Follow the steps below to add an OS basemap:

Installing OS Maps for Power BI Visual is straightforward and requires only a few steps. You should have received a link to Dropbox that contains a .pbiviz file with the name of your organisation on it. The .pbiviz file contains the visual that you'll import into Power BI.

Installing OS Maps for Power BI Visual

After installing the visual, click the OS icon and add it to a report. When you add a visual to a report, you’ll be presented with a landing page:

Linking the Power BI Visual to the OS Maps API

Rendering a basemap requires an OS Maps API Key, available from the . If you already have access to the OS Data Hub, skip to the page; otherwise, sign up for access to the OS Data Hub using the instructions below.

Signing up for the OS Data Hub

For public sector customers (i.e. PSGA Members):

• Register via the appropriate .

• You’ll need to be invited by the administrator of your organisation’s OS Data Hub account. (It’s usually someone in your GIS / Geospatial Team.) If you can’t find your OS Data Hub Administrator or want to know their contact details, please contact or your OS Account Manager.

For individuals and commercial organisations:

• Register via an to use the OS Maps API for free.

• Users requiring maps without restrictions will require a Premium OS data licence. This can be acquired via an .

Follow the steps below to create a point map:

Adding points on a map using UPRNs or Postcodes

If your data has a list of postcodes or UPRNs (unique property reference numbers), then you’re able to plot these on a map by simply dragging and dropping the relevant column in your data into the Points: Postcodes or UPRNs field of the visual.

Missing UPRN or postcode points

If you have incorrect or out-of-date postcodes and UPRNs in your data, they won’t geocode as points on the map. Clicking on the notification panel (the bell icon in the bottom left of the Power BI UI) will let you know which UPRNs or postcodes failed to geocode and are incorrect.

More detailed information, such as how many postcodes / UPRNs the visual attempted to geocode and how many succeeded, can be found by clicking on the notification panel after turning on the 'Show more detailed messaging' toggle found under Format visual > Map Settings in the Visualizations pane.

Adding points on a map using Longitude / Latitude or Eastings / Northings

If your data has a list of Longitude / Latitude or Eastings / Northings, then you’re able to plot these on a map by simply dragging and dropping the relevant columns in your data into the Points: X and Points: Y fields of the visual.

The reference layer feature provides a way to consistently display polygons/boundaries (e.g. LSOAs, wards, etc.) regardless of how point data is filtered on the page.

The reference layer feature can be found under the Visualisations pane > Format Visual > Reference Layer Settings

For a reference layer to be generated, the relevant GSS codes need to be input into the ‘GSS Codes to add as map’ text box.

GSS codes can be copied and pasted directly from a spreadsheet into the text box, and it will automatically work.

Once the codes have been input, the visual should update after a few seconds with the relevant polygons displayed on the map as a reference layer that is not linked to any other data used in the visual.

This getting started guide provides guidance on how to install and use the OS Maps for Power BI Visual. Topics covered in the guide include:

• Installation

• Adding an OS basemap

• Creating a point map

• Creating a point map using categorical data

• How to create a choropleth (fill) map using ONS geographies

• Combining points and polygons on a single map

• How to add custom geometry (GeoJSON or WKT) to a map

• How to add a polygon reference layer to the map

• Using the lasso tool on the map to filter data

It’s possible to combine a point and a polygon layer on a single map. However, depending on your use case, the data model being used may need to be correctly formatted to make it work.

If your use case involves being able to filter point data but you need boundaries (polygons) to always display on the map, regardless of how the point data is filtered on the page, then see the .

If you need the polygons to also filter on the map then continue below.

For both points and polygons to be displayed on the map and also allow filtering based on user selections, both point and polygon data must come from the same data model. This can be achieved by either having both point and polygon data in the same data table or by using the Power BI data model view to link the data together.

Data can be combined outside of Power BI or by using built-in Power BI functionality –

If using Power BI’s data model view to relate data sets to one another, then the following Power BI help article may help – .

The visual has been designed so that clicking on a point or polygon on the map displays a pop-up with additional useful information about that location instead of filtering data in other visuals on the page.

The lasso tool allows you to filter the data on other visuals based on a selection taken from the map.

Categorical data is data that's divided into groups, such as age, gender, occupation, etc.

Creating a map of categorical data

To create a map of categorical data, you first need to plot the data points on a map. The previous page, Creating a point map, provides detailed instructions on how to add data points to a map.

Once you have created a point map, drag the column in your data that contains the different categories into the Point: Colour field of the visual. The map will automatically recolour the points based on the different categories in your data.

Varying the size of points

It’s quite common that you might want to vary the size (radius) of the points on a map to represent an increase in occurrence or density (for example, larger points represent a greater number of crimes at a location).

To do this, having plotted points on a map, drag a data column containing numeric data into the Points: Size field of the visual. Then click on the downward arrow of that field and select Count. Now the size of your points will be based off the total count of data points at the locations of your points.

See an example below showing a combination of categorical data (crime type) and point size variation (count of crime).

Adding clickable point pop-ups

Additional information about a point can be displayed as a pop-up when a point on the map is clicked.

To add a pop-up to a point on the map, drag and drop data into the Points: Pop-ups field in the Visualization pane. Information included in the pop-up field should be shown when a user clicks on a point.

Handling overlapping points on a map using pop-ups

It’s quite common that points on a map will overlap, making the data more difficult to understand. For example, when considering crime data, a shoplifting crime and a violent crime may have been recorded to the same x, y coordinates; however, one point will be plotted above the other and will therefore obscure some of the data.

By dragging a relevant column of data into the Point: Pop-ups field, you can click on a point on the map to reveal a pop-up and then paginate through all the underlying points that were originally obscured.

Below is an example of a pop-up where data representing crime type is being used to enable pagination of overlapping points; the pop-up shows there are five points representing different crime types in the same location:

Changing the colour of categorical data on a map

If you add a column of data containing textual data representing categories (for example, School, Library, Gym) into the Points: Colour field, the points on the map will automatically colour based on a default colour palette, and a legend will be generated on the map showing what colour represents what category (for example, School = Green).

However, the colours can also be customised by specifying hex codes within the data. The only way to change the colour of categorical data (points and polygons) is by specifying the relevant colour hex code (for example, #cdf1f0) in the data and dragging the column of data that represents the colours to be used into the relevant Points / Features: Colour field in the visual. There is currently no way for you to to customise the colours that are displayed for categories by default via the user interface.

It’s easy to create a choropleth (or fill) map using Office for National Statistics (ONS) geographies – Lower layer Super Output Areas (LSOAs), wards, etc. – in the OS Maps for Power BI Visual, without requiring a separate geometry file.

To make the following steps work, your data will need a column that includes ONS Government Statistical Service (GSS) codes.

Examples of LSOA codes are shown in the table below:

To display these geographies as polygons on a map, simply drag and drop the column of data that has these codes into the Features Layer: GSS identifiers geocoding field of the visual.

To colour the map and create the choropleth, drag the relevant column of data into the Features Layer: Colour field. This field can accept either numeric or text data. It’s important that every row within your data table has a GSS code (representing the polygon) and the relevant data to colour the polygon (numeric or text).

How to filter map boundaries by an overarching geography

It’s quite common that a report reader will want to view a defined geography (for example, a local authority such as Cardiff) but see data on the map that represents an underlying geography, such as wards. To do this, it’s important that the underlying data is structured in the correct way. Each row should have both the geography to be displayed on the map (for example, ONS ward code – W05001272) and the geography to filter by (the local authority that the ward code belongs to; which in this case is Cardiff). The data might look like the following table:

A filter can then be created to display the data, such as having a table listing the local authorities alongside the map. When a user clicks a local authority, the relevant wards and any associated data making up that local authority will be displayed on the map.

How to style a choropleth map

Once appropriate data has been dragged into the Features Layer: Colour field, then the map’s colours should update. To customise these colours, go into the Format Visual > Styling: Features Layer section.

By changing the Min or Max Feature Colours, the map colours will update based on the minimum and maximum values of the data used. Opacity can also be altered to style the map.

There are two valid data formats that the visual accepts to display custom geometry on the map – WKT and GeoJSON. These geometries need to be properly formatted within your data in order to be displayed on the map.

How to use WKT data to add custom geometry to a map

The OS visual supports the ability to add custom geometry onto the map.

It’s quite common that a user might have their geometry in GeoJSON, Shape or another format. These steps will demonstrate how to turn those formats into WKT that the visual will accept.

If you need to simplify your geometry, it’s best to do so at the start of this process. Load your geometry into a tool such as QGIS. Then, under Layers, right-click and select Export, then Save Feature as. Save your file as a CSV, then under ‘Geometry’ you want to select AS_ WKT.

Exporting your file as a CSV will create a file with every polygon listed as a separate entry alongside any additional metadata associated with those polygons from the original file. The WKT column in that CSV is what you’d drag into the Features Layer: GeoJSON or WKT Geometry in the OS Visual to display the geometry.

How to use GeoJSON data to add custom geometry to a map

This step may be easier to follow by navigating to the ‘Add Some Data Tab’ on the landing page then looking for the ‘GeoJSON’ section. The landing page can be accessed via the ‘Question Mark’ button in the bottom left.

There are two ways you can use GeoJSON in this visual:

Using a JSON formatted geometry column within a table

You can visualise features using a JSON formatted geometry column within a table - this can be just the geometry, for example:

 {"type": "Polygon", "coordinates": [...]}

or may be a Feature, for example:

 {"type": "Feature", "properties": {...}, "geometry": ...}

If the Feature has properties, these will be added to map popups by default, but will be replaced if a column is dragged into the Features Layer: Pop-ups field.

Load an entire GeoJSON file

This option requires some extra steps:

{" & """type""" & ":" & """" & [features.geometry.type] & """" & "," & """coordinates""" & ":" & Text.FromBinary(Json.FromValue([features.geometry.coordinates])) & "