Print all hours:minutes from 00:00 to 23:59 - r

I would like to print all the hours: minutes in a day from 00:00 to 23:59.
This part goes beyond the question, but if you want to help me, this is the whole idea:
Once that is done, I would like to calculate all the "curious" times that can be interpreted as serendipities. Patterns like: 00:00, 22:22, 01:10, 12:34, 11:44, and the like.
Later on, I would like to count all the "serendipities", and divide them to the total number of hours to know the probabilities of find a "serendipity" each time a person look at the time on his smartphone.
To be honest, I am pretty lost. There is already some months without coding. For the first part of the problem, I guess that a loop can make the task.
For the second part, an if conditional can probably make it.
For the first part of the problem I have tried loops like this
for(i in x){
for(k in y){
cat(i,":",k, ",")
}
}
For the second, something like
Assuming the digits of the time are ab:cd
if(a==b & a==c & a==d){
print(ab:cd)
TRUE
}
if(a==b & c==d){
print(ab:cd)
TRUE
}
I would like to get the whole list of numbers first. Then, the list of "serendipities", and finally the count of both to make the percentage.
I find interesting how people find patterns in numbers when they look at the time, and I would like to know how probable is to get one of these patterns out of the 24*60 = 1440
I hope I have explained myself. (I used to be better with coding and maths, but after some months, I have forgotten almost everything).

Here's a way to generate the list of all possible times.
h <- seq(from=0, to=23)
m <- seq(from=0, to=59)
h <- sprintf('%02d', h)
m <- sprintf('%02d', m)
df <- data.frame(expand.grid(h, m))
df$times <- paste0(df$Var1, ':', df$Var2)
df <- df[order(df$times), ]
df$times
Partial output
df$times[1:25]
[1] "00:00" "00:01" "00:02" "00:03" "00:04" "00:05" "00:06" "00:07" "00:08"
[10] "00:09" "00:10" "00:11" "00:12" "00:13" "00:14" "00:15" "00:16" "00:17"
[19] "00:18" "00:19" "00:20" "00:21" "00:22" "00:23" "00:24"
Length of variable
dim(df)
[1] 1440 3

We can create a sequence of 1 minute interval starting from 00:00:00 to 23:59:00 and then use format to get output in desired format.
format(seq(as.POSIXct("00:00:00", format = "%T"),
as.POSIXct("23:59:00", format = "%T"), by = "1 min"), "%H:%M")
#[1] "00:00" "00:01" "00:02" "00:03" "00:04" "00:05" "00:06" "00:07" "00:08" "00:09"
# "00:10" "00:11" "00:12" "00:13" "00:14" "00:15" "00:16" "00:17" "00:18" "00:19" ...

Yet another way of doing it:
> result <- character(1440)
> for (i in 0:1439) result[i+1L] <- sprintf("%02d:%02d",
+ i %/% 60,
+ i %% 60
+ )
> head(result)
[1] "00:00" "00:01" "00:02" "00:03" "00:04" "00:05"
> tail(result)
[1] "23:54" "23:55" "23:56" "23:57" "23:58" "23:59"

Related

How to create a sequence of *%Year%Week* from numeric?

From my inputs, which is numeric format and represent the year and the week number, I need to create a sequence, from one input to the other.
Inputs example :
input.from <- 202144
input.to <- 202208
Desired output would be :
c(202144:202152, 202201:202208)
According to me, it is a little more complex, because of these constraints :
Years with 53 weeks : I tried lubridate::isoweek(), the %W or %v format, ...
Always keep two digits for the week : I tried "%02d", ...
I also tried to convert my input to date, ...
Anyway, many attemps without success to create my function.
Thanks for your help !
In case it would be useful to someone one day, here is finally the function I wrote, which respects ISO 8601 :
library(ISOweek)
foo <- function(pdeb, pfin) {
from <- ISOweek::ISOweek2date(paste0(substr(pdeb, 1, 4), "-W", substr(pdeb, 5, 6), "-1"))
to <- ISOweek::ISOweek2date(paste0(substr(pfin, 1, 4), "-W", substr(pfin, 5, 6), "-1"))
res <- seq.Date(from, to, by = "week")
return(format(res, format = "%G%V"))
}
foo(201950, 202205)
Step #1 : tranform input to character : YYYY-"W"WW-1
Step #2 : capture the ISOweek
Step #3 : sequence by week
Step #4 : return the sequence to the format "%G%V", still to respect ISO 8601 and YYYYWW
I'd go with
x <- c("202144", "202208")
out <- do.call(seq, c(as.list(as.Date(paste0(x, "1"), format="%Y%U%u")), by = "week"))
out
# [1] "2021-11-01" "2021-11-08" "2021-11-15" "2021-11-22" "2021-11-29" "2021-12-06" "2021-12-13" "2021-12-20" "2021-12-27"
# [10] "2022-01-03" "2022-01-10" "2022-01-17" "2022-01-24" "2022-01-31" "2022-02-07" "2022-02-14" "2022-02-21"
If you really want to keep them in the %Y%W format, then
format(out, format = "%Y%W")
# [1] "202144" "202145" "202146" "202147" "202148" "202149" "202150" "202151" "202152" "202201" "202202" "202203" "202204"
# [14] "202205" "202206" "202207" "202208"
(This answer heavily informed by Transform year/week to date object)
We could do some mathematics.
f <- function(from, to) {
r <- from:to
r[r %% 100 > 0 & r %% 100 < 53]
}
input.from <- 202144; input.to <- 202208
f(input.from, input.to)
# [1] 202144 202145 202146 202147 202148 202149 202150 202151 202152
# [10] 202201 202202 202203 202204 202205 202206 202207 202208

Discretize a date-time variable to "in-hours" and "after-hours"

I have date-times like:
x = c("2015-09-12 03:52:00", "2017-06-15 21:37:28", "2017-04-08 20:44:11")
I want to create two categories: If the time is between 6.30pm and 8 am I want to return "after-hours"`, otherwise it returns "in-hours".
I tried to solve this first by extracting the time part, but that converted it to a character which meant, ifelse was not working.
Thank you in advance.
base R
Cheating a little, converting to %H%M as an integer on a 24h clock.
vec <- as.POSIXct(c("2015-09-12 03:52:00", "2017-06-15 21:37:28", "2017-04-08 20:44:11"))
hhmm <- as.integer(format(vec, format = "%H%M"))
ifelse(hhmm < 0800 | hhmm > 1830, "after-hours", "in-hours")
# [1] "after-hours" "after-hours" "after-hours"
lubridate
Similar, but using decimal hours instead of fake-hour/minute.
library(lubridate)
hhmm2 <- hour(vec) + minute(vec)/60
ifelse(hhmm2 < 8 | hhmm2 > 18.5, "after-hours", "in-hours")
# [1] "after-hours" "after-hours" "after-hours"
times_as_char = c("2015-09-12 03:52:00", "2017-06-15 21:37:28", "2017-04-08 20:44:11")
# Converting character to date-time
times_as_datetimes <- lubridate::ymd_hms(times_as_char)
# We can use decimal hours to make time comparisons easier
times_as_hour_dec <- lubridate::hour(times_as_datetimes) +
lubridate::minute(times_as_datetimes)/60
time_status <- ifelse(times_as_hour_dec < 8 | times_as_hour_dec >= 18.5,
"after-hours",
"in hours")

Add 6 months to a date starting february

I am trying to subtract 3 months from February to a date using lubridate library, however, it always gives me date as 28. I know a lot of people have asked this question, but I have tried a lot of things, but still the same error. Looping through the day is an option. However, I was looking for something efficient
what my code does is this:
where test_end = "2019-02-28"
and lastnmonth = 3
as.Date(test_end) %m-% months(lastnmonth)
I always get the output as "2018-11-28" instead of "2018-11-30"
lubridate::ymd("2019-02-28") - lubridate::period(3, "months")
additional code to work-out mont-end
lubridate::ceiling_date(lubridate::ymd("2019-02-28") - lubridate::period(3, "months"), "months") - lubridate::ddays(1)
You want the last of the month -- so you can use the trick that the next is a first, move that one by the number of months -- and then substract one day.
All in one line of base R:
R> seq(as.Date("2019-02-28") + 1, length=4, by="-1 month") - 1
[1] "2019-02-28" "2019-01-31" "2018-12-31" "2018-11-30"
R>
We add one day, then use a sequence of four months (including current) backwards, and take out one day to be on the last day of the previous month.
If you just want one, simply add tail(..., 1):
R> tail(seq(as.Date("2019-02-28") + 1, length=4, by="-1 month") - 1, 1)
[1] "2018-11-30"
R>
Using Dirk's strategy we can draw-up a function to handle this type of operation:
start_date <- lubridate::ymd("2019-02-28")
mths_to_subtract <- 3
deduct_mth <- function(date_object = start_date,
mths_to_deduct = mths_to_subtract){
days_to_ceiling_date <- lubridate::ceiling_date(date_object, "months") - date_object
date_object + days_to_ceiling_date - lubridate::period(mths_to_deduct, "months") - days_to_ceiling_date
}
Gives the following answers:
> deduct_mth(ymd("2019-02-28"), 3)
[1] "2018-11-30"
> deduct_mth(ymd("2000-02-29"), 3)
[1] "1999-11-30"

R: generate dataframe of Friday dates for the year [duplicate]

This question already has answers here:
Get Dates of a Certain Weekday from a Year in R
(3 answers)
Closed 9 years ago.
I would like to generate a dataframe that contains all the Friday dates for the whole year.
Is there a simple way to do this?
eg for December 2013: (6/12/13,13/12/13,20/12/13,27/12/13)
Thank you for your help.
I'm sure there is a simpler way, but you could brute force it easy enough:
dates <- seq.Date(as.Date("2013-01-01"),as.Date("2013-12-31"),by="1 day")
dates[weekdays(dates)=="Friday"]
dates[format(dates,"%w")==5]
Building on #Frank's good work, you can find all of any specific weekday between two dates like so:
pick.wkday <- function(selday,start,end) {
fwd.7 <- start + 0:6
first.day <- fwd.7[as.numeric(format(fwd.7,"%w"))==selday]
seq.Date(first.day,end,by="week")
}
start and end need to be Date objects, and selday is the day of the week you want (0-6 representing Sunday-Saturday).
i.e. - for the current query:
pick.wkday(5,as.Date("2013-01-01"),as.Date("2013-12-31"))
Here is a way.
d <- as.Date(1:365, origin = "2013-1-1")
d[strftime(d,"%A") == "Friday"]
Alternately, this would be a more efficient approach for generating the data for an arbitrary number of Fridays:
wk1 <- as.Date(seq(1:7), origin = "2013-1-1") # choose start date & make 7 consecutive days
wk1[weekdays(wk1) == "Friday"] # find Friday in the sequence of 7 days
seq.Date(wk1[weekdays(wk1) == "Friday"], length.out=50, by=7) # use it to generate fridays
by=7 says go to the next Friday.
length.out controls the number of Fridays to generate. One could also use to to control how many Fridays are generated (e.g. use to=as.Date("2013-12-31") instead of length.out).
Takes a year as input and returns only the fridays...
getFridays <- function(year) {
dates <- seq(as.Date(paste0(year,"-01-01")),as.Date(paste0(year,"-12-31")), by = "day")
dates[weekdays(dates) == "Friday"]
}
Example:
> getFridays(2000)
[1] "2000-01-07" "2000-01-14" "2000-01-21" "2000-01-28" "2000-02-04" "2000-02-11" "2000-02-18" "2000-02-25" "2000-03-03" "2000-03-10" "2000-03-17" "2000-03-24" "2000-03-31"
[14] "2000-04-07" "2000-04-14" "2000-04-21" "2000-04-28" "2000-05-05" "2000-05-12" "2000-05-19" "2000-05-26" "2000-06-02" "2000-06-09" "2000-06-16" "2000-06-23" "2000-06-30"
[27] "2000-07-07" "2000-07-14" "2000-07-21" "2000-07-28" "2000-08-04" "2000-08-11" "2000-08-18" "2000-08-25" "2000-09-01" "2000-09-08" "2000-09-15" "2000-09-22" "2000-09-29"
[40] "2000-10-06" "2000-10-13" "2000-10-20" "2000-10-27" "2000-11-03" "2000-11-10" "2000-11-17" "2000-11-24" "2000-12-01" "2000-12-08" "2000-12-15" "2000-12-22" "2000-12-29"
There are probably more elegant ways to do this, but here's one way to generate a vector of Fridays, given any year.
year = 2007
st <- as.POSIXlt(paste0(year, "/1/01"))
en <- as.Date(paste0(year, "/12/31"))
#get to the next Friday
skip_ahead <- 5 - st$wday
if(st$wday == 6) skip_ahead <- 6 #for Saturdays, skip 6 days ahead.
first.friday <- as.Date(st) + skip_ahead
dates <- seq(first.friday, to=en, by ="7 days")
dates
#[1] "2007-01-05" "2007-01-12" "2007-01-19" "2007-01-26"
# [5] "2007-02-02" "2007-02-09" "2007-02-16" "2007-02-23"
# [9] "2007-03-02" "2007-03-09" "2007-03-16" "2007-03-23"
I think this would be the most efficient way and would also returns all the Friday in the whole of 2013.
FirstWeek <- seq(as.Date("2013/1/1"), as.Date("2013/1/7"), "days")
seq(
FirstWeek[weekdays(FirstWeek) == "Friday"],
as.Date("2013/12/31"),
by = "week"
)

Date sequence in R spanning B.C.E. to A.D

I would like to generate a sequence of dates from 10,000 B.C.E. to the present. This is easy for 0 C.E. (or A.D.):
ADtoNow <- seq.Date(from = as.Date("0/1/1"), to = Sys.Date(), by = "day")
But I am stumped as to how to generate dates before 0 AD. Obviously, I could do years before present but it would be nice to be able to graph something as BCE and AD.
To expand on Ricardo's suggestion, here is some testing of how things work. Or don't work for that matter.
I will repeat Joshua's warning taken from ?as.Date for future searchers in big bold letters:
"Note: Years before 1CE (aka 1AD) will probably not be handled correctly."
as.integer(as.Date("0/1/1"))
[1] -719528
as.integer(seq(as.Date("0/1/1"),length=2,by="-10000 years"))
[1] -719528 -4371953
seq(as.Date(-4371953,origin="1970-01-01"),Sys.Date(),by="1000 years")
# nonsense
[1] "0000-01-01" "'000-01-01" "(000-01-01" ")000-01-01" "*000-01-01"
[6] "+000-01-01" ",000-01-01" "-000-01-01" ".000-01-01" "/000-01-01"
[11] "0000-01-01" "1000-01-01" "2000-01-01"
> as.integer(seq(as.Date(-4371953,origin="1970-01-01"),Sys.Date(),by="1000 years"))
# also possibly nonsense
[1] -4371953 -4006710 -3641468 -3276225 -2910983 -2545740 -2180498 -1815255
[9] -1450013 -1084770 -719528 -354285 10957
Though this does seem to work for graphing somewhat:
yrs1000 <- seq(as.Date(-4371953,origin="1970-01-01"),Sys.Date(),by="1000 years")
plot(yrs1000,rep(1,length(yrs1000)),axes=FALSE,ann=FALSE)
box()
axis(2)
axis(1,at=yrs1000,labels=c(paste(seq(10000,1000,by=-1000),"BC",sep=""),"0AD","1000AD","2000AD"))
title(xlab="Year",ylab="Value")
Quite some time has gone by since this question was asked. With that time came a new R package, gregorian which can handle BCE time values in the as_gregorian method.
Here's an example of piecewise constructing a list of dates that range from -10000 BCE to the current year.
library(lubridate)
library(gregorian)
# Container for the dates
dates <- c()
starting_year <- year(now())
# Add the CE dates to the list
for (year in starting_year:0){
date <- sprintf("%s-%s-%s", year, "1", "1")
dates <- c(dates, gregorian::as_gregorian(date))
}
starting_year <- "-10000"
# Add the BCE dates to the list
for (year in starting_year:0){
start_date <- gregorian::as_gregorian("-10000-1-1")
date <- sprintf("%s-%s-%s", year, "1", "1")
dates <- c(dates, gregorian::as_gregorian(date))
}
How you use the list is up to you, just know that the relevant properties of the date objects are year and bce. For example, you can loop over list of dates, parse the year, and determine if it's BCE or not.
> gregorian_date <- gregorian::as_gregorian("-10000-1-1")
> gregorian_date$bce
[1] TRUE
> gregorian_date$year
[1] 10001
Notes on 0AD
The gregorian package assumes that when you mean Year 0, you're really talking about year 1 (shown below). I personally think an exception should be thrown, but that's the mapping users needs to keep in mind.
> gregorian::as_gregorian("0-1-1")
[1] "Monday January 1, 1 CE"
This is also the case with BCE
> gregorian::as_gregorian("-0-1-1")
[1] "Saturday January 1, 1 BCE"
As #JoshuaUlrich commented, the short answer is no.
However, you can splice out the year into a separate column and then convert to integer. Would this work for you?
The package lubridate seems to handle "negative" years ok, although it does create a year 0, which from the above comments seems to be inaccurate. Try:
library(lubridate)
start <- -10000
stop <- 2013
myrange <- NULL
for (x in start:stop) {
myrange <- c(myrange,ymd(paste0(x,'-01-01')))
}

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