Using Power BI to Report on Location Columns in SharePoint

At the end of 2018, SharePoint received something that we haven’t seen for a long time – a new column type, Location. Location columns will look up an address and geocode it as it is being entered in a form. It will also separate all the constituent parts of the address as well as the latitude and longitude into separate display only columns. These columns are used primarily in views but can also be used in reports. Given that I put together a series of posts recently on using Power BI to work with complex SharePoint report types, I was interested on how to report on this new column type. As it turns out, it is relatively straightforward.

This post will delve into the nuances involved with reporting on this new SharePoint Location column in Power BI..

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At the end of 2018, SharePoint received something that we haven’t seen for a long time – a new column type, Location. Location columns will look up an address and geocode it as it is being entered in a form. It will also separate all the constituent parts of the address as well as the latitude and longitude into separate display only columns. These columns are used primarily in views but can also be used in reports. Given that I put together a series of posts recently on using Power BI to work with complex SharePoint report types, I was interested on how to report on this new column type. As it turns out, it is relatively straightforward.

This post will delve into the nuances involved with reporting on this new SharePoint Location column in Power BI..

The Location Column

To begin with, the Location column is a “modern” SharePoint column. This means that it can be added to a list via the Add column button in the list view, but NOT through the list settings page as other column types are.

List view creation

List settings creation

If the Add column does not appear for you, you may be using a “classic” SharePoint site, or you may be using one or more column types that are not supported in “modern” which causes a classic view to be used. Removing these columns from the view is often enough to light up the add button.

Once created, you will have the option to add any or all of the address components to the view. These are display elements only and will be available to reports (or other views) whether or not they are added to the view at creation time.

Once created, entering data is as simple as typing in an address, or the name of a location into the column. The typeahead feature will attempt to find the location and fill in the details.

Once selected, the full address will be filled in, and all the constituent address properties will be populated. If they are on the view, the list can be sorted, filtered, etc. by these elements.

Reporting on the Location Column

Internally, the location is saved as a BLOB of JSON content within a column. When the column itself is used in the view, its friendly display format is displayed. When constituent items are displayed (City for example) their values are extracted from the column and displayed as discrete elements. For other SharePoint column types, this can provide complications, but the developers of the location feature seem to have had reporting in mind when it was built. Consider the following list that contains a Location column named Location:

Loading the Data

We first launch Power BI Desktop, select “Get Data” and then choose SharePoint Online list. We are then prompted for the URL of the SharePoint Site. The dialog is titled SharePoint lists, but the value is the URL of the site, NOT the list itself. Once this is entered, we are prompted for credentials if we haven’t connected to this site before. After entering credentials, we can select the list that we want to report on. In our case, it’s named Properties. We select it, and then click on the Edit button.


Once the data loads in, one of the first things that you’ll notice is that there are a lot of columns to choose from, and it’s a good idea to remove the columns that you don’t need. We can do this by right clicking on the desired column titles and selecting Remove.

Using FieldValuesAsText

With all other complex SharePoint column types, the FieldValuesAsText column will retrieve the textual representation of required column values. This is the way that the column value appears in a view. However, it appears that the Location column type is an exception to this rule. When the Location column is used, the JSON value itself is returned, which renders FieldValuesAsText relatively useless. THis value is also available using the Location column value itself. The steps for extracting FiedValuesAsText are covered in previous posts in this series. Given that ultimately this will not be a good approach for the Location column, we won’t go into it further here.

Field value and value extracted from FieldValuesAsText

Using DispName

The text value of the location column is instead available through the derived DispName column.

With Power BI, it is possible to transform the JSON data contained in the original column, or the extracted FieldValuesAsText column. All of the extracted properties are available through more efficient means. The FieldValuesAsText column can therefore be ignored for the purposes of reporting on Location columns. In addition, in most cases, the original column (Locations in this case) can be removed, and the DispName column should be renamed in its place.

This behaviour is inconsistent with the behaviour of other complex SharePoint fields. It does not affect capability, but in the interests of consistency, my strong suggestion would be for the SharePoint team to eliminate the DispName field, and leverage FieldValuesAsText for the text conversion in the data feed.

Using Location Components

All the text components of the location column are separated out automatically as columns in Power Query. They can be used as any other column, and no additional action is necessary.

Automatically extracted location components

Using GeoLoc

Power BI will automatically geocode data at the time the report is rendered. The text components can therefore be used by the reporting engine to place data on a map. However, geocoding is a relatively computationally expensive operation, especially if there is a lot of data, or poor internet connection. In addition, some visuals may require the use of specific latitude and longitude co-ordinates. These co-ordinates are available through the GeoLoc column if they are needed, but they do need to be extracted.

Within Power Query, locate the GeoLoc column, and click on the Expand icon in the right of the column header.

Select both the Latitude and Longitude columns and deselect Use original column name as prefix. In my testing, both Altitude and Measure do not return any meaningful data, so they can be safely ignored, however this could change in the future.

At this point, we are almost ready to do some reporting. Once all the required columns have been shaped, and their data types set, select the Close and Apply button from the ribbon.

Reporting

Before using the location data on a map, it is important to categorize each of the components so that Power BI knows how to use it on a map. To categorize a data field, select it from the fields list. Then select the Modeling tab from the ribbon click the Data Category dropdown.

The category for most of the fields is obvious, but below is a table of recommended choices. In addition, both the longitude and latitude fields need to be set to the Decimal Number type.

Field Category
City City
CountryOrRegion Country/Region
Latitude Latitude
Location Place
Longitude Longitude
PostalCode Postal Code
State State or Province
Street Address

Once categorized, the data can be placed on a map according to any desired parameters. In this can, the below shows a map of listings colour coded by the asking price range.

The resulting report can then be published to the Power BI service, and then embedded into a SharePoint page through either the Power BI web part, or secure embedding if so desired.

Happy reporting!

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