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Category: Visualization

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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Formatting Visuals in Power BI Desktop

Published 2023-05-11 by Kevin Feasel

Reza Rad shows off the new visual formatter in Power BI Desktop:

Where is the Format visual option in the new Power BI Desktop? There is a simple answer to this question, which I explained in this blog and video. This change applied from March 2023 version of Power BI Desktop, and by the time you read this article, it might be at general availability and the only way to format a visual in the Power BI Desktop.

I do hope they also keep the old way of formatting visuals, as there appear to be fewer clicks involved.

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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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Charts and Color Over-Use

Published 2023-05-04 by Kevin Feasel

Rita Fainshtein shows examples of how over-usage of color makes charts harder to read:

Both graphs convey a message of ranking and grouping into categories.

The categories are shown in both cases in a color-coded manner instead of in a hierarchical format. As graph creators, why do we tend to create graphs with color categories?

1. The fear of being boring, one color seems uninteresting, and here we have both colors and icons. This is an “excellent” attribute for a storyteller.

2. Visually representing a group with similar characteristics makes sense.

But can such graphs tell us anything about groups? Are they easy to understand?

Let’s discuss a few aspects of those cases together:

Click through for the full story, including an alternative to using color as a way to categorize data.

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Extending a tinyAML and shiny App

Published 2023-05-02 by Kevin Feasel

Steven Sanderson wraps up a series on shiny and tinyAML. Part 3 extends options for regression:

As data science continues to be a sought-after field, creating a reliable and accurate model is essential. While there are various machine learning algorithms available, the process of selecting the correct algorithm can be complex. The {tidyAML} package, part of the tidymodels suite, offers an easy-to-use, consistent interface for building machine learning models. In this post, we will explore a Shiny application that utilizes tidyAML to build a machine learning model.

Today I have updated the tidyAML shiny app to include the ability to set the parameter of the fast_regression() function .parsnip_fns and this is things like linear_reg.

And part 4 includes classification:

This is a Shiny app for building models using the {tidyAML} which is based on the tidymodels package in R. The app allows you to upload your own data or choose from one of two built-in datasets (mtcars or iris) and select the type of model you want to build (regression or classification).

Let’s take a closer look at the code.

This was an interesting series, for sure.

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Creating a Clickable Word Cloud with Shiny

Published 2023-04-28 by Kevin Feasel

Mandy Norrbo builds a word cloud:

Word clouds are a visual representation of text data where words are arranged in a cluster, with the size of each word reflecting its frequency or importance in the data set. Word clouds are a great way of displaying the most prominent topics or keywords in free text data obtained from websites, social media feeds, reviews, articles and more. If you want to learn more about working with unstructured text data, we recommend attending our Text Mining in R course

Usually, a word cloud will be used solely as an output. But what if you wanted to use a word cloud as an input? For example, let’s say we visualised the most common words in reviews for a hotel. Imagine we could then click on a specific word in the word cloud, and it would then show us only the reviews which mention that specific word. Useful, right?

Read on to see how you can create one of these.

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Removing Chartjunk

Published 2023-04-25 by Kevin Feasel

Elizabeth Ricks takes out the trash:

Why is clutter so hard for us to let go of? Perhaps because we think something has always been there, so it must belong there and we’re afraid of what might happen if we eliminate it. Or perhaps we don’t have a good framework for evaluating whether something is useful or not. 

This same concept applies to our graphs and business communications. We tend to blindly accept the default settings of our tools and very rarely consider if the included elements actually have a purpose. The “Windows XP” question, in this case, is: does this element add enough informative value to make up for its presence?” 

This is one of the most important ideas Edward Tufte championed—other than “pie charts are dumb, so don’t use them”. I don’t completely agree with Tufte’s definition of the term, which is (paraphrasing and going by memory) any marking on the page not absolutely necessary to convey the most relevant details to a viewer. But in this post, Elizabeth shows quite a bit we could remove while losing no critical information.

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Diagramming a Finite State Machine with Mermaid.JS

Published 2023-04-24 by Kevin Feasel

Matt Eland defeats the boss:

A year or two ago I built a small game prototype that featured a boss fight with a crab monster that was powered by a finite state machine. This monster waited for the player to enter its arena, then descended from the ceiling, roared a challenge, and began fighting the player.

The monster was only damageable after it finished descending. Taking enough damage would make the monster react in pain before it could attack again. Hurting the monster enough caused it to die.

Read on to see how you can model this information in a finite state machine and, from there, how to visualize it with the Mermaid library. I have used Mermaid in the past and can certainly recommend it if you need to generate diagrams programmatically.

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Using Dynamic Format Strings for Measures in Power BI

Published 2023-04-24 by Kevin Feasel

Meagan Longoria shows off a new preview feature:

The April 2023 release of Power BI desktop introduced a new preview feature called dynamic format strings for measures. This allows us to return values with different formats from the same measure. Previously, we needed to create calculation groups (usually by using Tabular Editor) to accomplish this. But now it is built in to Power BI Desktop.

Read on to learn good use cases for this feature, as well as a few important notes on operation and limitations.

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Styling Excel Tables in R

Published 2023-04-14 by Kevin Feasel

Steven Sanderson wants to spice things up:

The styledtable package in R, which allows users to create styled tables in R Markdown documents. The package can help to create tables with various formatting options such as bold text, colored cells, and borders. It also has functionality on how to port these to Excel itself.

The package offers a simple syntax that allows users to specify formatting options using HTML and CSS. The resulting table can be customized by changing the CSS file or by using the ‘styler’ function to apply custom styles to individual cells or rows.

Read on for more information on what the package does and a few examples of how it works.

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