Blog Archives

Upcoming speaking engagments

April 19, 2018
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Upcoming speaking engagments

I have a couple of public appearances coming up soon. The East Bay R Language Beginners Group: Preparing Datasets – The Ugly Truth & Some Solutions, Tuesday, May 1, 2018 at Robert Half Technologies, 1999 Harrison Street, Oakland, CA, 94612. Official May 2018 BARUG Meeting: rquery: a Query Generator for Working With SQL Data, Tuesday, … Continue reading Upcoming speaking engagments

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R Tip: Use Slices

April 17, 2018
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R Tip: Use Slices

R tip: use slices. R has a very powerful array slicing ability that allows for some very slick data processing. Suppose we have a data.frame “d“, and for every row where d$n_observations < 5 we wish to “NA-out” some other columns (mark them as not yet reliably available). Using slicing techniques this can be done … Continue reading R Tip: Use Slices

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cdata Update

April 12, 2018
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cdata Update

The R package cdata now has version 0.7.0 available from CRAN. cdata is a data manipulation package that subsumes many higher order data manipulation operations including pivot/un-pivot, spread/gather, or cast/melt. The record to record transforms are specified by drawing a table that expresses the record structure (called the “control table” and also the link between … Continue reading cdata Update

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Neglected R Super Functions

April 11, 2018
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Neglected R Super Functions

R has a lot of under-appreciated super powerful functions. I list a few of our favorites below. Atlas, carrying the sky. Royal Palace (Paleis op de Dam), Amsterdam. Photo: Dominik Bartsch, CC some rights reserved. stats::approx(): approximate a curve/function. base::cumsum(): cumulative ordered sum. stats::ecdf(): estimate the cumulative distribution function. base::findInterval(): assign values to bins. base::match(): … Continue reading Neglected R Super Functions

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Four Years of Practical Data Science with R

April 4, 2018
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Four Years of Practical Data Science with R

Four years ago today authors Nina Zumel and John Mount received our author’s copies of Practical Data Science with R! It has its imitators, but it remains the best “I have R, now what do I do with it?” book (as it works the user through non-trivial projects, analyses, presentations, predictive analytic, data science, and … Continue reading Four Years of Practical Data Science with R

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R Tip: Think in Terms of Values

April 2, 2018
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R tip: first organize your tasks in terms of data, values, and desired transformation of values, not initially in terms of concrete functions or code. I know I write a lot about coding in R. But it is in the service of supporting statistics, analysis, predictive analytics, and data science. R without data is like … Continue reading R Tip: Think in Terms of Values

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Hangul/Korean edition of Practical Data Science with R!

March 29, 2018
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Hangul/Korean edition of Practical Data Science with R!

Excited to see our new Hangul/Korean edition of “Practical Data Science with R” by Nina Zumel, John Mount, translated by Daekyoung Lim. Thank you for producing a handsome edition, Manning and JPub.kr!

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R Tip: Use let() to Re-Map Names

March 26, 2018
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R Tip: Use let() to Re-Map Names

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 # <chr> <chr> … Continue reading R Tip: Use let() to Re-Map Names

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R Tip: Break up Function Nesting for Legibility

March 21, 2018
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R Tip: Break up Function Nesting for Legibility

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 == 8), c("mpg", … Continue reading R Tip: Break up Function Nesting for Legibility

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The Many Faces of R

March 15, 2018
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The Many Faces of R

Some days I see R as an eclectic programming language preferred by scientists. “Programming languages as people.” From Leftover Salad (David Marino). Other days I see it more like the following. “Statistical tools as cars.” Shared previously by Darren L. Dhaly and brought to my attention by post by Dimitri Liakhovitski, not sure of original … Continue reading The Many Faces of R

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