I have a data frame that follows the below long Pattern:
Name MedName
Name1 atenolol 25mg
Name1 aspirin 81mg
Name1 sildenafil 100mg
Name2 atenolol 50mg
Name2 enalapril 20mg
And would like to get below (I do not care if I can get the columns to be named this way, just want the data in this format):
Name medication1 medication2 medication3
Name1 atenolol 25mg aspirin 81mg sildenafil 100mg
Name2 atenolol 50mg enalapril 20mg NA
Through this very site I have become familiarish with the reshape/reshape2 package, and have went through several attempts to try to get this to work but have thus far failed.
When I try dcast(dataframe, Name ~ MedName, value.var='MedName')
I just get a bunch of columns that are flags of the medication names (values that get transposed are 1 or 0) example:
Name atenolol 25mg aspirin 81mg
Name1 1 1
Name2 0 0
I also tried a dcast(dataset, Name ~ variable)
after I melted the dataset, however this just spits out the following (just counts how many meds each person has):
Name MedName
Name1 3
name2 2
Finally, I tried to melt the data and then reshape using idvar="Name"
timevar="variable"
(of which all just are Mednames), however this does not seem built for my issue since if there are multiple matches to the idvar, the reshape just takes the first MedName and ignores the rest.
Does anyone know how to do this using reshape or another R function? I realize that there probably is a way to do this in a more messy manner with some for loops and conditionals to basically split and re-paste the data, but I was hoping there was a more simple solution. Thank you so much!
@thelatemail's solution is similar to this one. When I generate the time variable, I use
rle
in case I'm not working interactively and theName
variable needs to be dynamic.Here's a shorter way, taking advantage of the way
unlist
deals with names:With the data.table package, this could easily be solved with the new
rowid
function:which gives:
Another method (commonly used before version 1.9.7):
giving the same result.
A similar approach, but now using the dplyr and tidyr packages:
which gives:
You could always generate a unique
timevar
before usingreshape
. Here I useave
to apply the functionseq_along
'along' each "Name".Result:
This seems to actually be a fairly common problem, so I have included a function called
getanID
in my "splitstackshape" package.Here's what it does:
Since "data.table" is loaded along with "splitstackshape", you have access to
dcast.data.table
, so you can proceed as with @mnel's example.The function essentially implements a
sequence(.N)
by the groups identified to create the "time" column.Assuming your data is in the object
dataset
: