Heatmap
allows you to visualize large amounts of data as clustered rectangles with a color scale.
Figure: Default Heatmap visualization showing city wise stocks count for each ship city
Figure: Heatmap visualization after various customizations
NOTE: Before adding the Heatmap widget to the design layout, make sure to create the data source. You can refer to this section to learn how to create a new data source.
IMPORTANT: To showcase a Heatmap, a minimum requirement of
one value
andtwo groups
by the field is needed.
The following steps explains about data configuration of the Heatmap.
Drag and drop the Heatmap
control icon from the tool box into design panel. You can find control in tool box by search.
Resize the widget as required.
Click the Properties
icon in the configuration panel.
The properties panel of the widget will be displayed as shown in the following screenshot. Now, switch to the ASSIGN DATA
tab.
The data tab will be opened with available columns from the connected data source.
Bind column by dragging and dropping the element from sections to values
.
NOTE:
Drag and drop the elements from sections to X-Axis
section.
NOTE:
Drag and drop the elements from sections to Y-Axis
section.
NOTE:
Image: Heatmap widget after configuring the mandatory fields.
Drag and drop the elements from sections to size
section. It will define the size of the bubble in the heatmap. Also, it is an optional section.
Image: Heatmap widget after configuring the size field
You can configure tooltip
section to showcase the additional information in the widget’s tooltip without affecting the visualization. Refer to this section for more details on configuring the tooltip fields.
You can filter
, format
, and sort
the data displayed in the widget from the settings menu options. To open the settings menu, click the settings
icon.
The following screenshots shows the various settings menu options based on the type of field configured in the type of section.
You can change the aggregation type
of the measure
section from the settings menu as shown in the following screenshot. Refer to this section for more details.
When the second value is added to the x-axis or y-axis section, the alert message will be shown.
Click Yes
to enable the option. If you click No,
then a single value will be added to the respected section( x-axis or y-axis).
Figure: Heat Map with a drilled view of the selected region.
You can use Filters to change the values by selecting the Filter
option. For more details, refer to Measure filter and dimension filter.
You can format the elements by selecting the Format
option. For more details, refer to measure format.
The configured field names can be edited by using the Rename
option provided in the settings
menu.
Click the Settings menu icon and select the Rename
menu option.
The column name will become editable now. Enter the required text and press enter
key.
Now, the changes will be reflected in the Heatmap widget’s tooltip and in the axes titles.
You can format the Heatmap
for better illustration of the view that you require using the settings available in the Properties
tab.
This allows you to set title
for this Heatmap widget.
This allows you to set subtitle
for this Heatmap widget. It is optional.
This allows you to set brief explanation about this Heatmap widget. It is optional.
This allows you to toggle the visibility of value labels.
This allows you to apply the specified radius to cell corners. Value ranges from 0 to 10. The Default value is 3
.
This allows you to toggle the visibility of border surrounding the cell. Value ranges from 0 to 10. Default value is 1
.
This allows you to configure a single-color palette whose saturation will be varied based on the value density.
Across Table: Monochromatic color applied based on the whole table minimum and maximum data values.
Column Wise:Monochromatic color applied based on the individual column wise minimum and maximum data values.
Row Wise: Monochromatic color applied based on the individual row wise minimum and maximum data values.
Select Advance setting to configure conditions and apply color to the cells based on that. Click here for more details.
This allows you to toggle the visibility of legend in the heatmap. By default, it will be disabled.
This allows you to change the legend position (selecting through the combo box).
This allows you to enable the visibility of x-axis labels.
This allows you to change the x-axis label color.
This allows you to enable the visibility of x-axis title.
This allows you to edit the x-axis title for the heatmap. It will reflect in the x-axis title of the heatmap.
This allows you to define the rotation angle for x-axis labels to display.
This allows you to handle the display mode of overlapping labels in the x-axis.
This option did not trim the end of overlapping label in the axis.
This option trims the end of overlapping label in the axis.
This allows you to change the axis label’s placement order from left to right in the x-axis.
This allows you to change the axis position from bottom to top in the x-axis.
This allows you to enable the visibility of y-axis labels.
This allows you to change the y-axis label color.
This allows you to enable the visibility of y-axis title.
This allows you to edit the x-axis title for the Heatmap. It will reflect in the y-axis title of the Heatmap.
This allows you to change the axis label’s placement order from bottom to top in the y-axis.
This allows you to change the axis position from left to right in the y-axis.
To configure the linking to URL or dashboard with the widget using its settings. For more details, refer to Linking.
This allows you to define the Heatmap widget as a master widget, such that its filter action can be listened by other widgets in the Dashboard.
This allows you to define the Heatmap widget to ignore responding filter actions applied on other widgets in the Dashboard.
Using this option, you can enable or disable the hierarchical Top N filtering. While applying Top N filter with multiple dimension columns, the returned data can be customized based on whether the filtering need to be done as flat or hierarchy of added dimension columns.
When the hierarchical filter option is enabled, the Top N will be applied for each individual column separately based on the number set for each column.
This section contain the property for pivot grid container’s layout.
This allows you to customize the widget container appearance, widget title’s properties and provides options to enable/ disable widget exporting options. For more detailed information, refer to container appearance properties.
In case, if you have the requirement to highlight any data based on some conditions, you might be required to enable the advanced formatting option.
In the properties pane, under the Formatting
section, click the Advanced Setting
radio button.
This will open the Conditional Formatting
dialog.
Select the mode
and enter the conditions as required and click the Save
button to apply.
Now, the widget visualization will be updated based on the conditions.
Refer to the following sections for the detailed steps on using the Gradient
and Rule
modes.
You can customize the fill color of the heatmap using the gradient based conditional formatting. This is the default mode.
The configured value fields. Based on field cannot be changed in the conditional formatting dialog.
The summary type of the configured value field.
You can define your range by entering the low, mid, and high values.
NOTE: It is optional, if no value is entered, then the ranges will be auto calculated based on the minimum and maximum values from the data source.
If the region of Heatmap value is out of the specified range, then the color specified in the default color will be applied.
This allows you to customize the fill color of the Heatmap based on one or more numerical / text conditions.
You can give a meaningful name to the applied conditions.
Choose the condition for measure field from the highlighted conditions.
You can mention the condition value.
Select the fill color for that condition using the color picker.
Click add condition to specify add new condition.
Click the delete button to remove the existing condition.
Cohort visualization examines the outcomes of predetermined groups, called cohorts, as they progress through a set of stages. The signature characteristic of a cohort is its comparison of the change in a variable across two different time series. A cohort is a group of people sharing common characteristics over a specified period and it’s helps for decision making purpose.
Drag and Drop the heatmap widget and bind the measure values in it.
Go to Formatting section
and change the drop down value to Row Wise
.
Above screenshot shows cohort visualization in heatmap widget.