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What is a Geographic Heat Map?
Geographic heat maps, also known as density maps, offer a vivid visual representation of data using colour gradients to indicate the density or intensity of a specific variable across a given geographic area. In areas with higher intensity or density, the colours appear more vivid or darker, while lower-density areas are represented by lighter shades.
These maps are invaluable for visualising a wide range of data types—be it population density, crime rates, pollution levels, customer footfall or any other geographically-referenced metrics. By utilising color gradients to signify varying levels of intensity, geographic heat maps furnish quick, intuitive insights, making it easy to pinpoint patterns, hotspots or areas that warrant closer investigation.
Creating these maps is increasingly accessible, thanks to no-code software options like Tableau and Alteryx, which enable users to craft meaningful visualisations effortlessly.
Facilitating in Tableau
1. Open Tableau Desktop and connect to the data source. Make sure the data includes geographic information such as latitude and longitude or location names (if recognised as location names by Tableau, for example, United States).
2. Drag the longitude field to the columns shelf and the latitude field to the rows shelf. A map view will be automatically generated.
3. Drag the measure to be visualised as a heat map to the colour card. This could be a numerical value that represents density, intensity or any other metric the user wants to display.
4. On the marks card, change the mark type to density. Tableau will automatically generate a density map based on the selected geographic field. The map can be further refined by customising colours (choosing a different colour palette), adding labels or adjusting the size of the marks.
5. To enhance the heat map, users can add additional dimensions to provide context or filter the data based on specific criteria.
6. Apply any formatting or styling options as desired. Change the background map style, adjust the colour intensity of data points, or customise tooltips to make the heat map more visually appealing and informative.
Facilitating in Alteryx
1. Import the data into Alteryx using the Input Data Tool and select the data source. Ensure the data contains geographic information in the form of latitude and longitude coordinates or addresses. It is ideal to filter the dataset using the Filter Tool to include only the relevant details needed. Large datasets may affect performance and slow down the rendering of the heat map.
2. Use the Create Points Tool to convert the coordinates into a spatial object that Alteryx can recognise. In the tool configuration, choose the appropriate fields for latitude and longitude. This allows the user to create the heat map.
3. Add a Filter Tool to remove any null centroids. Add the Heat Map Tool to the workflow and connect the spatial object created in step three to the Heat Map Tool’s input. Users can also adjust parameters such as the grid size, maximum distance and output type to suit business requirements.
4. Use the Browse Tool to view the geographic heat maps output. This will display the heat map on a map interface, showing areas with varying levels of intensity based on your data values. This allows users to explore different styles and colour palettes by selecting the base map dropdown list to customise the appearance of the heat map.
The output of the heat map are polygons which represent different levels of heat, with the fields – “Tile_Num”, “Tile_Name” and “SpatialObj”.
5. In the Report Map Configuration under Data Tab > Incoming Connections > #1, select “Tile_Num” as the thematic field and “Tile_Name” as the label field. This will assign colours to the heat map according to the “Tile_Num”.
Under the Layers Tab, add a polygons layer (#1) and set the theme to the following:
Tile Method: Smart Tile
Colour Method: Ramp
Start Colour: Blue
End Colour: Red
6. Alternatively, users can use the Report Map Tool to visualise the heat map and output it into a PDF Document using the Render Tool. This can be helpful when presenting findings to others or when incorporating them into reports or presentations.
A PDF document with the geographic heat map and legend will be generated.
7. To improve the visualisation of the map, output the spatial points as a Tableau Data Extract (.tde). Using the Output Data Tool visualise it in Tableau by dragging the Spatial Object created to the detail card and Tile Name to the colour card.
Not sure what heat map you should be using? Check out our Heat Maps 101 post to get caught up!
