Weekly data plot in R - r

Question

I have a big data frame (from 2007 to 2015), with data points at about every 2 minutes. I want to plot the graph of every week (from 2007 to 2015), with each week being automatically exported as a PNG file to my computer's folder. Previously, I was able to successfully produce working codes for annually, monthly, and daily plot. E.g.for yearly data:
for(j in 2007:2015){
mypath <- file.path("~", "Documents","Yearly", paste("WAO_AIR_Data_", j, ".png", sep = "" ))
png(filename = mypath, width = 963, height = 690)
timePlot(selectByDate(new_subdata, year = j),
pollutant = c("CO2", "O2", "APO"),
date.pad = TRUE,
pch = c(19,19,19),
cex = 0.2,
xlab = paste("Month of year in", j),
ylab = "CO2, O2, and APO concentrations",
name.pol = c("CO2 (ppm)", "O2 (per meg)", "APO (per meg)"),
)
dev.off()
}
The data frame looks like this
tail(new_subdata)
date CO2 O2 APO
1052042 2015-12-31 23:48:45 409.636 -666.39 -353.27
1052043 2015-12-31 23:50:46 409.652 -669.62 -356.41
1052044 2015-12-31 23:52:44 409.679 -669.44 -356.09
1052045 2015-12-31 23:54:46 409.703 -667.07 -353.59
1052046 2015-12-31 23:56:44 409.719 -671.02 -357.46
1052047 2015-12-31 23:58:46 409.734 NA NA
But I dont know how to produce the code for weekly plotting. Can anyone help me please? Thank you so much!

Answer 1

Via ?strptime, you can get the week out of a Date or POSIXct with %U
%U
Week of the year as decimal number (00–53) using Sunday as the first day 1 of the week (and typically with the first Sunday of the year as day 1 of week 1). The US convention.
x <- Sys.time()
class(x); format(x, '%U')
# [1] "POSIXct" "POSIXt"
# [1] "26"
x <- Sys.Date()
class(x); format(x, '%U')
# [1] "Date"
# [1] "26"
Using your example data with minor changes:
new_subdata <- read.table(header = TRUE, text = "date CO2 O2 APO
1052042 '2015-10-31 23:48:45' 409.636 -666.39 -353.27
1052043 '2015-10-31 23:50:46' 409.652 -669.62 -356.41
1052044 '2015-11-30 23:52:44' 409.679 -669.44 -356.09
1052045 '2015-11-30 23:54:46' 409.703 -667.07 -353.59
1052046 '2015-12-31 23:56:44' 409.719 -671.02 -357.46
1052047 '2015-12-31 23:58:46' 409.734 NA NA")
## create a new grouping variable with year/week
new_subdata <- within(new_subdata, {
yr_wk <- format(as.Date(date), '%Y %U')
})
## iterate over the unique values
jj <- unique(new_subdata$yr_wk)
# [1] "2015 43" "2015 48" "2015 52"
## do some plotting
par(mfrow = n2mfrow(length(jj)), las = 1, mar = c(5,6,2,2),
tcl = .2, mgp = c(3,.25,0))
xr <- range(new_subdata$O2, na.rm = TRUE)
yr <- range(new_subdata$CO2, na.rm = TRUE)
for (j in jj) {
mypath <- file.path("~", "Documents","Yearly", sprintf("WAO_AIR_Data_%s.png", j))
# png(filename = mypath, width = 963, height = 690)
plot(CO2 ~ O2, data = subset(new_subdata, yr_wk == j), xlim = xr, ylim = yr)
# dev.off()
}