A Fine Slice Of SQL Server
Devin Knight’s custom visuals series moves on to the next visual:
Great way to visualize and filter time data
Filtering the visual will provide a miniaturized preview of the data for the provided time period
I like this visual; you get the benefit of focus while still keeping the full picture on a time series.
Comments closedDavid Smith sheds some light on the ggiraph project:
R’s ggplot2 package is a well-known tool for producing beautiful static data visualizations that you can include in a printed report. But what if you want to include a ggplot2 graphic on a webpage and provide the ability for the user to interact with the data? The ggiraph package by David Gohel (available for installation via CRAN). WIth ggiraph, you can take an existing ggplot2 bar chart, scatterplot, boxplot, map, or many other types of chart and add one or both of the following iteractions:
Display a tooltip of your choice (e.g. data values or labels) when the cursor hovers over sections of the chart
Perform an action (a javascript function you provide: jump to another page, for example) when the viewer clicks on an element of the chart
I like it.
Comments closedDevin Knight shows off the word cloud custom visual in Power BI:
Key Takeaways
Great for parsing unstructured data
Utilize stop words to remove commonly used filler words like a, the, an, etc…
- You can use the default stop word that are provided and add your own that you would like to remove from the visual.
The size of the words in the visual tell you how frequently the word is used.
Cf. yesterday’s word cloud example. I’m not sure how truly valuable word clouds are for visualization purposes, but at least they’re fun to peruse.
Comments closedAllison Tharp shows how to generate a word cloud using Python:
Every week, someone on Reddit posts a “word cloud” on all of the NFL team’s subreddits. These word clouds show the most used words on that subreddit for the week (the larger the word, the more it was used). These word plots are always really fascinating to me, so I wanted to try to make some for myself. In this tutorial, we’ll be making the following word cloud from my board game stats twitter feed, @BGGStats
Looks like the implementation is fairly straightforward, so check it out.
Comments closedVessy combines Javascript and R to visualize networks:
The networkD3 package provides a function called igraph_to_networkD3, that uses an igraph object to convert it into a format that networkD3 uses to create a network representation. As I used igraph object to store my network, including node and edge properties, I was hoping that I may only need to use this function to create a visualization of my network. However, this function does not work exactly like that (which is not that surprising, given the differences in how D3.js works and how igraph object is defined). Instead, it extracts lists of nodes and edges from the igraph object, but not the information about all node and edges properties (the exception is a priori specified information about nodes membership groups/clusters, which can be derived from one or more network properties, e.g., node degree). Additionally, the igraph_to_networkD3 function does not plot the network itself, but only extracts parameters that are later used in theforceNetwork function that plots the network.
This is the kind of thing I want to see when working with network data. It doesn’t necessarily scale, but given how well the human eye tracks relationships, this is very useful.
Comments closedDevin Knight’s Power BI custom visuals series continues:
Allows for a slicer buttons instead of a list like the native Slicer
Values can be arranged vertically or horizontally
Filters can be based on text or images
This could be a great custom visual for a tablet or mobile dashboard.
Comments closedTodd Schneider has a fun analysis of the Simpsons:
Per Wikipedia:
While later seasons would focus on Homer, Bart was the lead character in most of the first three seasons
I’ve heard this argument before, that the show was originally about Bart before switching its focus to Homer, but the actual scripts only seem to partially support it.
Bart accounted for a significantly larger share of the show’s dialogue in season 1 than in any future season, but Homer’s share has always been higher than Bart’s. Dialogue share might not tell the whole story about a character’s prominence, but the fact is that Homer has always been the most talkative character on the show.
My reading is that it took a couple seasons for show writers to realize that Homer is the funniest character and that Bart’s character was too context-sensitive to be consistently funny. It took quite a bit more time before merchandisers figured that out, to the extent that they ever did.
Comments closedDevin Knight continues his visualization series with the Stream Graph:
Key Takeaways
Works and looks similar to a Stacked Area Chart but with a wiggle feature that gives it a more fluid look and feel
Great for displaying data that changes over time
At first, I read this as “Steam Graph,” which made it sound like a steampunk visualization with unnecessary pipes and mechanical accouterments, but alas, it was not meant to be. I do like the stream graph visual, though.
Comments closedDevin Knight continues his custom visuals series:
In this module you will learn how to use the Sunburst chart Power BI Custom Visual. The Sunburst chart is similar to the standard donut chart but allows you to show multiple level at once, which is great when presenting hierarchical data.
I dunno; looks a little pie charty to me…
Comments closedDevin Knight continues his custom visuals series with the bubble chart:
Each category is defined as a bubble on the visual.
The size of the bubble is defined by a measure.
The Bubble chart does allow for cross filtering. Meaning you can click on a bubble in the chart and it will filter other report items
This is a nice eye-catcher image, like you might see in a news article.
Comments closed