow(sites)) {
temp_title <- paste("site",k, "county", sites[k,2],"site",sites[k,3])
l <- which(hourly_nj_table$County.Code==sites[k,2]&hourly_nj_table$Site.Num==sites[k,3])#grab data for each site individually
temp_filename <- paste("/Users/bob111higgins/Documents/School/College/Rutgers/Atmospheric Research",temp_title,".pdf")
PM_site <- hourly_nj_table[l,]
PM_site$realTime <- as.numeric(PM_site$Time.Local)
PM_mean_site <- aggregate(PM_site, by=list(PM_site$Time.Local),FUN="mean",na.rm=TRUE) #Make it average by time of day so can make time series plots.
ifesle(k ==1 ,
plot(PM_mean_site$realTime,PM_mean_site$Sample.Measurement, type="l",lwd=10,main=paste(temp_title),xlab="LocalTime",ylab="Ozone (ppm)")#,ylim=c(0,0.05)),
lines(PM_mean_site$realTime,PM_mean_site$Sample.Measurement, lwd=10))
}
I'm sure there are better ways to go about this, but this is how I've done it in the past.
Related
Suppose we have these objects:
distM_ref1_matrix <- dist(cbind(distM_ref1$x, distM_ref1$y))
distM_ref2_matrix <- dist(cbind(distM_ref2$x, distM_ref2$y))
distM_ref3_matrix <- dist(cbind(distM_ref3$x, distM_ref3$y))
distM_ref4_matrix <- dist(cbind(distM_ref4$x, distM_ref4$y))
distM_ref5_matrix <- dist(cbind(distM_ref5$x, distM_ref5$y))
distM_ref6_matrix <- dist(cbind(distM_ref6$x, distM_ref6$y))
distM_ref7_matrix <- dist(cbind(distM_ref7$x, distM_ref7$y))
distM_ref8_matrix <- dist(cbind(distM_ref8$x, distM_ref8$y))
distM_ref9_matrix <- dist(cbind(distM_ref9$x, distM_ref9$y))
I have two questions:
How can I save code by creating all these objects automatically with a single line? Consider I do have tons of equivalent objects, not only 9 as in the example.
How can I calculate the mean value of all these objects at the same time?
I think that the answer for the second question would be somehow like this code:
mean(c(distM_ref[1:9]_matrix))
I am trying to create minimum convex polygons for a set of GPS coordinates, each day has 32 coordinates and I want to create a MCP with 1 day,2 days,3 days... and so on worth of data. For instance in the first step I want to include rows 1-32 which I have managed:
mydata <- read.csv("file.csv", stringsAsFactors = FALSE)
mydata <- mydata[1:32, ]
Currently to select data for me to do 2 days at a time I have written:
mydata <- read.csv("file.csv", stringsAsFactors = FALSE)
mydata <- mydata[1:64, ]
Is there a way to automate adding 32 rows at each step (in a loop) rather than me running the code manually each time and changing the amount of data used manually each time?
I am very new to R so I do not know whether it is possible to do this, the way I thought would work was:
n <- 32
for (i in 1:100) {
mydata <- mydata[1:n, ]
## CREATE MCP AND STORE HOME RANGE OUTPUT
n <- n+32
}
However it is not possible to have n representing a row number but is there a way to do this?
Apologies if this is unclear but as I said I am quite new to using R and really would appreciate any help that can be given.
I have a list, which contains 75 matrix with their names, and I want to do a plot for each matrix, and save each plot with the name that the matrix have.
My code do the plots with a loop and it works, I get 75 correct plots, but the problem is that the name of the plot file is like a vector "c(99,86,94....)",too long and I don´t know which one is.
I´m ussing that code, probably isn´t the best. I´m a beginner, and I have been looking for a solution one week, but it was impossible.
for (i in ssamblist) {
svg(paste("Corr",i,".svg", sep=""),width = 45, height = 45)
pairs(~CDWA+CDWM+HI+NGM2+TKW+YIELD10+GDD_EA,
data=i,lower.panel=panel.smooth, upper.panel=panel.cor,
pch=0, main=i)
dev.off()}
How put to a each plot his name?.
I try change "i" for names(i), but the name was the name of the first column,and only creates one plot. I try to do it with lapply but I could't.
PS: the plots are huge, and I have to expand the margins. I´m using Rstudio.
Thank you¡
Using for loop or apply:
# dummy data
ssamblist <- list(a = mtcars[1:10, 1:4], b = mtcars[11:20, 1:4], c = mtcars[21:30, 1:4])
# using for loop
for(i in names(ssamblist)) {
svg(paste0("Corr_", i, ".svg"))
pairs(ssamblist[[i]], main = i)
dev.off()}
# using apply
sapply(names(ssamblist), function(i){
svg(paste0("Corr_", i, ".svg"))
pairs(ssamblist[[i]], main = i)
dev.off()})
I've made a loop to create multiple boxplots. The thing is, I want to save all the boxplots without overwriting each other. Any suggestions?
This is my current code:
boxplot <- list()
for (x in 1:nrow(checkresults)){
boxplots <- boxplot(PIM[,x], MYC [,x], OBX[,x], WDR[,x], EV[,x],
main=colnames(PIM)[x],
xlab="PIM, MYC, OBX, WDR, EV")
}
Do you want to save them in some files, or save them to be able to look at them in different windows ?
If it is the first case, you can use a png, pdf or whatever function call inside your for loop :
R> for (i in 1:5) {
R> png(file=paste("plot",i,".png",sep=""))
R> plot(rnorm(10))
R> dev.off()
R> }
If you want to display them in separate windows, just use dev.new :
R> for (i in 1:5) {
R> dev.new()
R> plot(rnorm(10));
R> }
Just to add to #juba's answer, if you want to save the plots to a multi-page pdf file, then you don't have to use the paste command that #juba suggested. This
pdf("myboxplots.pdf")
for (x in seq_along(boxplots)){
boxplot(PIM[,x], MYC [,x], OBX[,x], WDR[,x],EV[,x],
main = colnames(PIM)[x],
xlab = "PIM, MYC, OBX, WDR, EV")
}
dev.off()
creates a single multi-page pdf document, where each page is a boxplot. If you want to store the boxplots in separate pdf documents, then use the file=paste command.
First, create a list of the right length - it just makes things easier and is good practice to allocate storage before filling objects in via a loop:
boxplots <- vector(mode = "list", length = nrow(checkresults))
Then we can loop over the data you want, assigning to each component of the boxplots list as we go, using the [[x]] notation:
for (x in seq_along(boxplots)){
boxplots[[x]] <- boxplot(PIM[,x], MYC [,x], OBX[,x], WDR[,x],EV[,x],
main = colnames(PIM)[x],
xlab = "PIM, MYC, OBX, WDR, EV")
}
Before, your code was overwriting the previous boxplot info during subsequent iterations.
When programming in Stata I often find myself using the loop index in the programming. For example, I'll loop over a list of the variables nominalprice and realprice:
local list = "nominalprice realprice"
foreach i of local list {
summarize `i'
twoway (scatter `i' time)
graph export "C:\TimePlot-`i'.png"
}
This will plot the time series of nominal and real prices and export one graph called TimePlot-nominalprice.png and another called TimePlot-realprice.png.
In R the method I've come up with to do the same thing would be:
clist <- c("nominalprice", "realprice")
for (i in clist) {
e <- paste("png(\"c:/TimePlot-",i,".png\")", sep="")
eval(parse(text=e))
plot(time, eval(parse(text=i)))
dev.off()
}
This R code looks unintuitive and messy to me and I haven't found a good way to do this sort of thing in R yet. Maybe I'm just not thinking about the problem the right way? Can you suggest a better way to loop using strings?
As other people have intimated, this would be easier if you had a dataframe with columns named nominalprice and realprice. If you do not, you could always use get. You shouldn't need parse at all here.
clist <- c("nominalprice", "realprice")
for (i in clist) {
png(paste("c:/TimePlot-",i,".png"), sep="")
plot(time, get(i))
dev.off()
}
If your main issue is the need to type eval(parse(text=i)) instead of ``i'`, you could create a simpler-to-use functions for evaluating expressions from strings:
e = function(expr) eval(parse(text=expr))
Then the R example could be simplified to:
clist <- c("nominalprice", "realprice")
for (i in clist) {
png(paste("c:/TimePlot-", i, ".png", sep=""))
plot(time, e(i))
dev.off()
}
Using ggplot2 and reshape:
library(ggplot2)
library(reshape)
df <- data.frame(nominalprice=rexp(10), time=1:10)
df <- transform(df, realprice=nominalprice*runif(10,.9,1.1))
dfm <- melt(df, id.var=c("time"))
qplot(time, value, facets=~variable, data=dfm)
I don't see what's especially wrong with your original solution, except that I don't know why you're using the eval() function. That doesn't seem necessary to me.
You can also use an apply function, such as lapply. Here's a working example. I created dummy data as a zoo() time series (this isn't necessary, but since you're working with time series data anyway):
# x <- some time series data
time <- as.Date("2003-02-01") + c(1, 3, 7, 9, 14) - 1
x <- zoo(data.frame(nominalprice=rnorm(5),realprice=rnorm(5)), time)
lapply(c("nominalprice", "realprice"), function(c.name, x) {
png(paste("c:/TimePlot-", c.name, ".png", sep=""))
plot(x[,c.name], main=c.name)
dev.off()
}, x=x)