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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