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Category: R

Using SHAP to Gauge Geographic Effects in R or Python

Published 2023-06-08 by Kevin Feasel

Michael Mayer runs an analysis:

This is the next article in our series “Lost in Translation between R and Python”. The aim of this series is to provide high-quality R and Python code to achieve some non-trivial tasks. If you are to learn R, check out the R tab below. Similarly, if you are to learn Python, the Python tab will be your friend.

This post is heavily based on the new {shapviz} vignette.

I appreciate the effort to include both R and Python code in this analysis, and recommend you peruse both sets of code listings.

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Unpivoting Data in R

Published 2023-06-08 by Kevin Feasel

Steven Sanderson shows off a function with a slightly confusing name:

In the world of data analysis and manipulation, tidying and reshaping data is often an essential step. R’s tidyr library provides powerful tools to efficiently transform and reshape data. One such function is pivot_longer(). In this blog post, we’ll explore how pivot_longer() works and demonstrate its usage through several examples. By the end, you’ll have a solid understanding of how to use this function to make your data more manageable and insightful.

The slight confusion is that this function is really unpivoting rather than pivoting. In R terminology, a pivot takes you from longer data to wider data: it uses some function to convert data from N rows * M columns to n*m, where N > n and M < m. Unpivoting does the opposite and I personally like that terminology better than “pivot wider” or “pivot longer.”

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Order, Sort, and Rank in R

Published 2023-06-05 by Kevin Feasel

Steven Sanderson compares three functions in R:

In the realm of data analysis and programming, organizing and sorting data efficiently is crucial. In R, a programming language renowned for its data manipulation capabilities, we have three powerful functions at our disposal: order(), sort(), and rank(). In this blog post, we will delve into the intricacies of these functions, explore their applications, and understand their parameters. These R functions are all used to sort data, however, they each have different purposes and use different methods to sort the data.

Coming at R from a SQL background, the idea of order() and sort() behaving so differently was strange at first, especially because the verbs are synonymous and it’s the noun form of “order” which we get back, rather than performing the ordering.

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Date Handling in Excel and R

Published 2023-05-22 by Kevin Feasel

Amieroh Abrahams continues a series comparing Excel and R:

Here we will explore the various ways to handle dates in Excel and R. Dates are a crucial part of data analysis and are used in various fields such as biology, healthcare, and social sciences. However, working with dates can be challenging, especially when dealing with large datasets or multiple formats.

In Excel, there are several functions available to handle dates, such as DATE, YEAR, MONTH, and DAY. Excel also provides various formatting options to customise the display of dates. However, Excel has some limitations when it comes to complex date calculations, and it can be time-consuming to work with dates in large datasets.

In contrast, R has a robust set of tools for handling dates, including the {lubridate} package, which simplifies the manipulation of dates and times. Additionally, R allows for efficient handling of dates in large datasets, making it a powerful tool for time-series analysis. Whether you are working with dates in Excel or R, this blog will provide you with the basic tools and techniques to handle dates efficiently and accurately. So let’s get started!

Read on for the comparison.

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Common Date and Time Operations in R

Published 2023-05-18 by Kevin Feasel

Steven Sanderson works with dates:

Dates and times are essential components in many programming tasks, and R provides various functions and packages to handle them effectively. In this post, we’ll explore some common operations using both the base R functions and the lubridate package, comparing their simplicity and ease of understanding.

I personally prefer the lubridate style of date operation, but it’s nice to have options.

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Dates and Times in R

Published 2023-05-16 by Kevin Feasel

Steven Sanderson talks dates and times. First up is an overview of how built-in date functionality works in R:

In this post, we will cover the basics of handling dates and times in R using the as.Date, as.POSIXct, and as.POSIXlt functions. We will use the example code below to explain each line in simple terms. Let’s get started!

The second post covers the Date type, as well as date plus time:

In the first part of our code, we use the as.Date() function to find the next Mother’s Day. Since we don’t need to consider specific times, we can simply use the Date class, which simplifies the process. We create a vector with two elements: startMothersDay and endMothersDay, both set to “2024-05-14”. This represents the range of Mother’s Day for the year 2024. Finally, we store the result in the variable NextMothersDay and print it to the console. Voilà! We have the next Mother’s Day date.

Note that this isn’t a post about date calculation, such as finding the Nth Sunday in the month of May

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An Introduction to ggflowchart

Published 2023-05-15 by Kevin Feasel

Nicola Rennie shows off a new package:

Flowcharts can be a useful way to visualise complex processes. However, I couldn’t find an easy way to create a flowchart in R. There are a few packages for either drawing basic components of flowcharts (like {grid}), packages that are great for visualising complex network data where order doesn’t really matter (like {ggnetwork} and {igraph}), but none of them gave me the control over customisation I was used to with {ggplot2}.

{ggflowchart} tries to fill that gap. The aim of {ggflowchart} is to help R users make simple, good-looking flowcharts, with as little code as possible. It computes a layout, then uses existing {ggplot2} functions to stitch together rectangles, text, and arrows.

It does remind me a bit of Mermaid, though quite early in the process. H/T R-Bloggers.

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Integrating VBA and R Code

Published 2023-05-11 by Kevin Feasel

Steven Sanderson has become Dr. Moreau. Part 1 shows how to call R code from VBA:

This line defines a subroutine called “CallRnorm”. A subroutine is a block of code that can be executed repeatedly from any part of the code, and it starts with the “Sub” keyword followed by the subroutine name and any arguments in parentheses.

Part 2, as you might expect, covers the obverse:

Yesterday I posted on using VBA to execute R code that is written inside of the VBA script. So today, I will go over a simple example on executing an R script from VBA. So let’s get into the code and what it does.

First, let’s look at the Function called “Run_R_Script”. This function takes four arguments, where the first two are mandatory, and the last two are optional.

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Converting Letters to Pre-Smartphone Numeric Codes

Published 2023-05-08 by Kevin Feasel

Tomaz Kastrun rolls back the clocks:

What a nightmare was to type a short message on these keypads. So, image writing Hello on this keypad, you had to press: 4433555555666 to get the letters “hello”.

44 = h
33 = e
555 = l
555 = l
666 = o

So creating converter would be great to troll on your friends

This seems like as good a reason as any to create such a function. Click through to see how to do it in R.

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Using a Map in shiny

Published 2023-05-05 by Kevin Feasel

Steven Sanderson plots a course:

The code is used to create a Shiny app that allows the user to search for a type of amenity (such as a pharmacy) in a particular city, state, and country, and then display the results on a map. Here is a step-by-step explanation of how the code works.

Click through for notes, the code, and an example of the app in operation.

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