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. For each package we have prepared a short introduction, so you … Continue reading Some Win-Vector R packages
sigr is a simple R package that conveniently formats a few statistics and their significance tests. This allows the analyst to use the correct test no matter what modeling package or procedure they use. Model Example Let’s take as our example the following linear relation between x and y: library('sigr') set.seed(353525) d <- data.frame(x= rnorm(5)) … Continue reading sigr: Simple Significance Reporting
In this screencast we demonstrate how to easily and effectively step-debug magrittr/dplyr pipelines in R using wrapr and replyr. Some of the big issues in trying to debug magrittr/dplyr pipelines include: Pipelines being large expressions that are hard to line-step into. Visibility of intermediate results. Localizing operations (in time and code position) in the presence … Continue reading Step-Debugging magrittr/dplyr Pipelines in R with wrapr and replyr
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 … Continue reading replyr: Get a Grip on Big Data in R
This article is on preparing data for modeling in R using vtreat. Our example Suppose we wish to work with some data. Our example task is to train a classification model for credit approval using the ranger implementation of the random forests method. We will take our data from John Ross Quinlan's re-processed "credit approval" … Continue reading vtreat: prepare data
This article is on writing sweet R code using the wrapr package. The problem Consider the following R puzzle. You are given: a data.frame, the name of a column that you wish to find missing values (NA) in, and the name of a column to land the result. For instance: d <- data.frame(x = c(1, … Continue reading wrapr: for sweet R code
I recently read an interesting thread on unexpected behavior in R when creating a list of functions in a loop or iteration. The issue is solved, but I am going to take the liberty to try and re-state and slow down the discussion of the problem (and fix) for clarity. The issue is: are references … Continue reading Iteration and closures in R
I am going to write about an insidious statistical, data analysis, and presentation fallacy I call “the zero bug” and the habits you need to cultivate to avoid it. The zero bug Here is the zero bug in a nutshell: common data aggregation tools often can not “count to zero” from examples, and this causes … Continue reading The Zero Bug
Recently Dirk Eddelbuettel pointed out that our R function debugging wrappers would be more convenient if they were available in a low-dependency micro package dedicated to little else. Dirk is a very smart person, and like most R users we are deeply in his debt; so we (Nina Zumel and myself) listened and immediately moved … Continue reading Announcing the wrapr packge for R
I want to share an edited screencast of my rehearsal for my recent San Francisco Bay Area R Users Group talk:
