Posted on Categories Programming, TutorialsTags , , , 2 Comments on coalesce with wrapr

coalesce with wrapr

coalesce is a classic useful SQL operator that picks the first non-NULL value in a sequence of values.

We thought we would share a nice version of it for picking non-NA R with convenient operator infix notation wrapr::coalesce(). Here is a short example of it in action:

library("wrapr")

NA %?% 0

# [1] 0

A more substantial application is the following.

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Posted on Categories data science, Practical Data Science, Pragmatic Data Science, Pragmatic Machine Learning, Programming, TutorialsTags , , Leave a comment on The blocks and rows theory of data shaping

The blocks and rows theory of data shaping

We have our latest note on the theory of data wrangling up here. It discusses the roles of “block records” and “row records” in the cdata data transform tool. With that and the theory of how to design transforms, we think we have a pretty complete description of the system.

Rowrecs to blocks

Posted on Categories Programming, TutorialsTags , , 4 Comments on Use Pseudo-Aggregators to Add Safety Checks to Your Data-Wrangling Workflow

Use Pseudo-Aggregators to Add Safety Checks to Your Data-Wrangling Workflow

One of the concepts we teach in both Practical Data Science with R and in our theory of data shaping is the importance of identifying the roles of columns in your data.

For example, to think in terms of multi-row records it helps to identify:

  • Which columns are keys (together identify rows or records).
  • Which columns are data/payload (are considered free varying data).
  • Which columns are "derived" (functions of the keys).

In this note we will show how to use some of these ideas to write safer data-wrangling code.

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Posted on Categories Programming, TutorialsTags Leave a comment on Conway’s Game of Life in R: Or On the Importance of Vectorizing Your R Code

Conway’s Game of Life in R: Or On the Importance of Vectorizing Your R Code

R is an interpreted programming language with vectorized data structures. This means a single R command can ask for very many arithmetic operations to be performed. This also means R computation can be fast. We will show an example of this using Conway’s Game of Life.

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Posted on Categories Programming, TutorialsTags , , 8 Comments on Faceted Graphs with cdata and ggplot2

Faceted Graphs with cdata and ggplot2

In between client work, John and I have been busy working on our book, Practical Data Science with R, 2nd Edition. To demonstrate a toy example for the section I’m working on, I needed scatter plots of the petal and sepal dimensions of the iris data, like so:

Unnamed chunk 1 1

I wanted a plot for petal dimensions and sepal dimensions, but I also felt that two plots took up too much space. So, I thought, why not make a faceted graph that shows both:

Unnamed chunk 2 1

Except — which columns do I plot and what do I facet on?

head(iris)
##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          5.1         3.5          1.4         0.2  setosa
## 2          4.9         3.0          1.4         0.2  setosa
## 3          4.7         3.2          1.3         0.2  setosa
## 4          4.6         3.1          1.5         0.2  setosa
## 5          5.0         3.6          1.4         0.2  setosa
## 6          5.4         3.9          1.7         0.4  setosa

Here’s one way to create the plot I want, using the cdata package along with ggplot2.

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Posted on Categories Programming, TutorialsTags , , , , ,

Piping into ggplot2

In our wrapr pipe RJournal article we used piping into ggplot2 layers/geoms/items as an example.

Being able to use the same pipe operator for data processing steps and for ggplot2 layering is a question that comes up from time to time (for example: Why can’t ggplot2 use %>%?). In fact the primary ggplot2 package author wishes that magrittr piping was the composing notation for ggplot2 (though it is obviously too late to change).

There are some fundamental difficulties in trying to use the magrittr pipe in such a way. In particular magrittr looks for its own pipe by name in un-evaluated code, and thus is difficult to engineer over (though it can be hacked around). The general concept is: pipe stages are usually functions or function calls, and ggplot2 components are objects (verbs versus nouns); and at first these seem incompatible.

However, the wrapr dot-arrow-pipe was designed to handle such distinctions.

Let’s work an example.

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Posted on Categories Opinion, ProgrammingTags , 4 Comments on A Better Example of the Confused By The Environment Issue

A Better Example of the Confused By The Environment Issue

Our interference from then environment issue was a bit subtle. But there are variations that can be a bit more insidious.

Please consider the following.

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Posted on Categories Opinion, Programming, TutorialsTags , 5 Comments on A Subtle Flaw in Some Popular R NSE Interfaces

A Subtle Flaw in Some Popular R NSE Interfaces

It is no great secret: I like value oriented interfaces that preserve referential transparency. It is the side of the public debate I take in R programming.

"One of the most useful properties of expressions is that called by Quine referential transparency. In essence this means that if we wish to find the value of an expression which contains a sub-expression, the only thing we need to know about the sub-expression is its value."

Christopher Strachey, "Fundamental Concepts in Programming Languages", Higher-Order and Symbolic Computation, 13, 1149, 2000, Kluwer Academic Publishers (lecture notes written by Christopher Strachey for the International Summer School in Computer Programming at Copenhagen in August, 1967).

Please read on for discussion of a subtle bug shared by a few popular non-standard evaluation interfaces.

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Posted on Categories Opinion, Programming, TutorialsTags , , ,

Timing Column Indexing in R

I’ve ended up (almost accidentally) collecting a number of different solutions to the “use a column to choose values from other columns in R” problem.

Please read on for a brief benchmark comparing these methods/solutions.

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Posted on Categories Coding, data science, Programming, TutorialsTags , , , , 15 Comments on Using a Column as a Column Index

Using a Column as a Column Index

We recently saw a great recurring R question: “how do you use one column to choose a different value for each row?” That is: how do you use a column as an index? Please read on for some idiomatic base R, data.table, and dplyr solutions.

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