A Fine Slice Of SQL Server
Devin Knight’s Power BI custom visuals series continues:
The Scroller the values move from left to right on an animated scroll bar.
The settings allow you to customize the speed, size, status indicator and colors used.
If you’d like to see the status indicator then you must have a deviation value.
Maybe it’s just me, but I’m not a fan of tickers. They’re too visually noisy for my taste.
Comments closedDevin Knight has part 24 of his custom visuals series:
The Globe Map is a 3D globe visualization.
It looks similar to the technology Power Map in Excel but lacks a few features like animating the data across time.
The map can have multiple data visualization layers on top of the map like a bar chart and a heat map.
Under the right circumstances, this can be a useful visualization. I think its benefit is mostly limited to the “wow, this looks cool” effect.
Comments closedDevin Knight continues his custom visuals series with the sparkline:
Key Takeaways
Shows trends in data most often by time.
It can only visualize a single measure.
The Sparkline can be configured to animate across time.
In the right circumstances, I love sparklines. My circumstances are as follows: when you are viewing time series data for relatively few elements in which the trend is more important than the levels. In that scenario, sparklines are efficient and tell the story without extraneous numbers or clutter getting in the way.
Comments closedDevin Knight’s series on Power BI custom visuals continues with the force-directed graph:
Key Takeaways
Shows relationships between different entities in your data.
The width of the line that separate each entity represents the strength of the relationship.
Click through for the discussion and a video. I’m not too sure that I’d use this in a real dashboard, but it’s available.
Comments closedDavid Smith points out the new R Graph Gallery:
Once upon a time, there was the original R Graph Gallery, by Romain François. Sadly, it’s been unavailable for several years. Now there’s a new R Graph Gallery to fill the void, created by Yan Holtz. It contains more than 200 data visualizations categorized by type, along with the R code that created them.
You can browse the gallery by types of chart (boxplots, maps, histograms, interactive charts, 3-D charts, etc), or search the chart descriptions. Once you’ve found a chart you like, you can admire it in the gallery (and interact with it, if possible), and also find the R code which you can adapt for your own use. Some entries even include mini-tutorials describing how the chart was made. You can even submit your own graph, if you’d like to have it displayed in the gallery as well.
Looks like a good place to go to get some inspiration.
Comments closedDevin 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 closed