I am attempting to convert a column in my data set from fctr to date format. The current column has data formatted as follows: "01/01/14. 01:00 Am." Ideally I would like to create a column for day and then a column for time as well. There are periods following the day and the time which is another issue I am facing. So far I have attempted to use lubridate to create a new column of data but I get the error "All formats failed to parse. No formats found." Any help would be greatly appreciated, thank you.
test <- fourteen %>%
mutate(When = mdy_hms(V3))
View(test)
If your date factor literally has levels that look like 01/01/14. 01:00 Am. including two periods and a space between the first period and the first hour digits and a space between the minutes and the am/pm designation, and all the dates are in this format, then the following should work:
... mutate(When = as.POSIXct(V3, format="%m/%d/%y. %H:%M %p.")) ...
In particular, the following standalone testcase works fine:
as.POSIXct(factor("01/01/14. 01:00 Am."), format="%m/%d/%y. %H:%M %p.")
For more information on the format argument being used here, see the R help page for the function strftime.
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I haven't found an answer that works for me yet. I have data that has observations on a 5 minute basis. I have start and end time columns named (creatively) STARTTIME and ENDTIME. I read.csv the data into R. When I do the STARTTIME and ENDTIME are treated as factors. The "cells" in the data frame are populated with date time values such as "7/2/2016 11:25:00 PM". So, I tried the following:
df$STARTTIME <- as.POSIXct(as.character(df$STARTTIME), format = "%m%d%Y %I:%M:%S %p", tz ="EST")
When I run that code the whole column is replaced with NA. Any Help is appreciated.
Newbie here, first post (please be gentle). I have been trying to resolve this for several hours, so finally decided time to ask advice.
I have a large spreadsheet which I am importing with readxl. It contains one column with date (format dd/mm/yyyy) and several time columns in format hh:mm as can be seen: excel
Essentially I want to be able to import both time and date columns and combine them, so that I can then do some other calculations, like time elapsed.
If I import letting R guess the col-types, it converts the times to POSIXct, but these then have a date on 1899 attached to them: R_POSIXct
If I force readxl to assign the time column to numeric, I get a decimal (e.g. 0.315972222 for 07:35), which then tried converting using similar syntax to
format(as.POSIXct(Sys.Date() + 0.315972222), "%Y-%m-%d %H:%M:%S", tz="UTC")
i.e.
df$datetime <- format(as.POSIXct(df$date + df$time), "%Y-%m-%d %H:%M", tz="UTC")
which results in the correct date, but with a time of 00:00, not the time it is passed.
I have tried searching here and found posts to be not quite the same question (e.g. Combining date and time columns into dd/mm/yyyy hh:mm), and have read widely, including about about lubridate, but as I'm only 6 months into R, am finding some explanations a bit cryptic.
Suggestions or ignposting appreciated (if there are solutions I haven't found)
If you subtract the number of days between 1899-01-01 and 1970-01-01 and then multiply that (shifted) Excel numeric value by 3600 you should come close to the number of seconds since start of 1970. You could then convert to POSIXct with as.POSIXct( x, origin="1970-01-01"). That does seem to be "the hard way", however
It would be far easier and probably more accurate to convert the date-times to YYYY-MM-DD H:M:S format and then export as csv to be imported into R as text. There is a "POSIXct" colClasses argument to read.csv, although it doesn't handle separate columns of date and time. For that you would be advised to import as character values and then paste the dates and times. Then watch you format strings for as.POSIXct. The dd/mm/yyyy "format" would be specified by "%d/%m/%Y".
I want to split up a Timestamp from Excel into year and julian day. I know, duplicate question, but combining everything I have found from other questions is not helping me.
The timestamp is formatted 1/13/2011 13:55 . So, I wanted to tell R to recognize this as a time variable. I have hours and minutes so I tried as.POSIXct and as.POSIXlt. These didn't work. I tried adding strptime --
as.POSIXct(strptime(df$TIMESTAMP, "%d/%m/%Y %H:%M%S"))
I just got NAs.
Once I got R to recognize it as a date, I was going to use lubridate like day(df$Date).
It seems as though you have month and day reversed
1/13/2011 13:55
with
"%d/%m/%Y %H:%M%S"
corresponds to the 1st day of the 13th month, which is probably why you're getting NAs. This seems to work for me:
a <- "01/13/2011 13:55"
t <- strptime(a, "%m/%d/%Y %H:%M")
t
"2011-01-13 13:55:00"
I've been trying to do a time series on my dataframe, and I need to strip times from my csv. This is what I've got:
campbell <-read.csv("campbell.csv")
campbell$date = strptime(campbell$date, "%m/%d")
campbell.ts <- xts(campbell[,-1],order.by=campbell[,1])
First, what I'm trying to do is just get xts to strip the dates as "xx/xx" meaning just the month and day. I have no year for my data. When I try that second line of code and call upon the date column, it converts it to "2013-xx-xx." These months and days have no year associated with them, and I can't figure out how to get rid of the 2013. (The csv file I'm calling on has the dates in the format "9/30,10/1...etc.)
Secondly, once I try and make a time series (the third line), I am unsure what the "order.by" command is calling on. What am I indexing?
Any help??
Thanks!
For strptime, you need to provide the full date, i.e. day, month and year. In case, any of these is not provided, current ones are assumed from the system's time and appended to the incomplete date. So, if you want to retain your date format as you have read it, first make a copy of that and store in a temporary variable and then use strptime over campbell$date to convert into R readable date format. Since, year is not a concern to you, you need not bother about it even though it is automatically appended by strptime.
campbell <-read.csv("campbell.csv")
date <- campbell$date
campbell$date <- strptime(campbell$date, "%m/%d")
Secondly, what you are doing by 'the third line' (xts(campbell[,-1],order.by=campbell[,1])) command is that, your are telling to order all the data of campbell except the first column (campbell[,-1]) according to the index provided by the time data in the first column of campbell (campbell[,1]). So, it would only work given the date is in the first column.
After ordering the data according to time-series, you can replace back the campbell$date column with date to get back the date format you wanted (although here, first you have to order date also like shown below)
date <- xts(date, order.by=campbell[,1]) # assuming campbell$date is campbell[,1]
campbell.ts <- xts(campbell[,-1], order.by=campbell[,1])
campbell.ts <- cbind(date, campbell.ts)
format(as.Date(campbell$dat, "%m/%d/%Y"), "%m/%d")
I am running into some date issues when working with Dates in R.
Here's my situation-
I have a data set based on dates and finally got the Date field converted from character to Date in R using the following code
o1$Date <- as.Date(o1$Date , "%m/%d/%y")
(My dataset is o1 and Date is the name of my Date column)
My Date column has the following values
"1/1/2013" "1/1/2014" "1/10/2013" "1/10/2014" "1/11/2013" "1/11/2014"
However when I convert the Char to Date I get the following Dates
"2020-01-01" "2020-01-01" "2020-01-10" "2020-01-10" "2020-01-11"
Any suggestions on what the problem could be and how to work around it?
look at ?strptime to see the formatting options for times and dates. You need to use %Y rather than %y which is for a 2 digit year.