You Can Tidy the Data

This week Sime suggested Tidy Data by Hadley Wickham for the Test team book club:

A huge amount of effort is spent cleaning data to get it ready for analysis, but there has been little research on how to make data cleaning as easy and effective as possible. This paper tackles a small, but important, component of data cleaning: data tidying. Tidy datasets are easy to manipulate, model and visualize, and have a specific structure: each variable is a column, each observation is a row, and each type of observational unit is a table.

Messy data needn't be bad data, but it might not be in a format that makes it easy to process. Many tables used for data presentation will contain implicit variables, such as person or result in the table here:

If you've ever generated, aggregated, or inherited data of any scale for analysis you're almost certainly already familiar with the basic ideas. You've probably also done informally, with much cursing, copy-pasting, and burnt fingers what this paper formalises as a small set of transformation patterns that, applied appropriately, will make messy data tidier.

The table below tidies the table above to have one row per experimental observation, one data value per cell, and all variables explicitly named:

In our discussion we noted some interesting overlap with the observability white paper we read recently. Although the term tidy data wasn't used, these pieces of advice suggest that the folks over at Honeycomb.io are familiar with the idea:

Exploring your systems and looking for common characteristics requires support for high-cardinality fields as a first-order group-by entity.

Add units to field names, not values (such as parsing_duration_µs or file_size_gb)

Generate one event per service/hop/query/etc.

Wickham's paper is short and readable so I won't summarise it here but I will note that the operations have snappy names (melting, splitting, casting) and examples that illustrate them, and their application and composition clearly.

I'll also mention that, once again, I'm struck by how useful it is to name a thing and take it out of the realms of tacit, experiential knowledge and into the world of explicit, inspectable knowledge and hence shared value.

Images: Tidy Data, AbeBooks

Comments

Unknown said…

"A huge amount of effort is spent cleaning data to get it ready for analysis"

Data science people I follow say that a data science project is usually 80% data engineering, and only 20% actual data science. (Data engineering includes cleaning, but can also be denormalising and other things.)

September 13, 2019 at 10:11 AM

Meet Me Halfway?

The Association for Software Testing is crowd-sourcing a book, Navigating the World as a Context-Driven Tester , which aims to provide responses to common questions and statements about testing from a context-driven perspective . It's being edited by Lee Hawkins who is posing questions on Twitter , LinkedIn , Mastodon , Slack , and the AST mailing list and then collating the replies, focusing on practice over theory. I've decided to contribute by answering briefly, and without a lot of editing or crafting, by imagining that I'm speaking to someone in software development who's acting in good faith, cares about their work and mine, but doesn't have much visibility of what testing can be. Perhaps you'd like to join me? --00-- "Stop answering my questions with questions." Sure, I can do that. In return, please stop asking me questions so open to interpretation that any answ...

Can Code, Can't Code, Is Useful

The Association for Software Testing is crowd-sourcing a book, Navigating the World as a Context-Driven Tester , which aims to provide responses to common questions and statements about testing from a context-driven perspective . It's being edited by Lee Hawkins who is posing questions on Twitter , LinkedIn , Mastodon , Slack , and the AST mailing list and then collating the replies, focusing on practice over theory. I've decided to contribute by answering briefly, and without a lot of editing or crafting, by imagining that I'm speaking to someone in software development who's acting in good faith, cares about their work and mine, but doesn't have much visibility of what testing can be. Perhaps you'd like to join me? --00-- "If testers can’t code, they’re of no use to us" My first reaction is to wonder what you expect from your testers. I am immediately interested ...

The Best Programmer Dan Knows

I was pairing with my friend Vernon at work last week, on a tool I've been developing. He was smiling broadly as I talked him through what I'd done because we've been here before. The tool facilitates a task that's time-consuming, inefficient, error-prone, tiresome, and important to get right. Vern knows that those kinds of factors trigger me to change or build something, and that's why he was struggling not to laugh out loud. He held himself together and asked a bunch of sensible questions about the need, the desired outcome, and the approach I'd taken. Then he mentioned a talk by Daniel Terhorst-North, called The Best Programmer I Know, and said that much of it paralleled what he sees me doing. It was my turn to laugh then, because I am not a good programmer, and I thought he knew that already. What I do accept, though, is that I am focussed on the value that programs can give, and getting some of that value as early as possible. He sent me a link to the ta...

Beginning Sketchnoting

In September 2017 I attended Ian Johnson 's visual note-taking workshop at DDD East Anglia . For the rest of the day I made sketchnotes, including during Karo Stoltzenburg 's talk on exploratory testing for developers (sketch below), and since then I've been doing it on a regular basis. Karo recently asked whether I'd do a Team Eating (the Linguamatics brown bag lunch thing) on sketchnoting. I did, and this post captures some of what I said. Beginning sketchnoting, then. There's two sides to that: I still regard myself as a beginner at it, and today I'll give you some encouragement and some tips based on my experience, to begin sketchnoting for yourselves. I spend an enormous amount of time in situations where I find it helpful to take notes: testing, talking to colleagues about a problem, reading, 1-1 meetings, project meetings, workshops, conferences, and, and, and, and I could go on. I've long been interested in the approaches I've evol...

How do I Test AI?

Recently a few people have asked me how I test AI. I'm happy to share my experiences, but I frame the question more broadly, perhaps something like this: what kinds of things do I consider when testing systems with artificial intelligence components . I freestyled liberally the first time I answered but when the question came up again I thought I'd write a few bullets to help me remember key things. This post is the latest iteration of that list. Caveats: I'm not an expert; what you see below is a reminder of things to pick up on during conversations so it's quite minimal; it's also messy; it's absolutely not a guide or a set of best practices; each point should be applied in context; the categories are very rough; it's certainly not complete. Also note that I work with teams who really know what they're doing on the domain, tech, and medical safety fronts and some of the things listed here are things they'd typically do some or all of. Testing ...

Not Strictly for the Birds

One of my chores takes me outside early in the morning and, if I time it right, I get to hear a charming chorus of birdsong from the trees in the gardens down our road, a relaxing layered soundscape of tuneful calls, chatter, and chirrupping. Interestingly, although I can tell from the number and variety of trills that there must be a large number of birds around, they are tricky to spot. I have found that by staring loosely at something, such as the silhouette of a tree's crown against the slowly brightening sky, I see more birds out of the corner of my eye than if I scan to look for them. The reason seems to be that my peripheral vision picks up movement against the wider background that direct inspection can miss. An optometrist I am not, but I do find myself staring at data a great deal, seeking relationships, patterns, or gaps. I idly wondered whether, if I filled my visual field with data, I might be able to exploit my peripheral vision in that quest. I have a wide monito...

Don't Know? Find Out!

In What We Know We Don't Know , Hillel Wayne crisply summarises a handful of research findings about software development, describes how the research is carried out and reviewed and how he explores it, and contrasts those evidence-based results with the pronouncements of charismatic thought leaders. He also notes how and why this kind of research is hard in the software world. I won't pull much from the talk because I want to encourage you to watch it. Go on, it's reasonably short, it's comprehensible for me at 1.25x, and you can skip the section on Domain-Driven Design (the talk was at DDD Europe) if that's not your bag. Let me just give the same example that he opens with: research shows that most code reviews focus more on the first file presented to reviewers rather than the most important file in the eye of the developer. What we should learn: flag the starting and other critical files to receive more productive reviews. You never even thought about that possi...

ChatGPTesters

The Association for Software Testing is crowd-sourcing a book, Navigating the World as a Context-Driven Tester , which aims to provide responses to common questions and statements about testing from a context-driven perspective . It's being edited by Lee Hawkins who is posing questions on Twitter , LinkedIn , Mastodon , Slack , and the AST mailing list and then collating the replies, focusing on practice over theory. I've decided to contribute by answering briefly, and without a lot of editing or crafting, by imagining that I'm speaking to someone in software development who's acting in good faith, cares about their work and mine, but doesn't have much visibility of what testing can be. Perhaps you'd like to join me? --00-- "Why don’t we replace the testers with AI?" We have a good relationship so I feel safe telling you that my instinctive reaction, as a member of the T...

Express, Listen, and Field

Last weekend I participated in the LLandegfan Exploratory Workshop on Testing (LLEWT) 2024, a peer conference in a small parish hall on Anglesey, north Wales. The topic was communication and I shared my sketchnotes and a mind map from the day a few days ago. This post summarises my experience report. Express, Listen, and Field Just about the most hands-on, practical, and valuable training I have ever done was on assertiveness with a local Cambridge coach, Laura Dain . In it she introduced Express, Listen, and Field (ELF), distilled from her experience across many years in the women’s movement, business, and academia. ELF: say your key message clearly and calmly, actively listen to the response, and then focus only on what is relevant to your needs. I blogged a little about it back in 2017 and I've been using it ever since. Assertiveness In a previous role, I was the manager of a test team and organised training for the whole ...

Software Sisyphus

The Association for Software Testing is crowd-sourcing a book, Navigating the World as a Context-Driven Tester , which aims to provide responses to common questions and statements about testing from a context-driven perspective . It's being edited by Lee Hawkins who is posing questions on Twitter , LinkedIn , Mastodon , Slack , and the AST mailing list and then collating the replies, focusing on practice over theory. I've decided to contribute by answering briefly, and without a lot of editing or crafting, by imagining that I'm speaking to someone in software development who's acting in good faith, cares about their work and mine, but doesn't have much visibility of what testing can be. Perhaps you'd like to join me? --00-- "How can I possibly test 'all the stuff' every iteration?" Whoa! There's a lot to unpack there, so let me break it down a little: who is suggesting that "al...

Hiccupps

Search This Blog