R sequence of dates with lubridate
ymd is a wrapper to parse date strings and returns a POSIXct object.
You simply need to use standard terminology described in ?seq.POSIXt (not lubridate) to define weeks
seq(ymd('2012-04-07'),ymd('2013-03-22'), by = '1 week')
seq(ymd('2012-04-07'),ymd('2013-03-22'), by = 'weeks')
will works
as will
seq(ymd('2012-04-07'),ymd('2013-03-22'), by = '2 week')
You could coerce the lubridate Period class object to a difftime, but that seems rather unnecessary
seq(ymd('2012-04-07'),ymd('2013-03-22'), by = as.difftime(weeks(1)))
Generate a sequence of time using R and lubridate
you could try using seq.Date():
seq.Date(from=as.Date("2000-01-01"), to=as.Date("2010-01-01"), by="month")
or:
seq(as.Date("2000/1/1"), by = "month", length.out = 12)
Create sequence of date on every last day of month
If you want last day of month, instead of start from 2018-01-31, try
seq(as.Date("2018-02-01",format="%Y-%m-%d"),by="month",length.out=6) -1
[1] "2018-01-31" "2018-02-28" "2018-03-31" "2018-04-30" "2018-05-31" "2018-06-30"
Generate sequence of dates for given frequency as per days of occurence
Working on larger sample, as discussed earlier in comments. Strategy followed -
- As your
daycolumn always start fromMonwhich is not equal tostart_dateso the column matchingweekdayis required. - So Created
dayfield to orderedfactortype so that it can be manipulatedit into integers. - Arranged the dataframe in such a way that your every group starts from that day only. Used modulo division
%%for this - After arranging the task was rather easier. I created seven dates for each weekday end, for each group and each start_date.
- Filtered out rows with
Y/Nas 0 anywhere. - Now you require only top row so used
slice_head()
df <- data.frame(
stringsAsFactors = FALSE,
Group = c("foo","foo","foo",
"foo","foo","foo","foo","foo","foo","foo",
"foo","foo","foo","foo","foo","foo","foo",
"foo","foo","foo","foo","bar","bar","bar",
"bar","bar","bar","bar","bar","bar","bar","bar",
"bar","bar","bar"),
start_date = c("02-06-2021",
"02-06-2021","02-06-2021","02-06-2021","02-06-2021",
"02-06-2021","02-06-2021","04-06-2021",
"04-06-2021","04-06-2021","04-06-2021","04-06-2021",
"04-06-2021","04-06-2021","06-06-2021","06-06-2021",
"06-06-2021","06-06-2021","06-06-2021",
"06-06-2021","06-06-2021","02-06-2021","02-06-2021",
"02-06-2021","02-06-2021","02-06-2021","02-06-2021",
"02-06-2021","05-06-2021","05-06-2021",
"05-06-2021","05-06-2021","05-06-2021","05-06-2021",
"05-06-2021"),
Day = c("Mon","Tue","Wed",
"Thu","Fri","Sat","Sun","Mon","Tue","Wed",
"Thu","Fri","Sat","Sun","Mon","Tue","Wed",
"Thu","Fri","Sat","Sun","Mon","Tue","Wed",
"Thu","Fri","Sat","Sun","Mon","Tue","Wed","Thu",
"Fri","Sat","Sun"),
y_n = c(0L,1L,0L,1L,1L,
1L,0L,0L,1L,0L,1L,1L,1L,0L,0L,1L,0L,1L,
1L,1L,0L,1L,0L,0L,1L,1L,0L,0L,1L,0L,
0L,1L,1L,0L,0L)
)
library(lubridate)
library(tidyverse)
df %>% group_by(Group, start_date) %>%
mutate(Day = factor(Day, levels = Day, ordered = T)) %>%
arrange(Group, (as.numeric(Day) + 7 - wday(dmy(start_date), week_start = 1)) %% 7, .by_group = T) %>%
mutate(next_available_date = dmy(start_date) + 0:6) %>%
filter(y_n !=0) %>%
slice_head()
#> # A tibble: 5 x 5
#> # Groups: Group, start_date [5]
#> Group start_date Day y_n next_available_date
#> <chr> <chr> <ord> <int> <date>
#> 1 bar 02-06-2021 Thu 1 2021-06-03
#> 2 bar 05-06-2021 Mon 1 2021-06-07
#> 3 foo 02-06-2021 Thu 1 2021-06-03
#> 4 foo 04-06-2021 Fri 1 2021-06-04
#> 5 foo 06-06-2021 Tue 1 2021-06-08
On the data provided
df <- data.frame(
stringsAsFactors = FALSE,
Group = c("foo","foo","foo",
"foo","foo","foo","foo","bar","bar","bar",
"bar","bar","bar","bar"),
start_date = c("02-06-2021",
"02-06-2021","02-06-2021","02-06-2021","02-06-2021",
"02-06-2021","02-06-2021","02-06-2021",
"02-06-2021","02-06-2021","02-06-2021","02-06-2021",
"02-06-2021","02-06-2021"),
Day = c("Mon","Tue","Wed",
"Thu","Fri","Sat","Sun","Mon","Tue","Wed",
"Thu","Fri","Sat","Sun"),
y_n = c(0L,1L,0L,1L,1L,
1L,0L,1L,0L,0L,1L,1L,0L,0L)
)
library(lubridate)
library(tidyverse)
df %>% group_by(Group, start_date) %>%
mutate(Day = factor(Day, levels = Day, ordered = T)) %>%
arrange(Group, (as.numeric(Day) + 7 - wday(dmy(start_date), week_start = 1)) %% 7, .by_group = T) %>%
mutate(next_available_date = dmy(start_date) + 0:6) %>%
filter(y_n !=0) %>%
slice_head()
#> # A tibble: 2 x 5
#> # Groups: Group, start_date [2]
#> Group start_date Day y_n next_available_date
#> <chr> <chr> <ord> <int> <date>
#> 1 bar 02-06-2021 Thu 1 2021-06-03
#> 2 foo 02-06-2021 Thu 1 2021-06-03
Created on 2021-06-02 by the reprex package (v2.0.0)
Sequence of dates by each next 15th or last day of month
start <- as.Date("2014-05-03")
end <- as.Date("2014-07-01")
library(lubridate)
floor_date(seq(start, end, by = 'month'), unit = "month") + 14
ceiling_date(seq(start, end, by = 'month'), unit = "month")-1
Sequence by the month and use floor_date from the lubridate package to start at the beginning of the month.
Using lubridate to get dates/times from continuous increments
I am not fully sure I understand your question. But from your example it appears you want to create timesteps. When I understand it correctly, a "one unit" is a adding 24 hours, while the half day is adding 12 hours. Your data frame example suggest you want to have this in a dataframe/tibble.
With {lubridate} you can "coerce" datetimestamps. There are some handy time formatting functions. From a character you can go to a timestamp.
For example
# create dataframe/tibble of ODE and Calendar times
mydata <- tribble(
~ODE_time, ~Calendar_Time
,0.0 , "01-01-2021 00:00"
,0.5 , "01-01-2021 12:00"
,1.0 , "01-02-2021 00:00"
,1.5 , "01-02-2021 12:00"
)
mydata <- mydata %>%
mutate(time = lubridate::mdy_hm(Calendar_Time))
In your case, I use the mdy_hm() function to make a timestamp (dttm) object.
I assign it to the time variable/column so you can check the presentation in R/RStudio.
What I get from your question is that you want to create a sequence of timestamps.
Here you can use the seq() function and work with the time offset, in your case 12 hours (or half a day). I limit the length out to 10 ... you can obviously define longer sequences or determine your end day (i.e. to parameter of seq())
date_time_seq <- seq( from = lubridate::mdy_hm("01-01-2021 00:00")
,length.out = 10,
,by = "12 hours")
This gives you a sequence of timestamps
date_time_seq
[1] "2021-01-01 00:00:00 UTC" "2021-01-01 12:00:00 UTC" "2021-01-02 00:00:00 UTC"
[4] "2021-01-02 12:00:00 UTC" "2021-01-03 00:00:00 UTC" "2021-01-03 12:00:00 UTC"
[7] "2021-01-04 00:00:00 UTC" "2021-01-04 12:00:00 UTC" "2021-01-05 00:00:00 UTC"
[10] "2021-01-05 12:00:00 UTC"
The syntax allows you to add various "steps" and you can use increments of different time units, e.g. mins, hours, days, weeks, etc.
This timestep vector you can operate in your dataframe/tibble and perform your other operations.
Good luck!
Create a sequence of dates and store in a data frame with a column name
There are lot of ways to do that, since you used data.frame :
library(lubridate)
library(magrittr)
seq.Date(from = as.Date(today()- days(7)),
to = as.Date(today()),
by = "day") %>%
data.frame(DATE = .)
# DATE
#1 2021-04-23
#2 2021-04-24
#3 2021-04-25
#4 2021-04-26
#5 2021-04-27
#6 2021-04-28
#7 2021-04-29
#8 2021-04-30
Sequence of time with lubridate for special months
You can extract the month and then filter:
library(lubridate)
day_list <- seq(ymd('1995-05-01'),ymd('2005-09-30'),by='day')
day_list <- day_list[which(month(day_list) %in% c(5:9))]
Generate a sequence of the last day of the month over two years
Yes, you found the correct trick: going back a day from the first of the next month.
Here is as a one-liner in base R:
R> seq(as.Date("2010-02-01"), length=24, by="1 month") - 1
[1] "2010-01-31" "2010-02-28" "2010-03-31" "2010-04-30" "2010-05-31"
[6] "2010-06-30" "2010-07-31" "2010-08-31" "2010-09-30" "2010-10-31"
[11] "2010-11-30" "2010-12-31" "2011-01-31" "2011-02-28" "2011-03-31"
[16] "2011-04-30" "2011-05-31" "2011-06-30" "2011-07-31" "2011-08-31"
[21] "2011-09-30" "2011-10-31" "2011-11-30" "2011-12-31"
R>
So no need for lubridate which (while being a fine package) isn't needed for simple task like this. Plus, its overloading of existing base functions still strikes me as somewhat dangerous...
How to generate a sequence of dates and times with a specific start date/time in R
No need for lubridate, just,R code:
x <- data.frame(date = c(as.POSIXct("2018-01-01 00:00:00"), rep(NA,10)))
startDate <- x[["date"]][1]
x[["date2"]] <- startDate + (seq_len(nrow(x)) - 1)
x
# date date2
# 1 2018-01-01 2018-01-01 00:00:00
# 2 <NA> 2018-01-01 00:00:01
# 3 <NA> 2018-01-01 00:00:02
# 4 <NA> 2018-01-01 00:00:03
# 5 <NA> 2018-01-01 00:00:04
# 6 <NA> 2018-01-01 00:00:05
# 7 <NA> 2018-01-01 00:00:06
# 8 <NA> 2018-01-01 00:00:07
# 9 <NA> 2018-01-01 00:00:08
# 10 <NA> 2018-01-01 00:00:09
# 11 <NA> 2018-01-01 00:00:10
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