Group R table entries by month - r

Question

I have as CSV value with two columns, a unix timestamp and a version string. What I finally want to achieve is to group the data by months and plot the data, so that the single months are entries on the x axis, and a line is plotted for each unique version string, where the y axis values should represent the number of hits on that month.
Here is a small example CSV:
timestamp,version
1434974143,1.0.0
1435734004,1.1.0
1435734304,1.0.0
1435735386,1.2.0
I'm new to R, so I encountered several problems. First I successfully read the csv with
mydata <- read.csv("data.csv")
and figured out an ungly function that convers a single timestamp into an R date:
as_time <- function(val){
return(head(as.POSIXct(as.numeric(as.character(val)),origin="1970-01-01",tz="GMT")))
}
But non of the several apply functions seemed to work on the table column.
So how do I create a data structure, that groups the version hits by month, and can be plotted later?

Answer 1

It's easier than you think!
You are essentially looking for the hist function.
#Let's make some mock data
# Set the random seed for reproducibility
set.seed(12345)
my.data <- data.frame(timestamp = runif(1000, 1420000000, 1460000000),
version = sample(1:5, 1000, replace = T))
my.data$timestamp <- as.POSIXct(my.data$timestamp, origin = "1970-01-01")
# Histogram of the data, irrespective of version
hist(my.data$timestamp, "month")
# If you want to see the version then split the data first...
my.data.split <- split(my.data, my.data$version)
# Then apply hist
counts <- sapply(my.data.split, function (x)
{
h <- hist(x$timestamp, br = "month", plot = FALSE)
h$counts
})
# Transform into a matrix and plot
counts <- do.call("rbind", counts)
barplot(counts, beside = T)

Answer 2

You can use the as.yearmon function from the zoo package to get year/month formats:
library(zoo)
dat$yearmon <- as.yearmon(as.POSIXct(dat$timestamp, origin = "1970-01-01", tz = "GMT"))
Then it depends what you want to do with your data. For example, number of version hits per month (thanks to #Frank for fixing):
dat %>% group_by(yearmon, version) %>%
summarise(hits = n())