search for: array2df

I have a file, each column of which is a separate year, and each row of each column is mean precipitation for that month. Looks like this (except it goes back to 1964). month X2000 X2001 X2002 X2003 X2004 X2005 X2006 X2007 X2008 X2009 1 1.600 1.010 4.320 2.110 0.925 3.275 3.460 0.675 1.315 2.920 2 2.960 3.905 3.230 2.380 2.720 1.880 2.430 1.380

Hi, I have a three dimensional array, e.g., my.array = array(0, dim=c(2,3,4), dimnames=list( d1=c("A1","A2"), d2=c("B1","B2","B3"), d3=c("C1","C2","C3","C4")) ) what I would like to get is then a dataframe: d1 d2 d3 value A1 B1 C1 0 A2 B1 C1 0 . . . A2 B3 C4 0 I'm sure there is one function to do

...PR#18503 and discussants, prompted by a report from Toby Dylan Hocking on the R-devel mailing list.) * The matrix multiply operator %*% is now an S3 generic, belonging to new group generic matrixOps. From Tomasz Kalinowski's contribution in PR#18483. * New function array2DF() to convert arrays to data frames, particularly useful for the list arrays created by tapply(). DATES and TIMES: * On platforms where (non-UTC) datetimes before 1902 (or before 1900 as with system functions on recent macOS) are guessed by extrapolating time zones from 190...

...PR#18503 and discussants, prompted by a report from Toby Dylan Hocking on the R-devel mailing list.) * The matrix multiply operator %*% is now an S3 generic, belonging to new group generic matrixOps. From Tomasz Kalinowski's contribution in PR#18483. * New function array2DF() to convert arrays to data frames, particularly useful for the list arrays created by tapply(). DATES and TIMES: * On platforms where (non-UTC) datetimes before 1902 (or before 1900 as with system functions on recent macOS) are guessed by extrapolating time zones from 190...