I have one question. How to convert that format 20110711201023 of date and time, to the number of hours. This is output of software which I use to image analysis, and I can’t change it. It is very important to define starting Date and Time.
Format: 2011 year, 07 month, 11 day, 20 hour, 10 minute, 23 second.
Example:
Starting Data and Time - 20110709201023,
First Data and Time - 20110711214020
Result = 49,5h.
I have 10000 data in this format so I don't want to do this manually.
I will be very gratefully for any advice.
Best is to first make it a real R time object using strptime:
time_obj = strptime("20110711201023", format = "%Y%m%d%H%M%S")
If you do this with both the start and the end date, you can simply say:
end_time - start_time
to get the difference in seconds, which can easily be converted to number of hours. To convert a whole list of these time strings, simply do:
time_vector = strptime(dat$time_string, format = "%Y%m%d%H%M%S")
where dat is the data.frame with the data, and time_string the column containing the time strings. Note that strptime works also on a vector (it is vectorized). You can also make the new time vector part of dat:
dat$time = strptime(dat$time_string, format = "%Y%m%d%H%M%S")
or more elegantly (at least if you hate $ as much as me :)):
dat = within(dat, { time = strptime(dat$time_string, format = "%Y%m%d%H%M%S") })
Related
I have a .csv file that looks like this:
Date
Time
Demand
01-Jan-05
6:30
6
01-Jan-05
6:45
3
...
23-Jan-05
21:45
0
23-Jan-05
22:00
1
The days are broken into 15 minute increments from 6:30 - 22:00.
Now, I am trying to do a time series on this, but I am a little lost on the notation of this.
I have the following so far:
library(tidyverse)
library(forecast)
library(zoo)
tp <- read.csv(".csv")
tp.ts <- ts(tp$DEMAND, start = c(), end = c(), frequency = 63)
The frequency I am after is an entire day, which I believe makes the number 63.***
However, I am unsure as to how to notate the dates in c().
***Edit
If the frequency is meant to be observations per a unit of time, and I am trying to observe just (Demand) by the 15 minute time slots (Time) in each day (Date), maybe my Frequency is 1?
***Edit 2
So I think I am struggling with doing the time series because I have a Date column (which is characters) and a Time column.
Since I need the data for Demand at the given hours on the dates, maybe I need to convert the dates to be used in ts() and combine the Date and Time date into a new column?
If I do this, I am assuming this should give me the times I need (6:30 to 22:00) but with the addition of having the date?
However, the data is to be used to predict the Demand for the rest of the month. So maybe the Date is an important variable if the day of the week impacts Demand?
We assume you are starting with tp shown reproducibly in the Note at the end. A complete cycle of 24 * 4 = 96 points should be represented by one unit of time internally. The chron class does that so read it in as a zoo series z with chron time index and then convert that to ts giving ts_ser or possibly leave it as a zoo series depending on what you are going to do next.
library(zoo)
library(chron)
to_chron <- function(date, time) as.chron(paste(date, time), "%d-%b-%y %H:%M")
z <- read.zoo(tp, index = 1:2, FUN = to_chron, frequency = 4 * 24)
ts_ser <- as.ts(z)
Note
tp <- structure(list(Date = c("01-Jan-05", "01-Jan-05"), Time = c("6:30",
"6:45"), Demand = c(6L, 3L)), row.names = 1:2, class = "data.frame")
Is there a time interval data (variable) type in R? I have a CSV file with datetime and timeinterval columns. The data type of the datetime column can be POSIXlt, but I don't know how to set a timeinterval data type for the other column. Is it possible, or what is the best way to handle time inervals in R?
The time interval values in my CSV file looks like this [<number of days> %H:%M:%S]:
'0 20:32:59'
In Python pandas, there is a timedelta64[ns] data type for time intervals.
Thank you!
Split the strings into the number of days and the time, using stringi, then use lubridate to manipulate the components.
library(stringi)
library(lubridate)
In the following example:
([0-9]+) means capture one or more digits.
+ means one or more spaces (not captured).
([0-9]{2}:[0-9]{2}:[0-9]{2}) means capture 2 digits, a colon, 2 digits, another colon, and 2 more digits.
x <- "0 20:32:59"
matches <- stri_match_first_regex(x, "([0-9]+) +([0-9]{2}:[0-9]{2}:[0-9]{2})")
The number of days is the second column, and the hours/minutes/seconds are in the third column.
days creates a period of the number of days; hms creates a period of hours, minutes, and seconds.
n_days <- days(as.integer(matches[, 2]))
time <- hms(matches[, 3])
Now your total is just n_days + time, though presumably you want this relative to some origin, for example:
Sys.time() + n_days + time
Yes, see ? difftime
If your csv is already split into columns, apply as.difftime to one and as.POSIXlt to the other.
For example:
as.difftime(0, units="days") + as.POSIXlt("20:32:59", format="%H:%M:%S")
[Edit]
If the entire result is to be an interval, this would do it:
as.difftime(0, units="days") + as.difftime("20:32:59", format="%H:%M:%S")
I have this .txt file:
http://pastebin.com/raw.php?i=0fdswDxF
First column (Date) shows date in month/day
So 0601 is the 1st of June
When I load this into R and I show the data, it removes the first 0 in the data.
So when loaded it looks like:
601
602
etc
For 1st of June, 2nd of June
For the months 10,11,12, it remains unchanged.
How do I change it back to 0601 etc.?
What I am trying to do is to change these days into the day of the year, for instance,
1st of January (0101) would be 1, and 31st of December would be 365.
There is no leap year to be considered.
I have the code to change this, if my data was shown as 0601 etc, but not as 601 etc.
copperNew$Date = as.numeric(as.POSIXct(strptime(paste0("2013",copperNew$Date), format="%Y%m%d")) -
as.POSIXct("2012-12-31"), units = "days")
Where Date of course is from the file linked above.
Please ask if you do not consider the description to be good enough.
You can use colClasses in the read.table function, then convert to POSIXlt and extract the year date. You are over complicating the process.
copperNew <- read.table("http://pastebin.com/raw.php?i=0fdswDxF", header=TRUE,
colClasses=c("character", "integer", rep("numeric", 3)))
tmp <- as.POSIXlt( copperNew$Date, format='%m%d' )
copperNew$Yday <- tmp$yday
The as.POSIXct function is able to parse a string without a year (assumes the current year) and computes the day of the year for you.
d<-as.Date("0201", format = "%m%d")
strftime(d, format="%j")
#[1] "032"
First you parse your string and obtain Date object which represents your date (notice that it will add current year, so if you want to count days for some specific year add it to your string: as.Date("1988-0201", format = "%Y-%m%d")).
Function strftime will convert your Date to POSIXlt object and return day of year. If you want the result to be a numeric value, you can do it like this: as.numeric(strftime(d, format = "%j"))(Thanks Gavin Simpson)
Convert it to POSIXlt using a year that is not a leap-year, then access the yday element and add 1 (because yday is 0 on January 1st).
strptime(paste0("2011","0201"),"%Y%m%d")$yday+1
# [1] 32
From start-to-finish:
x <- read.table("http://pastebin.com/raw.php?i=0fdswDxF",
colClasses=c("character",rep("numeric",5)), header=TRUE)
x$Date <- strptime(paste0("2011",x$Date),"%Y%m%d")$yday+1
In which language?
If it's something like C#, Java or Javascript, I'd follow these steps:
1-) parse a pair of integers from that column;
2-) create a datetime variable whose day and month are taken from the integers from step one. Set the year to some fixed value, or to the current year.
3-) create another datetime variable, whose date is the 1st of February of the same year as the one in step 2.
The number of the day is the difference in days between the datetime variables, + 1 day.
This one worked for me:
copperNew <- read.table("http://pastebin.com/raw.php?i=0fdswDxF",
header=TRUE, sep=" ", colClasses=c("character",
"integer",
rep("numeric", 3)))
copperNew$diff = difftime(as.POSIXct(strptime(paste0("2013",dat$Date),
format="%Y%m%d", tz="GMT")),
as.POSIXct("2012-12-31", tz="GMT"), units="days")
I had to specify the timezone (tz argument in as.POSIXct), otherwise I got two different timezones for the vectors I am subtracting and therefore non-integer days.
I want to create a single column with a sequence of date/time increasing every hour for one year or one month (for example). I was using a code like this to generate this sequence:
start.date<-"2012-01-15"
start.time<-"00:00:00"
interval<-60 # 60 minutes
increment.mins<-interval*60
x<-paste(start.date,start.time)
for(i in 1:365){
print(strptime(x, "%Y-%m-%d %H:%M:%S")+i*increment.mins)
}
However, I am not sure how to specify the range of the sequence of dates and hours. Also, I have been having problems dealing with the first hour "00:00:00"? Not sure what is the best way to specify the length of the date/time sequence for a month, year, etc? Any suggestion will be appreciated.
I would strongly recommend you to use the POSIXct datatype. This way you can use seq without any problems and use those data however you want.
start <- as.POSIXct("2012-01-15")
interval <- 60
end <- start + as.difftime(1, units="days")
seq(from=start, by=interval*60, to=end)
Now you can do whatever you want with your vector of timestamps.
Try this. mondate is very clever about advancing by a month. For example, it will advance the last day of Jan to last day of Feb whereas other date/time classes tend to overshoot into Mar. chron does not use time zones so you can't get the time zone bugs that code as you can using POSIXct. Here x is from the question.
library(chron)
library(mondate)
start.time.num <- as.numeric(as.chron(x))
# +1 means one month. Use +12 if you want one year.
end.time.num <- as.numeric(as.chron(paste(mondate(x)+1, start.time)))
# 1/24 means one hour. Change as needed.
hours <- as.chron(seq(start.time.num, end.time.num, 1/24))
How to convert between year,month,day and dates in R?
I know one can do this via strings, but I would prefer to avoid converting to strings, partly because maybe there is a performance hit?, and partly because I worry about regionalization issues, where some of the world uses "year-month-day" and some uses "year-day-month".
It looks like ISODate provides the direction year,month,day -> DateTime , although it does first converts the number to a string, so if there is a way that doesn't go via a string then I prefer.
I couldn't find anything that goes the other way, from datetimes to numerical values? I would prefer not needing to use strsplit or things like that.
Edit: just to be clear, what I have is, a data frame which looks like:
year month day hour somevalue
2004 1 1 1 1515353
2004 1 1 2 3513535
....
I want to be able to freely convert to this format:
time(hour units) somevalue
1 1515353
2 3513535
....
... and also be able to go back again.
Edit: to clear up some confusion on what 'time' (hour units) means, ultimately what I did was, and using information from How to find the difference between two dates in hours in R?:
forwards direction:
lh$time <- as.numeric( difftime(ISOdate(lh$year,lh$month,lh$day,lh$hour), ISOdate(2004,1,1,0), units="hours"))
lh$year <- NULL; lh$month <- NULL; lh$day <- NULL; lh$hour <- NULL
backwards direction:
... well, I didnt do backwards yet, but I imagine something like:
create difftime object out of lh$time (somehow...)
add ISOdate(2004,1,1,0) to difftime object
use one of the solution below to get the year,month,day, hour back
I suppose in the future, I could ask the exact problem I'm trying to solve, but I was trying to factorize my specific problem into generic reusable questions, but maybe that was a mistake?
Because there are so many ways in which a date can be passed in from files, databases etc and for the reason you mention of just being written in different orders or with different separators, representing the inputted date as a character string is a convenient and useful solution. R doesn't hold the actual dates as strings and you don't need to process them as strings to work with them.
Internally R is using the operating system to do these things in a standard way. You don't need to manipulate strings at all - just perhaps convert some things from character to their numerical equivalent. For example, it is quite easy to wrap up both operations (forwards and backwards) in simple functions you can deploy.
toDate <- function(year, month, day) {
ISOdate(year, month, day)
}
toNumerics <- function(Date) {
stopifnot(inherits(Date, c("Date", "POSIXt")))
day <- as.numeric(strftime(Date, format = "%d"))
month <- as.numeric(strftime(Date, format = "%m"))
year <- as.numeric(strftime(Date, format = "%Y"))
list(year = year, month = month, day = day)
}
I forego the a single call to strptime() and subsequent splitting on a separation character because you don't like that kind of manipulation.
> toDate(2004, 12, 21)
[1] "2004-12-21 12:00:00 GMT"
> toNumerics(toDate(2004, 12, 21))
$year
[1] 2004
$month
[1] 12
$day
[1] 21
Internally R's datetime code works well and is well tested and robust if a bit complex in places because of timezone issues etc. I find the idiom used in toNumerics() more intuitive than having a date time as a list and remembering which elements are 0-based. Building on the functionality provided would seem easier than trying to avoid string conversions etc.
I'm a bit late to the party, but one other way to convert from integers to date is the lubridate::make_date function. See the example below from R for Data Science:
library(lubridate)
library(nycflights13)
library(tidyverse)
a <- flights %>%
mutate(date = make_date(year, month, day))
Found one solution for going from date to year,month,day.
Let's say we have a date object, that we'll create here using ISOdate:
somedate <- ISOdate(2004,12,21)
Then, we can get the numerical components of this as follows:
unclass(as.POSIXlt(somedate))
Gives:
$sec
[1] 0
$min
[1] 0
$hour
[1] 12
$mday
[1] 21
$mon
[1] 11
$year
[1] 104
Then one can get what one wants for example:
unclass(as.POSIXlt(somedate))$mon
Note that $year is [actual year] - 1900, month is 0-based, mday is 1-based (as per the POSIX standard)