Plot a histogram of yearly counts - r

Question

I have a csv file that consists of one column. The column presents the date of posting on a website. I want to plot a histogram to see how the number of posts varies over the years. The file contains the years (2012 to 2016) and consists of 11,000 rows.
sample of the file:
2 30/1/12 21:07
3 2/2/12 15:53
4 3/4/12 0:49
5 14/11/12 3:49
6 11/8/13 16:00
7 31/7/14 8:08
8 31/7/14 10:48
9 6/8/14 9:24
10 16/12/14 3:34
The data types is dataframe
class(postsData)
[1] "data.frame"
I tried converting the data to text using strptime function as below:
formatDate <- strptime(as.character(postsData$Date),format="“%d/%m/%y")
then plot the histogram
hist(formatDate,breaks=10,xlab="year")
Any tip or suggestion would be useful. Thank you,

Answer 1

use lubridate::dmy_hm()
strptime() is overly complicated in my opinion compared to { lubridate }.
library(lubridate)
d <- c("30/1/12 21:07",
"2/2/12 15:53",
"3/4/12 0:49",
"14/11/12 3:49",
"11/8/13 16:00",
"31/7/14 8:08",
"31/7/14 10:48",
"6/8/14 9:24",
"16/12/14 3:34")
d2 <- dmy_hm(d)
d2
Returns:
[1] "2012-01-30 21:07:00 UTC"
[2] "2012-02-02 15:53:00 UTC"
[3] "2012-04-03 00:49:00 UTC"
[4] "2012-11-14 03:49:00 UTC"
[5] "2013-08-11 16:00:00 UTC"
[6] "2014-07-31 08:08:00 UTC"
[7] "2014-07-31 10:48:00 UTC"
[8] "2014-08-06 09:24:00 UTC"
[9] "2014-12-16 03:34:00 UTC"
As you can see, lubridate functions return POSIXct objects.
class(d2)
[1] "POSIXct" "POSIXt"
Next, you can use lubridate::year() to get the year of each POSIXct object returned by dmy_hm(), and plot that histogram.
hist(year(d2))

Answer 2

Here's one approach. I think your date conversion is fine but you need to count the number of dates that occur in each year then plot that count as a histogram.
library(tidyverse)
# generate some data
date.seq <- tibble(xdate = seq(from = lubridate::ymd_hms('2000-01-01 00:00:00'), to=lubridate::ymd_hms('2016-12-31 24:59:59'), length.out = 100))
date.seq %>%
mutate(xyear = lubridate::year(xdate)) %>% # add a column of years
group_by(xyear) %>%
summarise(date_count = length(xdate)) %>% # Count the number of dates that occur in each year
ggplot(aes(x = xyear, y = date_count)) +
geom_col(colour = 'black', fill = 'blue') # plot as a column graph

Answer 3

There's no problem with strptime()*, however, the format option is intended to specify how the is formatted.
df1$date <- strptime(df1$date, format="%d/%m/%y %H:%M")
# [1] "2012-01-30 21:07:00 CET" "2012-02-02 15:53:00 CET"
# [3] "2012-04-03 00:49:00 CEST" "2012-11-14 03:49:00 CET"
# [5] "2013-08-11 16:00:00 CEST" "2014-07-31 08:08:00 CEST"
# [7] "2014-07-31 10:48:00 CEST" "2014-08-06 09:24:00 CEST"
# [9] "2014-12-16 03:34:00 CET"
What you probably want then is to use the format() function
formatDate <- format(df1$date, format="%F")
(or in this case simpler with formatDate <- as.Date(df1$date))
and then
hist(formatDate, breaks=10, xlab="year")
* credits to #MikkoMarttila
Data
df1 <- structure(list(id = 2:10, date = c("30/1/12 21:07", "2/2/12 15:53",
"3/4/12 0:49", "14/11/12 3:49", "11/8/13 16:00", "31/7/14 8:08",
"31/7/14 10:48", "6/8/14 9:24", "16/12/14 3:34")), class = "data.frame", row.names = c(NA,
-9L))