Playing with Maps

Though the data I usually work with has very little to do with physical locations, I decided to play around with the maps visualization in Power BI this evening.  Since the data set I’ve been playing with includes both latitude and longitude information, it was the perfect opportunity to try it out.

To begin with, I selected the map visualization which gave me several options for input fields.  I dragged the latitude and longitude fields from the data into the appropriate boxes and was rewarded with a map of Chicago.

However, the map is really crowded when all the data is displayed.  Just for fun, I added gender to the legend field and the visualization became slightly more overwhelming.

While wanting to avoid grouping the data, I added some page level filters which limited the rides to female riders in February in thunderstorms.  This left me with a much smaller amount of rides and after zooming in, I started to see the details in the maps.

Though this is still a bit cluttered, it’s easy to see where distinctions in the data could start to be made.

It’s a fun feature to play.

How to Count Distinct in a Pie Chart

Recently, I created this pie chart based on distinct counts in Power BI.  This was interesting simply because I didn’t think that there would be an difference in my data based on the day of the week, but there it was.  The difference is slight, but surprising nonetheless.

To create a pie chart with distinct counts, I started by selecting the pie chart visualization.  I think added my day field to the “legend” input and added from station to the values option.

To switch from a total value on the from_station, I pressed the small downward arrow and selected “Count (Distinct) as shown in the image below.

My output was the pie chart showing the distinct value counts below.

Finding Public Datasets

Power BI is a wonderful to use when you have data that you’re trying to display.  Sometimes you may just want to play with alternative datasets to explore the full functionality offered by Power BI.

This will be an ever expanding list of sources of public data sets.

Kaggle Datasets

Actuarial Climate Index/

Government Data

California Data

Minneapolis, MN data

CDC Death Data

Enron Email Data

AIRBNB Data

 

Please feel free to add any sample data sets in the comments below.

Divvy Bike Sharing Data – Take 2

After putting together a very simple example yesterday using a standard white background and default colors, I decided to have a little fun with the bicycle sharing data and attempt a visualization based on a picture of a bicycle. Though there is not a lot of graphs included on the Power BI example below, you can see how pictures can be used to add another element on the sheet. Given more time, one could also customize the colors of the elements in the graph.

 

 

To add a background image to your Power BI presentation, follow the rules below.

Select the background of the slide (make sure none of your visualization elements are selected).

Go to the format menu

On the format menu, you will need to navigate to the Page Background section

You will then need to click on the add image button and navigate to the directory where you have saved the image.

After the image has been selected, you are given additional options for customization which include transparency and image fit.  In the example above, I used the “fit” option for the image and have the transparency set at 100%.

Background images expand the design possibilities within Power BI.

Divvy Bike Sharing Data

Below is a simple example of the visualizations available in Power BI using a public data set from Kaggle.com.  Kaggle.com has a public repository of datasets, although you will need to check the licenses for each dataset prior to use.

 

The Divvy Bicycle data set includes gender, day, time, distance, latitude, longitude and a host of other fields to play with.

 

This dashboard was created using the default color scheme in Power BI.