There is this great example of how to use ggplot2 to create a heat map the 'R; way: Rheatmap which provides a link to the raw data and the source code.
There was a followup using ggplot2: ggplot2 which lays out the ggplot2 code.
At key points the ggplot2 code uses reshape2 and plyr.
nba.m <- melt(nba)
nba.m <- ddply(nba.m, .(variable), transform,rescale = rescale(value))
My goal is to duplicate these calculations using tidyr and dplyr.
 nba.m <- melt(nba)
has a tidyr equivalent in:
 nba.g <- gather(nba, Name) 
What is the dplyr equivalent to this line?
nba.m <- ddply(nba.m, .(variable), transform,rescale = rescale(value))
eipi10 kindly suggested
nba.m2 <- nba.m %>%group_by(Name) %>% mutate(rescale=rescale(value))
However, it looks like the rescale calculation is not occuring in quite the same way:
> head(nba.m)
        Name variable value   rescale
1   Dwyane Wade         G    79 0.9473684
2  LeBron James         G    81 0.9824561
3   Kobe Bryant         G    82 1.0000000
4 Dirk Nowitzki         G    81 0.9824561
5 Danny Granger         G    67 0.7368421
6  Kevin Durant         G    74 0.8596491
> head(nba.m2)
Source: local data frame [6 x 4]
Groups: Name
        Name Name.1 value   rescale
1   Dwyane Wade       G    79 0.9634146
2  LeBron James       G    81 0.9878049
3   Kobe Bryant       G    82 1.0000000
4 Dirk Nowitzki       G    81 0.9878049
5 Danny Granger       G    67 0.8170732
6  Kevin Durant       G    74 0.9024390
> 
What is missing?
Thanks, Matt
 
                        
I think you need write
dplyr::mutate, notmutate.I presume you loaded
plyranddplyrin the same session.dplyrandplyrare conflict the following objects:arrange, count, desc, failwith, id, mutate, rename, summarise, summarize