I have a variable of the form "2020-09-01". I need to increase and decrease this by 3 months and 5 months and store it in other variables. I need a syntax in Spark R.Thanks. Any other method will also work.Thanks, Again
In R following code works fine
y <- as.Date(load_date,"%Y-%m-%d") %m+% months(i)
The code below didn't work. Error says
unable to find an inherited method for function ‘add_months’ for signature ‘"Date", "numeric"
loaddate = 202009
year <- substr(loaddate,1,4)
month <- substr(loaddate,5,6)
load_date <- paste(year,month,"01",sep = "-")
y <- as.Date(load_date,"%Y%m%d")
y1 <- add_months(y,-3)
Expected Result - 2020-06-01
The lubridate package makes dealing with dates much easier. Here I have shuffled as.Date up a step, then simply subtract 3 months.
library(lubridate)
loaddate = 202009
year <- substr(loaddate,1,4)
month <- substr(loaddate,5,6)
load_date <- as.Date(paste(year,month,"01",sep = "-"))
new_date <- load_date - months(3)
new_date Output:
Date[1:1], format: "2020-06-01"
Related
For a time series analysis of over 1000 raster in a raster stack I need the date. The data is almost weekly in the structure of the files
"... 1981036 .... tif"
The zero separates year and week
I need something like: "1981-36"
but always get the error
Error in charToDate (x): character string is not in a standard unambiguous format
library(sp)
library(lubridate)
library(raster)
library(Zoo)
raster_path <- ".../AVHRR_All"
all_raster <- list.files(raster_path,full.names = TRUE,pattern = ".tif$")
all_raster
brings me:
all_raster
".../VHP.G04.C07.NC.P1981036.SM.SMN.Andes.tif"
".../VHP.G04.C07.NC.P1981037.SM.SMN.Andes.tif"
".../VHP.G04.C07.NC.P1981038.SM.SMN.Andes.tif"
…
To get the year and the associated week, I have used the following code:
timeline <- data.frame(
year= as.numeric(substr(basename(all_raster), start = 17, stop = 17+3)),
week= as.numeric(substr(basename(all_raster), 21, 21+2))
)
timeline
brings me:
timeline
year week
1 1981 35
2 1981 36
3 1981 37
4 1981 38
…
But I need something like = "1981-35" to be able to plot my time series later
I tried that:
timeline$week <- as.Date(paste0(timeline$year, "%Y")) + week(timeline$week -1, "%U")
and get the error:Error in charToDate(x) : character string is not in a standard unambiguous format
or I tried that
fileDates <- as.POSIXct(substr((all_raster),17,23), format="%y0%U")
and get the same error
until someone will post a better way to do this, you could try:
x <- c(".../VHP.G04.C07.NC.P1981036.SM.SMN.Andes.tif", ".../VHP.G04.C07.NC.P1981037.SM.SMN.Andes.tif",
".../VHP.G04.C07.NC.P1981038.SM.SMN.Andes.tif")
xx <- substr(x, 21, 27)
library(lubridate)
dates <- strsplit(xx,"0")
dates <- sapply(dates,function(x) {
year_week <- unlist(x)
year <- year_week[1]
week <- year_week[2]
start_date <- as.Date(paste0(year,'-01-01'))
date <- start_date+weeks(week)
#note here: OP asked for beginning of week.
#There's some ambiguity here, the above is end-of-week;
#uncommment here for beginning of week, just subtracted 6 days.
#I think this might yield inconsistent results, especially year-boundaries
#hence suggestion to use end of week. See below for possible solution
#date <- start_date+weeks(week)-days(6)
return (as.character(date))
})
newdates <- as.POSIXct(dates)
format(newdates, "%Y-%W")
Thanks to #Soren who posted this anwer here: Get the month from the week of the year
You can do it if you specify that Monday is a Weekday 1 with %u:
w <- c(35,36,37,38)
y <- c(1981,1981,1981,1981)
s <- c(1,1,1,1)
df <- data.frame(y,w,s)
df$d <- paste(as.character(df$y), as.character(df$w),as.character(df$s), sep=".")
df$date <- as.Date(df$d, "%Y.%U.%u")
# So here we have variable date as date if you need that for later.
class(df$date)
#[1] "Date"
# If you want it to look like Y-W, you can do the final formatting:
df$date <- format(df$date, "%Y-%U")
# y w s d date
# 1 1981 35 1 1981.35.1 1981-35
# 2 1981 36 1 1981.36.1 1981-36
# 3 1981 37 1 1981.37.1 1981-37
# 4 1981 38 1 1981.38.1 1981-38
# NB: though it looks correct, the resulting df$date is actually a character:
class(df$date)
#[1] "character"
Alternatively, you could do the same by setting the Sunday as 0 with %w.
Let's say we have this:
ex <- c('2012-41')
This represent the week 41 from the year 2012. How would I get the month from this?
Since a week can be between two months, I will be interested to get the month when that week started (here October).
Not duplicate to How to extract Month from date in R (do not have a standard date format like %Y-%m-%d).
you could try:
ex <- c('2019-10')
splitDate <- strsplit(ex, "-")
dateNew <- as.Date(paste(splitDate[[1]][1], splitDate[[1]][2], 1, sep="-"), "%Y-%U-%u")
monthSelected <- lubridate::month(dateNew)
3
I hope this helps!
This depends on the definition of week. See the discussion of %V and %W in ?strptime for two possible definitions of week. We use %V below but the function allows one to specify the other if desired. The function performs a sapply over the elements of x and for each such element it extracts the year into yr and forms a sequence of all dates for that year in sq. It then converts those dates to year-month and finds the first occurrence of the current component of x in that sequence, finally extracting the match's month.
yw2m <- function(x, fmt = "%Y-%V") {
sapply(x, function(x) {
yr <- as.numeric(substr(x, 1, 4))
sq <- seq(as.Date(paste0(yr, "-01-01")), as.Date(paste0(yr, "-12-31")), "day")
as.numeric(format(sq[which.max(format(sq, fmt) == x)], "%m"))
})
}
yw2m('2012-41')
## [1] 10
The following will add the week-of-year to an input of year-week formatted strings and return a vector of dates as character. The lubridate package weeks() function will add the dates corresponding to the end of the relevant week. Note for example I've added an additional case in your 'ex' variable to the 52nd week, and it returns Dec-31st
library(lubridate)
ex <- c('2012-41','2016-4','2018-52')
dates <- strsplit(ex,"-")
dates <- sapply(dates,function(x) {
year_week <- unlist(x)
year <- year_week[1]
week <- year_week[2]
start_date <- as.Date(paste0(year,'-01-01'))
date <- start_date+weeks(week)
#note here: OP asked for beginning of week.
#There's some ambiguity here, the above is end-of-week;
#uncommment here for beginning of week, just subtracted 6 days.
#I think this might yield inconsistent results, especially year-boundaries
#hence suggestion to use end of week. See below for possible solution
#date <- start_date+weeks(week)-days(6)
return (as.character(date))
})
Yields:
> dates
[1] "2012-10-14" "2016-01-29" "2018-12-31"
And to simply get the month from these full dates:
month(dates)
Yields:
> month(dates)
[1] 10 1 12
I'm trying to set up a new variable that incorporates the difference (in number of days) between a known date and the end of a given year. Dummy data below:
> Date.event <- as.POSIXct(c("12/2/2000","8/2/2001"), format = "%d/%m/%Y", tz = "Europe/London")
> Year = c(2000,2001)
> Dates.test <- data.frame(Date.event,Year)
> Dates.test
Date.event Year
1 2000-02-12 2000
2 2001-02-08 2001
I've tried applying a function to achieve this, but it returns an error
> Time.dif.fun <- function(x) {
+ as.numeric(as.POSIXct(sprintf('31/12/%s', s= x['Year']),format = "%d/%m/%Y", tz = "Europe/London") - x['Date.event'])
+ }
> Dates.test$Time.dif <- apply(
+ Dates.test, 1, Time.dif.fun
+ )
Error in unclass(e1) - e2 : non-numeric argument to binary operator
It seems that apply() does not like as.POSIXct(), as testing a version of the function that only derives the end of year date, it is returned as a numeric in the form '978220800' (e.g. for end of year 2000). Is there any way around this? For the real data the function is a bit more complex, including conditional instances using different variables and sometimes referring to previous rows, which would be very hard to do without apply.
Here are some alternatives:
1) Your code works with these changes. We factored out s, not because it is necessary, but only because the following line gets very hard to read without that due to its length. Note that if x is a data frame then so is x["Year"] but x[["Year"]] is a vector as is x$Year. Since the operations are all vectorized we do not need apply.
Although we have not made this change, it would be a bit easier to define s as s <- paste0(x$Year, "-12-31") in which case we could omit the format argument in the following line owing to the use of the default format.
Time.dif.fun <- function(x) {
s <- sprintf('31/12/%s', x[['Year']])
as.numeric(as.POSIXct(s, format = "%d/%m/%Y", tz = "Europe/London") -x[['Date.event']])
}
Time.dif.fun(Dates.test)
## [1] 323 326
2) Convert to POSIXlt, set the year, month and day to the end of the year and subtract. Note that the year component uses years since 1900 and the mon component uses Jan = 0, Feb = 1, ..., Dec = 11. See ?as.POSIXlt for details on these and other components:
lt <- as.POSIXlt(Dates.test$Date.event)
lt$year <- Dates.test$Year - 1900
lt$mon <- 11
lt$mday <- 31
as.numeric(lt - Dates.test$Date.event)
## [1] 323 326
3) Another possibility is:
with(Dates.test, as.numeric(as.Date(paste0(Year, "-12-31")) - as.Date(Date.event)))
## [1] 323 326
You could use the difftime function:
Dates.test$diff_days <- difftime(as.POSIXct(paste0(Dates.test[,2],"-12-31"),format = "%Y-%m-%d", tz = "Europe/London"),Dates.test[,1],unit="days")
You can use ISOdate to build the end of year date, and the difftime(... units='days') to get the days til end of year.
From ?difftime:
Limited arithmetic is available on "difftime" objects: they can be
added or subtracted, and multiplied or divided by a numeric vector.
If you want to do more than the limited arithmetic, just coerce with as.numeric(), but you will have to stick with whatever units you specified.
By convention, you may wish to use the beginning of the next year (midnight on new year's eve) as your endpoint for that year. For example:
Dates.test <- data.frame(
Date.event = as.POSIXct(c("12/2/2000","8/2/2001"),
format = "%d/%m/%Y", tz = "Europe/London")
)
# use data.table::year() to get the year of a date
year <- function(x) as.POSIXlt(x)$year + 1900L
Dates.test$Date.end <- ISOdate(year(Dates.test$Date.event)+1,1,1)
# if you don't want class 'difftime', wrap it in as.numeric(), as in:
Dates.test$Date.diff <- as.numeric(
difftime(Dates.test$Date.end,
Dates.test$Date.event,
units='days')
)
Dates.test
# Date.event Date.end Date.diff
# 1 2000-02-12 2001-01-01 12:00:00 324.5
# 2 2001-02-08 2002-01-01 12:00:00 327.5
The apply() family are basically a clean way of doing for loops, and you should strive for more efficient, vectorized solutions.
I have a vector of dates of the form BW01.68, BW02.68, ... , BW26.10. BW stands for "bi-week", so for example, "BW01.68" represents the first bi-week of the year 1968, and "BW26.10" represents the 26th (and final) bi-week of the year 2010. Using R, how could I convert this vector into actual dates, say, of the form 01-01-1968, 01-15-1968, ... , 12-16-2010? Is there a way for R to know exactly which dates correspond to each bi-week? Thanks for any help!
An alternative solution.
biwks <- c("BW01.68", "BW02.68", "BW26.10")
bw <- substr(biwks,3,4)
yr <- substr(biwks,6,7)
yr <- paste0(ifelse(as.numeric(yr) > 15,"19","20"),yr)
# the %j in the date format is the number of days into the year
as.Date(paste(((as.numeric(bw)-1) * 14) + 1,yr,sep="-"),format="%j-%Y")
#[1] "1968-01-01" "1968-01-15" "2010-12-17"
Though I will note that a 'bi-week' seems a strange measure and I can't be sure that just using 14 day blocks is what is intended in your work.
You can make this code a lot shorter. I have spaced out each step to help understanding but you could finish it off in one (long) line of code.
bw <- c('BW01.68', 'BW02.68','BW26.10','BW22.13')
# the gsub will ensure that bw01.1 the same as bw01.01, bw1.01, or bw1.1
#isolating year no
yearno <- as.numeric(
gsub(
x = bw,
pattern = "BW.*\\.",
replacement = ""
)
)
#isolating and converting bw to no of days
dayno <- 14 * as.numeric(
gsub(
x = bw,
pattern = "BW|\\.[[:digit:]]{1,2}",
replacement = ""
)
)
#cutoff year chosen as 15
yearno <- yearno + 1900
yearno[yearno < 1915] <- yearno[yearno < 1915] + 100
# identifying dates
dates <- as.Date(paste0('01/01/',yearno),"%d/%m/%Y") + dayno
# specifically identifinyg mondays of that week no
mondaydates <- dates - as.numeric(strftime(dates,'%w')) + 1
Output -
> bw
[1] "BW01.68" "BW02.68" "BW26.10" "BW22.13"
> dates
[1] "1968-01-15" "1968-01-29" "2010-12-31" "2013-11-05"
> mondaydates
[1] "1968-01-15" "1968-01-29" "2010-12-27" "2013-11-04"
PS: Just be careful that you're aligned with how bw is measured in your data and whether you're translating it correctly. You should be able to manipulate this to get it to work, for instance you might encounter a bw 27.
This works for me in R:
# Setting up the first inner while-loop controller, the start of the next water year
NextH2OYear <- as.POSIXlt(firstDate)
NextH2OYear$year <- NextH2OYear$year + 1
NextH2OYear<-as.Date(NextH2OYear)
But this doesn't:
# Setting up the first inner while-loop controller, the start of the next water month
NextH2OMonth <- as.POSIXlt(firstDate)
NextH2OMonth$mon <- NextH2OMonth$mon + 1
NextH2OMonth <- as.Date(NextH2OMonth)
I get this error:
Error in as.Date.POSIXlt(NextH2OMonth) :
zero length component in non-empty POSIXlt structure
Any ideas why? I need to systematically add one year (for one loop) and one month (for another loop) and am comparing the resulting changed variables to values with a class of Date, which is why they are being converted back using as.Date().
Thanks,
Tom
Edit:
Below is the entire section of code. I am using RStudio (version 0.97.306). The code below represents a function that is passed an array of two columns (Date (CLass=Date) and Discharge Data (Class=Numeric) that are used to calculate the monthly averages. So, firstDate and lastDate are class Date and determined from the passed array. This code is adapted from successful code that calculates the yearly averages - there maybe one or two things I still need to change over, but I am prevented from error checking later parts due to the early errors I get in my use of POSIXlt. Here is the code:
MonthlyAvgDischarge<-function(values){
#determining the number of values - i.e. the number of rows
dataCount <- nrow(values)
# Determining first and last dates
firstDate <- (values[1,1])
lastDate <- (values[dataCount,1])
# Setting up vectors for results
WaterMonths <- numeric(0)
class(WaterMonths) <- "Date"
numDays <- numeric(0)
MonthlyAvg <- numeric(0)
# while loop variables
loopDate1 <- firstDate
loopDate2 <- firstDate
# Setting up the first inner while-loop controller, the start of the next water month
NextH2OMonth <- as.POSIXlt(firstDate)
NextH2OMonth$mon <- NextH2OMonth$mon + 1
NextH2OMonth <- as.Date(NextH2OMonth)
# Variables used in the loops
dayCounter <- 0
dischargeTotal <- 0
dischargeCounter <- 1
resultsCounter <- 1
loopCounter <- 0
skipcount <- 0
# Outer while-loop, controls the progression from one year to another
while(loopDate1 <= lastDate)
{
# Inner while-loop controls adding up the discharge for each water year
# and keeps track of day count
while(loopDate2 < NextH2OMonth)
{
if(is.na(values[resultsCounter,2]))
{
# Skip this date
loopDate2 <- loopDate2 + 1
# Skip this value
resultsCounter <- resultsCounter + 1
#Skipped counter
skipcount<-skipcount+1
} else{
# Adding up discharge
dischargeTotal <- dischargeTotal + values[resultsCounter,2]
}
# Adding a day
loopDate2 <- loopDate2 + 1
#Keeping track of days
dayCounter <- dayCounter + 1
# Keeping track of Dicharge position
resultsCounter <- resultsCounter + 1
}
# Adding the results/water years/number of days into the vectors
WaterMonths <- c(WaterMonths, as.Date(loopDate2, format="%mm/%Y"))
numDays <- c(numDays, dayCounter)
MonthlyAvg <- c(MonthlyAvg, round((dischargeTotal/dayCounter), digits=0))
# Resetting the left hand side variables of the while-loops
loopDate1 <- NextH2OMonth
loopDate2 <- NextH2OMonth
# Resetting the right hand side variable of the inner while-loop
# moving it one year forward in time to the next water year
NextH2OMonth <- as.POSIXlt(NextH2OMonth)
NextH2OMonth$year <- NextH2OMonth$Month + 1
NextH2OMonth<-as.Date(NextH2OMonth)
# Resettting vraiables that need to be reset
dayCounter <- 0
dischargeTotal <- 0
loopCounter <- loopCounter + 1
}
WaterMonths <- format(WaterMonthss, format="%mm/%Y")
# Uncomment the line below and return AvgAnnualDailyAvg if you want the water years also
# AvgAnnDailyAvg <- data.frame(WaterYears, numDays, YearlyDailyAvg)
return((MonthlyAvg))
}
Same error occurs in regular R. When doing it line by line, its not a problem, when running it as a script, it it.
Plain R
seq(Sys.Date(), length = 2, by = "month")[2]
seq(Sys.Date(), length = 2, by = "year")[2]
Note that this works with POSIXlt too, e.g.
seq(as.POSIXlt(Sys.Date()), length = 2, by = "month")[2]
mondate.
library(mondate)
now <- mondate(Sys.Date())
now + 1 # date in one month
now + 12 # date in 12 months
Mondate is bit smarter about things like mondate("2013-01-31")+ 1 which gives last day of February whereas seq(as.Date("2013-01-31"), length = 2, by = "month")[2] gives March 3rd.
yearmon If you don't really need the day part then yearmon may be preferable:
library(zoo)
now.ym <- yearmon(Sys.Date())
now.ym + 1/12 # add one month
now.ym + 1 # add one year
ADDED comment on POSIXlt and section on yearmon.
Here is you can add 1 month to a date in R, using package lubridate:
library(lubridate)
x <- as.POSIXlt("2010-01-31 01:00:00")
month(x) <- month(x) + 1
>x
[1] "2010-03-03 01:00:00 PST"
(note that it processed the addition correctly, as 31st of Feb doesn't exist).
Can you perhaps provide a reproducible example? What's in firstDate, and what version of R are you using? I do this kind of manipulation of POSIXlt dates quite often and it seems to work:
Sys.Date()
# [1] "2013-02-13"
date = as.POSIXlt(Sys.Date())
date$mon = date$mon + 1
as.Date(date)
# [1] "2013-03-13"