I am relatively new to R and I have a dataset in which I am trying to convert a date and time into a numeric value. The date and time are in the format 01JUN17:00:00:00 under a variable called pickup_datetime. I have tried using the code
cab_small_sample$pickup_datetime <- as.numeric(as.Date(cab_small_sample$pickup_datetime, format = '%d%b%y'))
but this way doesn't incorporate time, I tried to add the time format to the format section of code but still did not work. Is there an R function that will convert the data into a numeric value>
R has two main time classes: "Date" and "POSIXct". POSIXct is a datetime class and you can get all the gory details at: ? DateTimeClasses. The help page for the formats used at the time of data input, however, are at ?striptime.
cab_small_sample <- data.frame(pickup_datetime = "01JUN17:00:00:00")
cab_small_sample$pickup_dt <- as.numeric(as.POSIXct(cab_small_sample$pickup_datetime,
format = '%d%b%y:%H:%M:%S'))
cab_small_sample
# pickup_datetime pickup_dt
#1 01JUN17:00:00:00 1496300400 # seconds since 1970-01-01
I find that a "destructive reassignment of values" is generally a bad idea so as a "my (best?) practice rule" I don't assign to the same column until I'm sure I have the code working properly. (And I always leave an untouched copy somewhere safe.)
lubridate is an extremely handy package for dealing with dates. It includes a variety of functions which do the date/time parsing for you, as long as you can provide the order of components. In this case, since your data is in day-month-year-hms form, you can use the dmy_hms function.
library(lubridate)
cab_small_sample <- dplyr::tibble(
pickup_datetime = c("01JUN17:00:00:00", "01JUN17:11:00:00"))
cab_small_sample$pickup_POSIX <- dmy_hms(cab_small_sample$pickup_datetime)
Related
I have data below for work hours which I need to compare - start and stop with date and time. I first extract the time portion of each as start and stop variables, then use the chron package to change them from factor data to something I can compare more easily.
require(chron)
eg_data3 <- data.frame(
id = c('42', '42', '42', '42', '42'),
time_in = as.factor(c('11/5/2017 13:52', '11/4/2017 14:25', '11/5/2017 15:30', '11/5/2017 17:10', '11/6/2017 18:20')),
time_out = as.factor(c('11/5/2017 13:59', '11/4/2017 14:59', '11/5/2017 16:00', '11/5/2017 17:45', '11/6/2017 18:50')))
eg_data3$start_time <- substring(strptime(eg_data3$time_in, format = "%m/%d/%Y %H:%M"),12,19)
eg_data3$end_time <- substring(strptime(eg_data3$time_out, format = "%m/%d/%Y %H:%M"),12,19)
eg_data3$end_time <- chron(times = eg_data3$end_time)
eg_data3$start_time <- chron(times = eg_data3$start_time)
Next, I generate another variable which compares the difference between stop time 1, and start time 2, IE stop time in row 1 with start time in row 2, to see the gap between them.
require(dplyr)
eg_data3 <- eg_data3 %>% group_by(id) %>% mutate(diff_outX0_inX1 = start_time - lag(end_time))
When I do this, the variable is formatted as a decimal. I cannot for the life of me get it to display as hh:mm:ss. I have tried specifying out.format as hh:mm:ss in chron, changing time_in / time_out to numeric and character before and after extraction and applying chron(times), changing the format of the diff_ variable after, etc.
What seems like a very simple question -
How do I get the result comparison (diff_outX0_inX1) variable to display as time, either hh:mm or hh:mm:ss ?? I know the formula to convert fractional days into minutes in Excel, but I'd prefer to not write out a two step function, I assume it's a simple formatting issue.
Any help is appreciated.
EDIT - got flagged as a duplicate...OK. I asked if there was a way to do this that did not involve writing a function. The answer that was linked involves a function. First comment provided a clean simple answer. I can reproduce the answer in the comment, I could not reproduce the function myself, not nearly as helpful. I also added another solution that does not requre dplyr. No where I looked online showed me something as simple as "just format the result with chron."
I'm trying to make a timeline like you'd make with any of the timevis, vistime, or timeline R packages, but I'm only interested in times and not dates. I don't mind putting a placeholder date in there, but it seems that all of these packages require the start and end times to include dates and include the date in the timeline.
I've been searching for ways to either not include dates in a timeline or only print the time but not the date in any of these package, but haven't been able to find anything. Does anyone have any ideas?
All of those packages use as.POSIXct under the hood, which requires objects to be Date objects and doesn't work with times only. So, if your data is about only one day, you can add the date on the clock times (using paste) and e.g. vistime will display only the time (ok, a date almost completely hidden in the corner):
dat <- data.frame(event = 1:2,
start = c("14:00", "16:00"),
end = c("15:30", "17:00"))
# add a Date
dat[,c("start", "end")] <- sapply(dat[,c("start", "end")], function(x) paste(Sys.Date(), x))
vistime(dat)
I use vistime version 0.7.0.9000 which can be obtained by executing devtools::install_github("shosaco/vistime").
If you want to represent times without any date information, you should try out the package hms. It is part of the tidyverse collection and is described as:
A simple class for storing durations or time-of-day values and displaying them in the hh:mm:ss format.
Example use:
library(hms)
hms(56, 34, 12)
#> 12:34:56
I have dates in the following formats:
08MAR1978:00:00:00
10FEB1973:00:00:00
15AUG1982:00:00:00
I would like to convert them to:
1978-03-08
1973-02-10
1982-09-15
I have tried the following in SparkR:
period_uts <- unix_timestamp(all.new$DATE_OF_BIRTH, '%d%b%Y:%H:%M:%S')
period_ts <- cast(period_uts, 'timestamp')
period_dt <- cast(period_ts, 'date')
df <- withColumn(all.new, 'p_dt', period_dt)
But when I do this, all the dates get changed into "NA".
Can anyone please provide some insights on how I can convert dates in %d%B%Y:%H:%M:%S format to dates in SparkR?
Thanks!
I don't think you need SparkR to solve this question.
What you have:
DoB <- c("08MAR1978:00:00:00", "10FEB1973:00:00:00", "15AUG1982:00:00:00")
If you want to get 1978-03-08 etc. you could just use as.Date in combination with the date format you already found yourself:
as.Date(DoB, format="%d%B%Y:%H:%M:%S")
# [1] "1978-03-08" "1973-02-10" "1982-08-15"
as.Date will ensure that R knows how to interpret your string as a date.
Note, however, that in general the way dates are displayed to you (i.e. 1978-03-08) actually don't really matter. The reason is that 'under the hood', R understands your date now, so all date-related operations will be performed appropriately.
I figured out how to do it:
all.new = all.new %>% withColumn("Date_of_Birth_Fixed", to_date(.$DATE_OF_BIRTH, "ddMMMyyyy"))
This works in Spark 2.2.x
I have date format in following format in a data frame:
Jan-85
Apr-99
1-Nov
Feb-96
When I see the typeof(df$col) I get the answer as "integer".
Actually when I see the format in excel it is in m/d/yyyy format. I was trying to convert this to date format in R. All my efforts yielded NA.
I tried parse_date_time function. I tried as.date along with as.character. I tried as.POSIXct but everything is giving me NA.
My trials were as follows and everything was a failure:
as.Date.numeric(df$col,"m%d%Y")
transform(df$col, as.Date(as.character(df$col), "%m%d%Y"))
as.Date(df$col,"m%d%Y")
as.POSIXct.numeric(as.character(loan_new$issue_d), format="%Y%m%d")
as.POSIXct.date(as.character(df$col), format="%Y%m%d")
mdy(df$col)
parse_date_time(df$col,c("mdy"))
How can I convert this to date format? I have used lubridate package for parse_date_time and mdy package.
dput output is below
Label <- factor(c("Apr-08",
"Apr-09", "Apr-10", "Apr-11", "Aug-07", "Aug-08", "Aug-09", "Aug-10",
"Aug-11", "Dec-07", "Dec-08", "Dec-09", "Dec-10", "Dec-11", "Feb-08",
"Feb-09", "Feb-10", "Feb-11", "Jan-08", "Jan-09", "Jan-10", "Jan-11",
"Jul-07", "Jul-08", "Jul-09", "Jul-10", "Jul-11", "Jun-07", "Jun-08",
"Jun-09", "Jun-10", "Jun-11", "Mar-08", "Mar-09", "Mar-10", "Mar-11",
"May-08", "May-09", "May-10", "May-11", "Nov-07", "Nov-08", "Nov-09",
"Nov-10", "Nov-11", "Oct-07", "Oct-08", "Oct-09", "Oct-10", "Oct-11",
"Sep-07", "Sep-08", "Sep-09", "Sep-10", "Sep-11"))
NA is typically what you get when you misspecify the format. Which is what you do. That said, if your data is really looking like the first example you gave, it's impossible to simply convert this to a date. You have two different formats, one being month-year and the other day-month.
If your updated date (i.e. Dec-11) is the correct format, then you use the format argument of as.Date like this:
date <- "Dec-11"
as.Date(date, format = "%b-%d")
# [1] "2017-12-11"
Or on your example data:
as.Date(Label, format = "%b-%d")
# [1] "2017-04-08" "2017-04-09" "2017-04-10" "2017-04-11" "2017-08-07" "2017-08-08"
# [7] "2017-08-09" "2017-08-10" "2017-08-11" "2017-12-07" "2017-12-08" "2017-12-09"
If you want to convert something like Jan-85, you have to decide which day of the month that date should have. Say we just take the first of each month, then you can do:
x <- "Jan-85"
xd <- paste0("1-",x)
as.Date(xd, "%d-%b-%y")
# [1] "1985-01-01"
More information on the format codes can be found on ?strptime
Note that R will automatically add this year as the year. It has to, otherwise it can't specify the date. In case you do not have a day of the month (eg like Jan-85), conversion to a date is impossible because the underlying POSIX algorithms don't have all necessary information.
Also keep in mind that this only works when your locale is set to english. Otherwise you have a big chance your OS won't recognize the month abbreviations correctly. To do so, do eg:
Sys.setlocale(category = "LC_TIME", locale = "English_United Kingdom")
You can later set it back to the original one if you must, or restart your R session to reset the locale settings.
note: Please check carefully which locale notations are valid for your OS. The above example works on Windows, but is not guaranteed on either Linux or Mac.
Why you see integer
The fact that these string values are of integer type, is due to the fact that R automatically convert character vectors to factors when reading in a data frame. So typeof() returns integer because that's the internal representation of a factor.
I have a dataset with some date time like this "{datetime:2015-07-01 09:10:00" So I wanted to remove the text, and then keep the date & the time as as.Date returns only the date. So I write this code but the only problem I have is that during the second line with strsplit, it only returns me the date time of the first line and so erase the others... I woud love to get ALL my date time not only the first. I thought about sapply maybe, but I can't make it right I have many errors or maybe with a loop for? I am novice to R so I don't really know how to do this the best way.
Could you help me please? Besides If you have another idea for the time & date format or a simple way to do it, it should be very nice of you too.
data$`Date Time`=as.character(data$`Date Time`)
data$`Date Time`=unlist(strsplit(data[,1], split='e:'))[2]
date=substr(data$`Date Time`,0,10)
date=as.Date(date)
time=substr(data$`Date Time`,12,19)
data$Date=date
data$Time=time
Thank you very much for your help!
You could use the format argument to avoid all the strsplit:
times <- as.POSIXct(data$`Date Time`, format='{datetime:%Y-%m-%d %H:%M:%S')
(The reason for the "{datetime:" in the format is because you mentioned this is the format of your strings).
This object has both date and time in it, and then you can just store it in the dataframe as a single column of type POSIXct rather than two columns of type string e.g.
data$datetime <- times
but if you do want to store the date as a Date and the time as a string (as in your example above):
data$Date <- as.Date(times)
data$Time <- strftime(times, format='%H:%M:%S')
See ?as.Date, ?as.POSIXct, ?strptime for more details on that format argument and various conversions between date and string.