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2 Visualizations

2 Visualizations...

Editor’s note: This is the second of a series of posts on the caret package. The featurePlot function is a wrapper for different lattice plots to visualize the data. For example, the following figures show the default plot for continuous outcomes generated using the featurePlotfunction. For classification data sets, the iris data are used for illustration. […]

Decrypt Emotion with our Web App…and learn APIs in R

Decrypt Emotion with...

Editor’s Note: Jump to the emotion reader application, submit the img url and see what their face says. An API is a way for one piece of software to interact with another application.  API stands for “application program interface” allowing your application or R script to interact with an outside service.  The cool thing about APIs is […]

The caret Package

The caret Package...

Editor’s note: This is the first of a long series of posts on the caret package. Introduction The caret package (short for _C_lassification _A_nd _RE_gression _T_raining) is a set of functions that attempt to streamline the process for creating predictive models. The package contains tools for: data splitting pre-processing feature selection model tuning using resampling […]

heatmaply: interactive heat maps (with R)

heatmaply: interacti...

I am pleased to announce heatmaply, my new R package for generating interactive heat maps, based on the plotly R package. tl;dr By running the following 3 lines of code: install.packages("heatmaply") library(heatmaply) heatmaply(mtcars, k_col = 2, k_row = 3) %>% layout(margin = list(l = 130, b = 40)) You will get this output in your […]

Choroplethr v3.5.3 is now on CRAN

Choroplethr v3.5.3 i...

A new version of choroplethr is now on CRAN. You can get it by typing the following: 1 2 3 4 5 install.packages("choroplethr") packageVersion("choroplethr") [1] '3.3.1' Motivation This new version was motivated by a few warnings that had started appearing since the latest update to ggplot2: 1 2 3 4 5 6 7 8 library(choroplethr) data(df_pop_state) […]

Reminder. R 3.3.2!

Reminder. R 3.3.2!...

R 3.3.2 (codename “Sincere Pumpkin Patch”) was released yesterday You can get the latest binaries version from here. (or the .tar.gz source code from here). The full list of bug fixes and new features is provided below. Upgrading to R 3.3.2 on Windows If you are using Windows you can easily upgrade to the latest version of R using the installr […]

Reproducible Finance with R: Sector Correlations

Reproducible Finance...

Welcome to the first installation of reproducible finance for 2017. It’s a new year, a new President takes office soon, and we could be entering a new political-economic environment. What better time to think about a popular topic over the last few years: equity correlations. Elevated correlations are important for several reasons – life is […]

How to “Get Good at R”

How to “Get Good a...

Editor’s note: post modified from original How can I get good at R? This has come up enough times for me to outline my thoughts on the subject. That way I can simply forward people to this post the next time the question comes up. My advice is geared towards people who want to build an […]

Installing Jupyter with the PySpark and R kernels for Spark development

Installing Jupyter w...

This is a quick tutorial on installing Jupyter and setting up the PySpark and the R kernel (IRkernel) for Spark development. The pre-reqs for following this tutorial is to have a Hadoop/Spark cluster deployed and the relevant services up and running (e.g. HDFS, YARN, Hive, Spark etc.). In this tutorial I am using IBM’s Hadoop […]