如何将此日期格式转换为 lubridate 接受的格式？

Question

I have imported data in R from an Excel sheet with package readxl.

The sheet contains a column with dates. These dates behave like dates in Excel (I can change the date formatting in Excel).

Directly after importing in R with readxl the format is this:

# A tibble: 1 x 1
  `datum`         
  <dttm>             
1 2010-01-20 21:00:00

My goal is to use the lubridate function days_in_month on the imported dates.

lubridate::days_in_month(df[2,1])

Although using this function gives this error:

Error in as.POSIXlt.default(x, tz = tz(x)) : 
  do not know how to convert 'x' to class “POSIXlt”

I did serveral test to identify the format:

is.Date(df[2,1])
is.POSIXt(df[2,1])
is.instant(df[2,1])

All give result FALSE.

If I print one date I receive this result:

# A tibble: 1 x 1
  `datum`         
  <dttm>             
1 2010-01-20 21:00:00

I have tried several conversions:

df$datum <- as.Date(df$datum, origin = "1899-12-30")
df$datum <- as.Date(as.POSIXct(df$datum, 'GMT'))
df$datum <- as.Date(df$datum, format='%Y-%m-%d')

Although the results of the tests above after conversion are all FALSE.

If I do the first conversion as.Date(df$datum, origin = "1899-12-30"). After this the outcome of print is:

# A tibble: 1 x 1
  `datum`
  <date>    
1 2010-01-20


df$datum + 60 gives:
1 2010-03-21

So it seems it is behaving as a date since I can add 60.

Although all the test give FALSE and days_in_month from lubridate still gives the error above.

How can I convert the date into a correct format which lubridate can process?

Thanks a lot!

Answer 1

You are being bitten by the differences in [ between data.frame and tbl_df . Reading your file (present in the comments), I ultimately see:

df <- readxl::read_excel("example dates.xlsx")
df
# # A tibble: 3 x 2
#   datum               datum2             
#   <dttm>              <dttm>             
# 1 2010-01-01 13:25:00 2010-12-22 23:53:40
# 2 2010-01-23 13:30:00 2011-01-07 23:09:10
# 3 2010-02-16 21:45:00 2011-03-19 01:00:52

# for everybody else
df <- structure(list(datum = structure(c(1262352300, 1264253400, 1266356700), class = c("POSIXct", "POSIXt"), tzone = "UTC"), datum2 = structure(c(1293062020.704, 1294441750.08, 1300496452.128), class = c("POSIXct", "POSIXt"), tzone = "UTC")), row.names = c(NA, -3L), class = c("tbl_df", "tbl", "data.frame"))

Can we agree that it does not make sense to try to convert a whole frame at once?

as.Date(df)
# Error in as.Date.default(df) : 
#   do not know how to convert 'df' to class "Date"

Dumb question. Well, let's see what happens with other variants.

df$datum
# [1] "2010-01-01 13:25:00 UTC" "2010-01-23 13:30:00 UTC" "2010-02-16 21:45:00 UTC"
as.Date(df$datum)
# [1] "2010-01-01" "2010-01-23" "2010-02-16"

df[2,1]
# # A tibble: 1 x 1
#   datum              
#   <dttm>             
# 1 2010-01-23 13:30:00
as.Date(df[2,1])
# Error in as.Date.default(df[2, 1]) : 
#   do not know how to convert 'df[2, 1]' to class "Date"

With a simple data.frame , [2,1] will return a scalar, not a frame, so that makes sense in base R:

as.data.frame(df)[2,1]
# [1] "2010-01-23 13:30:00 UTC"
as.Date(as.data.frame(df)[2,1])
# [1] "2010-01-23"

So the problem is that tibble is forcing you to be explicit in that you want to drop from a frame to a scalar/vector.

This is normally a good thing, frankly. When dealing with a "normal" (non- tibble ) frame and you want to look at a group of columns, as.data.frame(df[,1:2]) , R always returns a data.frame . Unfortunately, if you define the columns programmatically and it returns a single column, then [ by default reduces it from a frame to a vector: as.data.frame(df)[,1] . You can prevent this auto-coercion with drop= , ala as.data.frame(df[,1,drop=FALSE]) . Many (including myself) consider this to be a mistake: df[,cols] should be relied on to always return the same type of object, regardless if it is 20 columns or just 1 column. (I recognize that there are reasons why it does this, and I'm not berating the original R developers.)

So the problem causing your error is that tibble is requiring you to be explicit when subsetting your tbl_df into a single cell. If you want to work on a single cell, use df$datum[2] or df[2,1][[1]] to force it. If you want to work on a whole column, then df$datum . And all of those work directly with as.Date , since it knows how to deal with vectors of POSIXt (natively) and numeric / integer (along with origin= ). Unfortunately, df[,1] of a tibble will not return a vector, so as.Date does not know what to do with it.

Bottom line:

as.Date(df$datum[2])
# [1] "2010-01-23"
as.Date(df[2,1][[1]])
# [1] "2010-01-23"
as.Date(df$datum)
# [1] "2010-01-01" "2010-01-23" "2010-02-16"