#Workflowy example how to#
#Workflowy example code#
#Workflowy example trial#

#Workflowy example code#

The code examples are built around base R, FrankвЂ™s Hmisc and rms packages and an eclectic mix of packages that include data.table. I should mention that FrankвЂ™s eBook is not a tidyverse presentation. For example, donвЂ™t miss the if Trick in section 2.4.3. The missing value section suggests a whole array of analyses through a careful presentation of plots, and the section on data checking introduces a level of automation beyond what is commonly done.ДЇrankвЂ™s writing style is clear, informal and from the perspective of a teacher who wants to show you some cool things along with the basics. FrankвЂ™s examples are streamlined presentations of analyses and code that are both sophisticated an practical. Then, there is the synthesis of a wide range of content into a succinct, very readable exposition that dips in to some very deep topics. As the diagram indicates, the document takes a holistic viewpoint of a statistical analysis covering document preparation, data manipulation, statistical practice computational concerns, and more.

#Workflowy example trial#

This workflow is clearly the result of a process forged through trial and error by a master statistician over many years. To begin with, the workflow itself is much more than a simple progression of logical steps. Frank HarrellвЂ™s new eBook, R Workflow, which aims to: вЂњto foster best practices in reproducible data documentation and manipulation, statistical analysis, graphics, and reportingвЂќ is an ambitious document that is notable on multiple levels. A social network is the perfect example of what this kind of database is ideal for, but there's plenty more! Your hard-drive directory structure perhaps? I'd love to hear any other random ideas, so do please comment below with your weird and wonderful use-cases!. What other data sources can you think of that would be awesome dumped into Neo4j? The obvious one for this shape of data is social media, where a node is a user and the relationships points to other users that they're following. Obviously, Workflowy data is just one example idea I had. It's much more fun though when you're browsing your own data - so if you're a Workflowy user, I'd highly recommend having a play and using my code to export your own data into a local Neo4j instance. Note that the Workflowy data in the animated gif is pinched from Workflowy's Live Demo, as I want to keep my own personal Workflowy data, well, personal. Instead, just enjoy this animated gif of the results!.

#Workflowy example how to#

The readme file in my GitHub project gives step by step instructions on how to use it, so I won't repeat that here. The project consists of a Docker docker-compose file to spin up Neo4j locally, and also a LINQPad script which processes a Workflowy exported text file, writing the data to Neo4j. Right, as you've probably gathered by now - a large Workflowy dataset would make an awesome Neo4j visualization! So, I wrote some code, and put it on GitHub. All with really nice animations (see animated gif further down this blog post).

In the browser, you can drag nodes around, expand and collapse nodes, etc. It comes with the Neo4j Browser, which is a really nice user interface for browsing your data - allowing you to enter queries which then get rendered into a graph visualization. So you're storing data in nodes which can have relationships pointing at other nodes. Graph databases are designed to be highly relational. NET Oxford without all that other stuff getting in the way. And yet in the screenshot, you can see that I can happily work in the context of just. Bare in mind that my entire Workflowy account has everything from my various project details and todos, to recipe lists, to holiday information, to info about my kids nursery, etc. The bullet points with the halo indicate collapsed nodes with more information. The below screenshot shows that I'm zoomed into the. There's also some really useful keyboard shortcuts in the Workflowy user interface which really helps you to quickly navigate your hierarchy. This means that you can store a huge amount of data in Workflowy about various things - notes, todo lists, project details and breakdowns, bookmarks, recipes, gym workouts, inventory, holiday information, and anything else you can imagine! So the power comes from the ability to zoom into any node in the hierarchy. But that doesn't sound very interesting does it? Microsoft Word can do that can't it? The simplest description of Workflowy is that it allows you to create lists consisting of bullet points, and those bullet points can be indented / nested. Due to the very hierarchical nature of Workflowy, I had a random idea that this would make a very cool Neo4j visualization! So I made a thing, and put it on GitHub.ДЇirst of all though, I should really explain what both Workflowy and Neo4j actually are. I'm a heavy user of Workflowy, which is an amazing tool for taking notes. 27 July 2017 - Docker, LINQPad, Neo4j, Workflowy