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
plyr
anddplyr
in the same session.dplyr
andplyr
are conflict the following objects:arrange, count, desc, failwith, id, mutate, rename, summarise, summarize