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.
Related
I have loaded in time series data of creek depth and am needing to calculate total annual values (Oct-April) for each year. The following is what I have tried thus far:
depth <- read_csv("Depth.Water_Depth-_All_Instruments#GCNP_-_Robber's_Roost_Spring.EntireRecord .csv")
The following is a screenshot of the resulting data frame
enter image description here
These are my attempts at making the timestamp column (ISO_UTC) into a date class. Although, each attempt makes all values for ISO_UTC into N/A values instead of dates / times.
ymd_hm(depth$ISO_UTC)
depth$ISO_UTC<- as.Date(depth$ISO_UTC, format = "%Y-%m-%dT%H:%M")
depth$ISO_UTC<- as.POSIXct(depth$ISO_UTC, format = "%Y-%m-%d %H:%M", tz = "US/Pacific")
Please help me to put these data into usable datetime values.
Please see the above details.
Newbie here, first post (please be gentle). I have been trying to resolve this for several hours, so finally decided time to ask advice.
I have a large spreadsheet which I am importing with readxl. It contains one column with date (format dd/mm/yyyy) and several time columns in format hh:mm as can be seen: excel
Essentially I want to be able to import both time and date columns and combine them, so that I can then do some other calculations, like time elapsed.
If I import letting R guess the col-types, it converts the times to POSIXct, but these then have a date on 1899 attached to them: R_POSIXct
If I force readxl to assign the time column to numeric, I get a decimal (e.g. 0.315972222 for 07:35), which then tried converting using similar syntax to
format(as.POSIXct(Sys.Date() + 0.315972222), "%Y-%m-%d %H:%M:%S", tz="UTC")
i.e.
df$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 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.
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.
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") })