I think David was pointing out that reshape() is not a reshape2 function. It
is in the stats package.
I am not sure exactly what you are doing but perhaps something along the lines
of
library(reshape2)
mm <- melt(clim.data, id = Cs("yr_frac", "yr_mn", "AMO", "NINO34", "SSTA"))
is a start?
I also don't think that the more recent versions of ggplot2 automatically load
reshape2 so it may be that you are working with a relatively old installation
of ggplot and reshape?
sessionInfo()
R version 2.15.2 (2012-10-26)
Platform: i686-pc-linux-gnu (32-bit)
locale:
[1] LC_CTYPE=en_CA.UTF-8 LC_NUMERIC=C LC_TIME=en_CA.UTF-8
[4] LC_COLLATE=en_CA.UTF-8 LC_MONETARY=en_CA.UTF-8
LC_MESSAGES=en_CA.UTF-8
[7] LC_PAPER=C LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=en_CA.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] grid stats graphics grDevices utils datasets methods base
other attached packages:
[1] lubridate_1.2.0 directlabels_2.9 RColorBrewer_1.0-5 gridExtra_0.9.1
stringr_0.6.2
[6] scales_0.2.3 plyr_1.8 reshape2_1.2.1 ggplot2_0.9.3
loaded via a namespace (and not attached):
[1] colorspace_1.2-0 dichromat_1.2-4 digest_0.6.0 gtable_0.1.2
labeling_0.1
[6] MASS_7.3-22 munsell_0.4 proto_0.3-9.2 tools_2.15.2
John Kane
Kingston ON Canada
> -----Original Message-----
> From: natemille...@gmail.com
> Sent: Thu, 13 Dec 2012 09:58:34 -0800
> To: dwinsem...@comcast.net
> Subject: Re: [R] More efficient use of reshape?
>
> Sorry David,
>
> In my attempt to simplify example and just include the code I felt was
> necessary I left out the loading of ggplot2, which then imports reshape2,
> and which was actually used in the code I provided. Sorry to the mistake
> and my misunderstanding of where the reshape function was coming from.
> Should have checked that more carefully.
>
> Thanks,
> Nate
>
>
> On Thu, Dec 13, 2012 at 9:48 AM, David Winsemius
> <dwinsem...@comcast.net>wrote:
>
>>
>> On Dec 13, 2012, at 9:16 AM, Nathan Miller wrote:
>>
>> Hi all,
>>>
>>> I have played a bit with the "reshape" package and function along with
>>> "melt" and "cast", but I feel I still don't have a good handle on how
>>> to
>>> use them efficiently. Below I have included a application of "reshape"
>>> that
>>> is rather clunky and I'm hoping someone can offer advice on how to use
>>> reshape (or melt/cast) more efficiently.
>>>
>>>
>> You do realize that the 'reshape' function is _not_ in the reshape
>> package, right? And also that the reshape package has been superseded by
>> the reshape2 package?
>>
>> --
>> David.
>>
>>
>>> #For this example I am using climate change data available on-line
>>>
>>> file <- ("
>>> http://processtrends.com/**Files/RClimate_consol_temp_**anom_latest.csv<http://processtrends.com/Files/RClimate_consol_temp_anom_latest.csv>
>>> ")
>>> clim.data <- read.csv(file, header=TRUE)
>>>
>>> library(lubridate)
>>> library(reshape)
>>>
>>> #I've been playing with the lubridate package a bit to work with dates,
>>> but
>>> as the climate dataset only uses year and month I have
>>> #added a "day" to each entry in the "yr_mn" column and then used "dym"
>>> from
>>> lubridate to generate the POSIXlt formatted dates in
>>> #a new column clim.data$date
>>>
>>> clim.data$yr_mn<-paste("01", clim.data$yr_mn, sep="")
>>> clim.data$date<-dym(clim.data$**yr_mn)
>>>
>>> #Now to the reshape. The dataframe is in a wide format. The columns
>>> GISS,
>>> HAD, NOAA, RSS, and UAH are all different sources
>>> #from which the global temperature anomaly has been calculated since
>>> 1880
>>> (actually only 1978 for RSS and UAH). What I would like to
>>> #do is plot the temperature anomaly vs date and use ggplot to facet by
>>> the
>>> different data source (GISS, HAD, etc.). Thus I need the
>>> #data in long format with a date column, a temperature anomaly column,
>>> and
>>> a data source column. The code below works, but its
>>> #really very clunky and I'm sure I am not using these tools as
>>> efficiently
>>> as I can.
>>>
>>> #The varying=list(3:7) specifies the columns in the dataframe that
>>> corresponded to the sources (GISS, etc.), though then in the resulting
>>> #reshaped dataframe the sources are numbered 1-5, so I have to
>>> reassigned
>>> their names. In addition, the original dataframe has
>>> #additional data columns I do not want and so after reshaping I create
>>> another! dataframe with just the columns I need, and
>>> #then I have to rename them so that I can keep track of what everything
>>> is.
>>> Whew! Not the most elegant of code.
>>>
>>> d<-reshape(clim.data, varying=list(3:7),idvar="date"**,
>>> v.names="anomaly",direction="**long")
>>>
>>> d$time<-ifelse(d$time==1,"**GISS",d$time)
>>> d$time<-ifelse(d$time==2,"HAD"**,d$time)
>>> d$time<-ifelse(d$time==3,"**NOAA",d$time)
>>> d$time<-ifelse(d$time==4,"RSS"**,d$time)
>>> d$time<-ifelse(d$time==5,"UAH"**,d$time)
>>>
>>> new.data<-data.frame(d$date,d$**time,d$anomaly)
>>> names(new.data)<-c("date","**source","anomaly")
>>>
>>> I realize this is a mess, though it works. I think with just some help
>>> on
>>> how better to work this example I'll probably get over the learning
>>> hump
>>> and actually figure out how to use these data manipulation functions
>>> more
>>> cleanly.
>>>
>>> Any advice or assistance would be appreciated.
>>> Thanks,
>>> Nate
>>>
>>> [[alternative HTML version deleted]]
>>>
>>> ______________________________**________________
>>> R-help@r-project.org mailing list
>>> https://stat.ethz.ch/mailman/**listinfo/r-help<https://stat.ethz.ch/mailman/listinfo/r-help>
>>> PLEASE do read the posting guide http://www.R-project.org/**
>>> posting-guide.html <http://www.R-project.org/posting-guide.html>
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>
>> David Winsemius, MD
>> Alameda, CA, USA
>>
>>
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
____________________________________________________________
Receive Notifications of Incoming Messages
Easily monitor multiple email accounts & access them with a click.
Visit http://www.inbox.com/notifier and check it out!
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
