R Tip: Use match_order() to Align Data
RTools & Languagesposted by John Mount April 20, 2018
R tip. Use wrapr::match_order() to align data. Suppose we have data in two data frames, and both of these data frames have common row-identifying columns called “idx“. library("wrapr") d1 <- build_frame( "idx", "x" | 3 , "a" | 1 , "b" | 2 , "c" ) d2 <- build_frame( "idx", "y" |... Read more
Laminar flow with ggplot2 and gganimate
RToolsTools & Languagesposted by Eugene Joh April 17, 2018
Preface I’ve realized that all my previous posts were quite substantial in length and took quite a long time to create them. From this point forward I’ll be generating posts of shorter length (partially for my sanity and more for my impulsivity with ideas). A few of these posts won’t be... Read more
R Tip: Use let() to Re-Map Names
RTools & Languagesposted by John Mount April 13, 2018
Another R tip. Need to replace a name in some R code or make R code re-usable? Use wrapr::let(). Here is an example involving dplyr. Let’s look at some example data: library("dplyr") library("wrapr") starwars %>% select(., name, homeworld, species) %>% head(.) # # A tibble: 6 x 3 # name homeworld species #... Read more
Using Excel for Data Entry
RToolsTools & Languagesposted by Bob Muenchen April 11, 2018
This article shows you how to enter data so that you can easily open in statistics packages such as R, SAS, SPSS, or jamovi (code or GUI steps below). Excel has some statistical analysis capabilities, but they often provide incorrect answers. For a comprehensive list of these limitations, see http://www.forecastingprinciples.com/paperpdf/McCullough.pdfand http://www.burns-stat.com/documents/tutorials/spreadsheet-addiction. Simple Data... Read more
R Tip: Use let() to Re-Map Names
RTools & Languagesposted by John Mount April 6, 2018
Another Rtip. Need to replace a name in some R code or make R code re-usable? Use wrapr::let(). Here is an example involving dplyr. Let’s look at some example data: library("dplyr") library("wrapr") starwars %>% select(., name, homeworld, species) %>% head(.) # # A tibble: 6 x 3 # name homeworld species #... Read more
R Tip: Break up Function Nesting for Legibility
RTools & LanguagesProgramming Language|Rposted by John Mount March 30, 2018
There are a number of easy ways to avoid illegible code nesting problems in R. In this R tip we will expand upon the above statement with a simple example. At some point it becomes illegible and undesirable to compose operations by nesting them, such as in the following code. head(mtcars[with(mtcars, cyl... Read more
R Tip: Use stringsAsFactors = FALSE
RTools & Languagesposted by John Mount March 27, 2018
R tip: use stringsAsFactors = FALSE. R often uses a concept of factors to re-encode strings. This can be too early and too aggressive. Sometimes a string is just a string. It is often claimed Sigmund Freud said “Sometimes a cigar is just a cigar.” To avoid problems delay re-encoding of strings... Read more
R Tip: Use the vtreat Package For Data Preparation
RTools & Languagesposted by John Mount March 21, 2018
If you are working with predictive modeling or machine learning in Rthis is the R tip that is going to save you the most time and deliver the biggest improvement in your results. R Tip: Use the vtreat package for data preparation in predictive analytics and machine learning projects. When attempting predictive modeling with real-world data you quicklyrun into difficulties beyond... Read more
jamovi for R: Easy but Controversial
RTools & Languagesposted by Bob Muenchen March 20, 2018
jamovi is software that aims to simplify two aspects of using R. It offers a point-and-click graphical user interface (GUI). It also provides functions that combines the capabilities of many others, bringing a more SPSS- or SAS-like method of programming to R. The ideal researcher would be an expert at... Read more
EXPLORATORY ANALYSIS – WHEN TO CHOOSE R, PYTHON, TABLEAU OR A COMBINATION
PlatformsPythonRTools & LanguagesData Science|Data Visualization|Programming Language|Python|Rposted by Scott Stoltzman March 14, 2018
Not all data analysis tools are created equal. Recently, I started looking into data sets to compete in Go Code Colorado (check it out if you live in CO). The problem with such diversity in data sets is finding a way to quickly visualize the data and do exploratory analysis. While... Read more
