Split time series data into time intervals (say an hour) and then plot the count

Question

I just have a data file with one column of time series:

'2012-02-01 17:42:44'
'2012-02-01 17:42:44'
'2012-02-01 17:42:44'

... I want to split the data up such that I have a count at the top of hour. Say:

'2012-02-01 17:00:00'  20   
'2012-02-01 18:00:00'  30  

The '20' and '30' represent the number of time series entries for that out period. And I want to be able to graph the time vs that 'count'. How can I do this with R?

Here is my current line graph plot.

library(ggplot2)

req <- read.table("times1.dat")
summary(req)

da <- req$V2
db <- req$V1

time <- as.POSIXct(db)

png('time_data_errs.png', width=800, height=600)
gg <- qplot(time, da) + geom_line()

print(gg)
dev.off()

Answer 1

It sounds like you want to use cut to figure out how many values occur within an hour.

It's generally helpful if you can provide some sample data. Here's some:

set.seed(1) # So you can get the same numbers as I do
MyDates <- ISOdatetime(2012, 1, 1, 0, 0, 0, tz = "GMT") + sample(1:27000, 500)
head(MyDates)
# [1] "2012-01-01 01:59:29 GMT" "2012-01-01 02:47:27 GMT" "2012-01-01 04:17:46 GMT"
# [4] "2012-01-01 06:48:39 GMT" "2012-01-01 01:30:45 GMT" "2012-01-01 06:44:13 GMT"

You can use table and cut (with the argument breaks="hour" (see ?cut.Date for more info)) to find the frequencies per hour.

MyDatesTable <- table(cut(MyDates, breaks="hour"))
MyDatesTable
# 
# 2012-01-01 00:00:00 2012-01-01 01:00:00 2012-01-01 02:00:00 2012-01-01 03:00:00 
#                  59                  73                  74                  83 
# 2012-01-01 04:00:00 2012-01-01 05:00:00 2012-01-01 06:00:00 2012-01-01 07:00:00 
#                  52                  62                  64                  33 
# Or a data.frame if you prefer
data.frame(MyDatesTable)
#                  Var1 Freq
# 1 2012-01-01 00:00:00   59
# 2 2012-01-01 01:00:00   73
# 3 2012-01-01 02:00:00   74
# 4 2012-01-01 03:00:00   83
# 5 2012-01-01 04:00:00   52
# 6 2012-01-01 05:00:00   62
# 7 2012-01-01 06:00:00   64
# 8 2012-01-01 07:00:00   33

Finally, here's a line plot of the MyDatesTable object:

plot(MyDatesTable, type="l", xlab="Time", ylab="Freq")

---

cut can handle a range of time intervals. For example, if you wanted to tabulate for every 30 minutes, you can easily adapt the breaks argument to handle that:

data.frame(table(cut(MyDates, breaks = "30 mins")))
#                   Var1 Freq
# 1  2012-01-01 00:00:00   22
# 2  2012-01-01 00:30:00   37
# 3  2012-01-01 01:00:00   38
# 4  2012-01-01 01:30:00   35
# 5  2012-01-01 02:00:00   32
# 6  2012-01-01 02:30:00   42
# 7  2012-01-01 03:00:00   39
# 8  2012-01-01 03:30:00   44
# 9  2012-01-01 04:00:00   25
# 10 2012-01-01 04:30:00   27
# 11 2012-01-01 05:00:00   33
# 12 2012-01-01 05:30:00   29
# 13 2012-01-01 06:00:00   29
# 14 2012-01-01 06:30:00   35
# 15 2012-01-01 07:00:00   33

---

Update

Since you were trying to plot with ggplot2, here's one approach (not sure if it is the best since I usually use base R's graphics when I need to).

Create a data.frame of the table (as demonstrated above) and add a dummy "group" variable and plot that as follows:

MyDatesDF <- data.frame(MyDatesTable, grp = 1)
ggplot(MyDatesDF, aes(Var1, Freq)) + geom_line(aes(group = grp))