aggregate(), tapply(), do.call(), rbind() (etc.) are extremely useful
functions that have been available in R for a long time. They remain
useful regardless what plotting approach you use - base graphics,
lattice or the more recent ggplot.
Philip
On 22/02/2017 8:40 AM, C W wrote:
Hi Carl,
I have not fully learned dplyr, but it seems harder than tapply() and the
?apply() family in general.
Almost every ggplot2 data I have seen is manipulated using dplyr. Something
must be good about dplyr.
aggregate(), tapply(), do.call(), rbind() will be sorely missed! :(
Thanks!
On Tue, Feb 21, 2017 at 4:21 PM, Carl Sutton<suttonc...@ymail.com> wrote:
Hi
I have found that:
A) Hadley's new book to be wonderful on how to use dplyr, ggplot2 and his
other packages. Read this and using as a reference saves major frustration.
b) Data Camps courses on ggplot2 are also wonderful. GGPLOT2 has more
capability than I have mastered or needed. To be an expert with ggplot2
will take some effort. To just get run of the mill helpful, beautiful
plots, no major time needed for that.
I use both of these sources regularly, especially when what is in my grey
matter memory banks is not working. Refreshers are sometimes needed.
If your data sets are large and available memory limited, then data.table
is the package I use. I am amazed at the difference of memory usage with
data.table versus other packages. My laptop has 16gb ram, and tidyr maxed
it but data.table melt used less than 6gb(if I remember correctly) on my
current work. Since discovering fread and fwrite, read.table, read.csv,
and write have been benched. Every script I have includes
library(data.table)
Carl Sutton
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