The Enhanced Scatter functions very similarly to the standard Power BI scatter chart but with a few new properties added to it including:
Shapes as markers
Background image support
I’ve enjoyed going through this series and getting a chance to dig into custom visuals others have created.
So how do we do this? Well, the first thing to do is get the number of swearwords per minute. I mentioned that for the original article someone just counted every swearwords, in our case, we’re just going to parse a subtitle file, and extract the swear words from that.
Without going into too much detail, you can find the code I’ve experimtend with in this gist (it’s very ugly code, since I just hacked something together that worked).
Jos includes counts for four movies. This link does contain a few bad words, but if you get past that, it’s a good pattern for analyzing word counts in general.
In this module you will learn how to use the Histogram, a Power BI Custom Visual. A Histogram is a column chart which shows the distribution of occurrences divided into categories, called bins. This type of chart is useful for estimating density and discovering outliers.
Another fine entry in a great series. Check it out.
In this post we’ll try to replicate some of the charts created by the Federal Reserve which visualize some well known macroeconomic indicators. We’ll also showcase the new Plotly 4.0 syntax.
This is a very code-heavy blog post and is a good way to learn about plotly.
Change the Banding type property to one of the following:
Increasing is better – Increasing is best when you’re measuring things like sales or profit. If you go over your profit target that’s a good thing!
Decreasing is better – Decreasing is probably best when you’re looking at something like budgeting. Staying under budget is usually a good thing. Unless you being too far under budget means you won’t get that money again next year which leads to the last option
Closer is better – This is for when you need your data to land in the middle of a bell curve. Meaning if you go too high or too low that’s a bad thing. This is often useful when looking at medical data. For example, if your blood pressure is too high then that’s a bad thing, but if you’re blood pressure is too low that’s also a bad thing too. You need to land in the middle somewhere, which is what this option allows.
There’s plenty of good advice here, so check out the video.
In this module you will learn how to use the Radar Chart, a Power BI Custom Visual. The Radar Chart is sometimes is also know to some as a web chart, spider chart, or star chart. Using the Radar Chart allows you to display multiple categories of data on each spoke (like spokes on a bicycle wheel) of the chart. The Radar Chart does support the display of multiple metrics, which allows you to compare and contrast the “pull” that each category has on your metrics.
I still say you should stick with the fish chart for all of your visualization needs.
In this module you will learn how to use the Hexbin Scatterplot Power BI Custom Visual. The Hexbin Scatterplot is a variation of the traditional Scatter Chart but instead of using bubble size it relies on color saturation and hexbins to show value distribution. You should consider using this chart when you’re more interested in visualizing density instead of individuals points themselves.
This is worth checking out.
In this module you will learn how to use the Enlighten Aquarium Power BI Custom Visual. While it might not be the most practical visualization it does provide a fun way to show categorical data and can have multiple series shown as well.
From now on, all dashboards must look like screensavers from the 1990s.
After loading data into a server-based associative, in-memory database, Qlik customers could explore the data in a variety of ways from an AJAX Web GUI, enabling them to create and publish all sorts of reports and dashboards. The approach is not entirely dissimilar to the one taken by its rival, Tableau Software, which has also benefited from the big data boom and the democratization of BI.
The combination of market forces and a keen eye for product development were propellant for growth at Qlik. In 2009, the Radnor, Pennsylvania-based company had 11,400 customers and $157 million in revenues. By 2010, it had grown to 13,000 customers and had an IPO. By 2015, the company boasted 37,000 customers, $612 million in revenue, and a market cap north of $2.8 billion.
Qlik is definitely one of the big players in the visualization market, which includes Tableau, and Power BI/SSRS in Gartner’s Leaders quadrant and a bunch of competitors nipping at their heels.
Common chart clutter items include:
Dark gridlines (use soft gray gridlines or eliminate gridlines when possible)
Overuse of bright, bold colors
Unnecessary use of all uppercase text (uppercase text is only necessary when calling attention to an element)
Basically, remove every visualization “feature” that Excel 97 gave you…