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Category: Visualization

Transit Data Visualization In R

Goncalo Trincao Cunha shows us how to plot General Transit Feed Specification data in R:

GTFS (General Transit Feed Specification) is a specification that defines a data format for public transportation routes, stop, schedules, and associated geographic information.

In this post, we’ll use R with ggplot2 and ggmap to visualize GTFS route and schedule information on a map.

This post uses a GTFS feed from CARRIS, which is a bus public transport operator from the city of Lisbon.

Click through for code and a few interesting maps of Lisbon, Portugal.

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Comparing Baselines Using Power BI

Melissa Connors shows how to take baseline data from SentryOne and visualize it within Power BI:

Using Power BI to connect to multiple baselines in SentryOne allows me to make fast comparisons. I previously translated baseline values into charts manually or through some Excel/SQL Server connections. See this post on data compression as an example. I wanted to compare performance between different compression levels (None, Row, and Page), and include the Average, Minimum, Maximum, and Standard Deviation values. Now, I have a standard template that looks better in Power BI. Once I create a baseline in my database, I have access to it in my charts. If you don’t have Power BI, you can use the query from this post in Excel or another reporting method for your comparisons.

Even if you don’t use SentryOne, the principles are generally applicable.

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Limiting Color Usage On Dashboard Charts

Jesse Gorter explains why you shouldn’t overwhelm your dashboard chart users with colors:

In this example we use a signal color for the past too. Do you notice how the usage of green distracts from the current week which is a red? This suggest we are doing great overall even though at this time, we are doing not so great. It is up to you to decide what you want to communicate. If you are a sports team showing the rank during the season, only the current position would be important. In sales, having 30 weeks of outstanding sales above the target and the current week selling slightly under, it would make sense to show the signal color for the past.

Not to mention making it easier for people with CVD to read your report, something with which the red-green scheme does not do great.

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The Great Custom Visual Move

Ginger Grant runs into a problem with some of the custom visuals (not) in the Office Store:

This week I decided to do a demo using the Aquarium custom visual.  As readers of my blog know, I have used the custom visual before, but it has been a while and I have changed PCs since then.  No worries I can always go download the visual from the store, right? Wrong. The aquarium visual is not available on the new store. Neither is Image Viewer, if one is looking to add that into your latest Power BI report it is not available. What happened?

Read on to learn why the aquarium is missing.  RIP aquarium (hopefully only temporarily).

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Maps In Power BI

Reid Havens shows off the different map visuals within Power BI:

ArcGIS Map

The most recent addition to the Power BI Map family. It’s supported by a company called Esri, and is a very feature rich map visual! What makes this visual stand out is that you can overlay whatever data you have with public geographical data such as demographics, weather, and even historical data. It’s highly customizable and offers multiple ways to visualize data with maps, and that’s even before you start adding the public data sets! Can you tell that I like this visual a lot? Because I do! visualize data with maps

Now I could easily spend an entire blog post JUST outlining all the ways to use this visual, but I’ll stick to the highlight reel. It can visualize data with maps using the bubble or fill method similar to the other map visuals, albiet with a few more customizations and tweaks. However, one of the unique features of this visual is the heat map option! Any of you familiar with Power Maps in Excel has probably seen this before…well now we have it in Power BI. I find this data visualization super useful in identifying data clustering based on location.

Read on for additional varieties of maps you can create.  I personally think the bubble map is ugly and that one map with pie charts (thankfully not shown in Reid’s post) is hideous, but there are some very good map visuals available to us.

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