[R] Confused about using data.table package,

P Tennant philipt900 at iinet.net.au
Tue Feb 21 22:47:00 CET 2017

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.


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<suttoncarl at 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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