This is a note on debugging `magrittr`

pipelines in `R`

using Bizarro Pipe and eager assignment.

# Tag: R

## Datashader is a big deal

I recently got back from Strata West 2017 (where I ran a very well received workshop on `R`

and `Spark`

). One thing that really stood out for me at the exhibition hall was `Bokeh`

plus `datashader`

from Continuum Analytics.

I had the privilege of having Peter Wang himself demonstrate `datashader`

for me and answer a few of my questions.

I am so excited about `datashader`

capabilities I literally *will not wait* for the functionality to be exposed in `R`

through `rbokeh`

. I am going to leave my usual `knitr`

/`rmarkdown`

world and dust off `Jupyter Notebook`

just to use `datashader`

plotting. This is worth trying, even for diehard `R`

users. Continue reading Datashader is a big deal

## Practical Data Science with R: ACM SIGACT News Book Review and Discount!

Our book Practical Data Science with R has just been reviewed in Association for Computing Machinery Special Interest Group on Algorithms and Computation Theory (ACM SIGACT) News by Dr. Allan M. Miller (U.C. Berkeley)!

The book is half off at Manning March 21st 2017 using the following code (please share/Tweet):

Deal of the Day March 21: Half off my book Practical Data Science with R. Use code

`dotd032117au`

at https://www.manning.com/dotd

Please read on for links and excerpts from the review. Continue reading Practical Data Science with R: ACM SIGACT News Book Review and Discount!

## Another R [Non-]Standard Evaluation Idea

Jonathan Carroll had a an interesting `R`

language idea: to use `@`

-notation to request value substitution in a non-standard evaluation environment (inspired by msyql User-Defined Variables).

He even picked the right image:

## New screencast: using R and RStudio to install and experiment with Apache Spark

I have new short screencast up: using R and RStudio to install and experiment with Apache Spark.

More material from my recent Strata workshop Modeling big data with R, sparklyr, and Apache Spark can be found here.

## Practical Data Science with R errata update: Java SQLScrewdriver replaced by R procedures and article

We have updated the errata for Practical Data Science with R to reflect that it is no longer worth the effort to use the Java version of SQLScrewdriver as described.

We are very sorry for any confusion, trouble, or wasted effort bringing in Java software (something we are very familiar with, but forget not everybody uses) has caused readers. Also, database adapters for R have greatly improved, so we feel more confident depending on them alone. Practical Data Science with R remains an excellent book and a good resource to learn from that we are very proud of and fully support (hence errata). Continue reading Practical Data Science with R errata update: Java SQLScrewdriver replaced by R procedures and article

## Some Win-Vector R packages

This post concludes our mini-series of Win-Vector open source `R`

packages. We end with `WVPlots`

, a collection of ready-made `ggplot2`

plots we find handy.

Please read on for list of some of the Win-Vector LLC open-source R packages that we are pleased to share. Continue reading Some Win-Vector R packages

## sigr: Simple Significance Reporting

## Step-Debugging magrittr/dplyr Pipelines in R with wrapr and replyr

In this screencast we demonstrate how to easily and effectively step-debug magrittr/dplyr pipelines in R using wrapr and replyr.

## replyr: Get a Grip on Big Data in R

`replyr`

is an `R`

package that contains extensions, adaptions, and work-arounds to make remote `R`

`dplyr`

data sources (including big data systems such as `Spark`

) behave more like local data. This allows the analyst to more easily develop and debug procedures that simultaneously work on a variety of data services (in-memory `data.frame`

, `SQLite`

, `PostgreSQL`

, and `Spark2`

currently being the primary supported platforms).