Question

I have a CSV file that looks like this, where “time” is a UNIX timestamp:

time,count
1300162432,5
1299849832,0
1300006132,1
1300245532,4
1299932932,1
1300089232,1
1299776632,9
1299703432,14
... and so on

I am reading it into R and converting the time column into POSIXct like so:

data <- read.csv(file="data.csv",head=TRUE,sep=",")
data[,1] <- as.POSIXct(data[,1], origin="1970-01-01")

Great so far, but now I would like to build a histogram with each bin corresponding to the average hourly count. I’m stuck on selecting by hour and then counting. I’ve looked through ?POSIXt and ?cut.POSIXt, but if the answer is in there, I am not seeing it.

Any help would be appreciated.

Answer 1

Here is one way:

R> lines <- "time,count
1300162432,5
1299849832,0
1300006132,1
1300245532,4
1299932932,1
1300089232,1
1299776632,9
1299703432,14"
R> con <- textConnection(lines); df <- read.csv(con); close(con)
R> df$time <- as.POSIXct(df$time, origin="1970-01-01")
R> df$hour <- as.POSIXlt(df$time)$hour
R> df
                 time count hour
1 2011-03-15 05:13:52     5    5
2 2011-03-11 13:23:52     0   13
3 2011-03-13 09:48:52     1    9
4 2011-03-16 04:18:52     4    4
5 2011-03-12 12:28:52     1   12
6 2011-03-14 08:53:52     1    8
7 2011-03-10 17:03:52     9   17
8 2011-03-09 20:43:52    14   20
R> tapply(df$count, df$hour, FUN=mean)
 4  5  8  9 12 13 17 20 
 4  5  1  1  1  0  9 14 
R> 

Your data doesn’t actually yet have multiple entries per hour-of-the-day but this would average over the hours, properly parsed from the POSIX time stamps. You can adjust with TZ info as needed.