在R中每天，每月和每年的观察次数计数

Question

I have the a dataframe in the following form (its too big to post here entirerly):

      listing_id    date    city    type    host_id availability
1   703451  25/03/2013  amsterdam   Entire home/apt 3542621 245
2   703451  20/04/2013  amsterdam   Entire home/apt 3542621 245
3   703451  28/05/2013  amsterdam   Entire home/apt 3542621 245
4   703451  15/07/2013  amsterdam   Entire home/apt 3542621 245
5   703451  30/07/2013  amsterdam   Entire home/apt 3542621 245
6   703451  19/08/2013  amsterdam   Entire home/apt 3542621 245

and so on...

I would like three new data frames. One counting the number of observations for a particular year (2013,2012, 2011 and so on) another per month (07/2013, 06/2013 and so on) and another per day (28/05/2013, 29/05/2013 and so on). I just want to count how many occurances there are per unit of time.

How would I do that?

Answer 1

Using data.table , this is pretty straightforward:

library(data.table)
dt <- fread("listing_id    date    city    type    host_id availability
703451  25/03/2013  amsterdam   Entire_home/apt 3542621 245
703451  20/04/2013  amsterdam   Entire_home/apt 3542621 245
703451  28/05/2013  amsterdam   Entire_home/apt 3542621 245
703451  15/07/2013  amsterdam   Entire_home/apt 3542621 245
703451  30/07/2013  amsterdam   Entire_home/apt 3542621 245
703451  19/08/2013  amsterdam   Entire_home/apt 3542621 245")
dt$date <- as.Date(dt$date, "%d/%m/%Y")

dt[, .N, by=year(date)] 
#    year N
# 1: 2013 6

dt[, .N, by=.(year(date), month(date))] 
#    year month N
# 1: 2013     3 1
# 2: 2013     4 1
# 3: 2013     5 1
# 4: 2013     7 2
# 5: 2013     8 1

dt[, .N, by=date] # or: dt[, .N, by=.(year(date), month(date), day(date)] 
#          date N
# 1: 2013-03-25 1
# 2: 2013-04-20 1
# 3: 2013-05-28 1
# 4: 2013-07-15 1
# 5: 2013-07-30 1
# 6: 2013-08-19 1

Answer 2

We can convert the 'date' column to Date class, extract the year using the ?year from library(lubridate) , get the month-year using as.yearmon from library(zoo) . We place the 'dates', 'yr', 'monyr' in a list , loop through it ( lapply ), and create the count of occurance column in the original dataset ('df1') using ave . It is better to place the datasets in the list . However, if you insist, we can overload the global environment with multiple objects using list2env .

library(zoo)
library(lubridate)
dates <- as.Date(df1$date, '%d/%m/%Y')
yr <- year(dates)
monyr <- as.yearmon(dates)
lst <- lapply(list(dates, yr, monyr), function(x) 
       transform(df1, Count=ave(seq_along(x), x, FUN= length)))
names(lst) <- paste0('newdf', seq_along(lst))
list2env(lst, envir=.GlobalEnv)

Answer 3

Get your index into Postxct format, then:

counts <- data.frame(table(as.Date(index(my_data_frame))))

Change as.Date as necessary.