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Google heat map

Overview

This chart displays the density of data points on a geographical map through latitude and longitude coordinates and helps you see the intensity of phenomena visualized through a color scale. Information can be clustered on the map by an optional additional value.

These are useful when you need to analyze big geographical datasets. They are especially suited to display indicative trends at a high level. Patterns can be identified quickly, and relevance determined for even the largest datasets.

What data do I need for this widget?

The option to create this map will be disabled unless your query contains at least three columns with numeric values. Furthermore, to show meaningful content on the map, two of those columns must correspond to longitude and latitude and you must group your data.

Creating a Google heat map

Working with Google heat maps

To change the visualization style use the options at the bottom:

  • Map: click it to activate the street map view.
    Upon activation of this option, the Terrain option is displayed with a checkbox for you to mark. When marked, the map is displayed together with the topographic features.

  • Satellite: Click it to activate the satellite imagery.
    Upon activation of this option, the Labels option is displayed with a checkbox for you to mark. When marked, the map is displayed together with the geo-political namings.

To change the visualization area you can perform the following actions:

  • Click the + button to zoom in.

  • Click the - button to zoom out.

  • Left-click and drag to pan the map to the desired area.

  • Double-click to zoom in.

  • Double-right-click to zoom out.

  • Click the button at the top right to toggle fullscreen mode.

You can hit the following keys to perform different visualization actions:

Shortcut keys

Description

Shortcut keys

Description

w

Increases the radius of the heat points.

s

Decreases the radius of the heat points.

a

Increases the color gradient for temperature representation. This will change the color scale for another with a different base color and number of colors to represent the lowest/coldest and highest/warmest. When you get to the las available gradient, pressing the key will go back to the first.

This might be useful when the values are very similar and belong to the same range so they would be represented in the same or very similar color. This way we might be overlooking the differences in the values because of the lack of contrast and changing the gradient could help so that the values would be represented differently.

l

Applies a logarithmic operation to normalize the data, which will be reflected in the heat areas on the map. This might be useful when some values are too far from the general range so normalization is needed for a more cohesive representation. 

t

Applies an arctangential operation to normalize the data, which will be reflected in the heat areas on the map. This might be useful when some values are too far from the general range so normalization is needed for a more cohesive representation. 

n

Resets configuration to revert the applied operations.

p

Shows/hides a legend with the element added in the partitioning field.

f

Shows only visible elements. This acts as a switch that applies the temperature scale only to the elements inside the displayed area or to all of them, even if they cannot be seen. This might be helpful in a specific approach to spot the hottest points per geographical area or in a global approach to maintain the perspective regardless of the zoom applied.

?

Shows/hides the list of shortcut keys.

Query example

You can recreate the example shown in the picture above using the data of the following query and mapping the fields as follows:

Query

Required field

Column added

Query

Required field

Column added

from demo.ecommerce.data select mmlatitude(clientIpAddress) as latitude, mmlongitude(clientIpAddress) as longitude group every 1m by latitude, longitude, method, timeTaken every 1m

Longitude

latitude

Longitude

longitude

Size/Color

timeTaken

Partitioning

method