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Polar plot

The Polar plot is suitable for comparing Data Values across Categories using a circular shape. It arranges categories along the circumference of the circle and encodes data values into circular sectors. You can also choose a method of dividing data values into subcategories within a containing category. The examples below emphasize Data Values with a bold font and Categories - with an italic font.

Simple Polar

In its simplest form, a polar plot displays one value per category. For instance, the simple polar demo shows the Sales Amount per Product Category.

Clustered Polar

A clustered polar plot breaks down data values into subcategories by placing corresponding circular sectors next to each other within the containing category. The Clustered Polar Demo shows the Sales Amount for each sales channel per Product Category.

Stacked Polar

A stacked polar plot is another way to break down data values into subcategories by dividing corresponding circular sectors into subsections. The Stacked Polar Demo shows the Sales Amount for each product category per Sales Channel.

Percentage Stacked Polar

A percentage stacked polar plot combines the stacked polar plot and the Percentage axis scale. It indicates the contribution of each data values' sub-category to a containing category's total. For instance, the Percentage Stacked Polar Demo shows the percentage share of the product categories' Sales Amount per Sales Channel.

You can configure all these types using the Polar plot template and its properties that we described in the following sections. The Stacked Polar and Percentage Stacked Polar templates are just shortcuts to a specific configuration.

You can use the following demos to explore the plot properties - open a link, toggle the Report explorer, select the Plot - Plot 1 node and use the Properties panel to modify the configuration.

You could also download the report files listed below and open them in the Standalone Report Designer.

Data Values

The Polar plot is used for comparing items, such as the net sales or the average rainfall. The plot's Values collection determine these items that consist of two properties:

  • The Value is usually a bound field reference. Note: This property is the collection, but the Polar plot takes the first item only.
  • The Aggregate is an optional function, such as Count or Average, that reduces many field values into a single one. If a Bound DataSet contains aggregated values, then you can set this property to None.

For instance, the plot in the Simple Polar Demo has the Value={SalesAmount}, Aggregate=Sum Data Value.

The Polar plot does not currently support multiple data values. Therefore the Values collection should always contain one item.

Category Encoding

The Category Encoding of a Polar plot is a set of properties that determine the range of Category Values for which the plot generates circular sectors representing those above Data Values.

  • The Category is usually one or more bound field references. Bound DataSet Records with the same values of these fields fall into the same category. For instance, the chart in the Simple Polar Demo is bound to the Sales DataSet containing several fields per data record including the ProductCategory. The plot's Category list contains the {ProductCategory} reference. Therefore the plot goes through the Sales DataSet and places distinct ProductCategory field values along the circle's circumference.

  • The Category Sorting configuration determines the order of the category values appearance. For instance, the plot in the Simple Polar Demo has the following settings to sort the product categories by the sum of sales in ascending order.

    • Category Sort Expression = {SalesAmount}
    • Category Sorting Aggregate = Sum
    • Category Sort Direction = Ascending

Details Encoding

The Details Encoding allows you to break down those above Data Values into subcategories within the containing category for more granular comparison. The Details property of a Polar plot is the collection of items that define these subcategories. Each item includes several properties:

  • The Values is usually one or more bound field references. Bound DataSet Records with the same values of these fields fall into the same subcategory. For instance, in the Stacked Polar Demo the plot's Details value is {ProductCategory}. Consequently, the SalesAmount circular sectors break down into multiple subsections corresponding to distinct product categories.
  • The Exclude Nulls flag indicates whether DataSet Records with an undefined Details Value should be excluded from the visualization.
  • The Group property determines how the plot arranges circular sectors divided into subsections.
    • Stack - a plot places subsections on top of each other. You can use this value to configure a Stacked Polar plot.
    • Cluster - subsections are clustered into groups. You can use this value to configure a Clustered Polar plot.
    • None - equals the default value.
  • The Sorting configuration determines the order of the subsections' appearance.

Colors Encoding

The Colors Encoding enables the color legend of the Category Encoding or Details Encoding and includes the Color expression and the optional Color Aggregate function that reduces many Color values into a single one.

Suppose the Details Encoding is empty. In that case, a Polar plot calculates distinct Color Encoding results for the categories produced by the Category Encoding, convert them to the background color of the corresponding circular sectors, and displays the match in the legend.

Otherwise, the plot calculates distinct Color Encoding results for the subcategories produced by the Details Encoding, converts them to the background color of the corresponding subsections, and displays the match in the legend.

In both cases, plots pick up colors from the Chart Palette.

For instance, the colors encoding in the Clustered Polar Demo is set to the {SalesChannel} expression. Consequently, the report output shows the legend that matches Sales Channels with corresponding subsections background.

In most cases, you will use the same configuration for both Details Encoding and Colors Encoding to enable a visual map of data values breakdown.

Note: The Color property is the collection, but the Polar plot takes the first item only.

Polar look-and-feel

The following properties allow you to fine-tune the outfit of geometrical shapes that form Polar plots. You can see their effect in action by modifying the configuration of polar plot demos.

The Opacity is a Number in percentage that determines the opacity of circular sectors. 100% means they are opaque, and 0% means that they are completely transparent.

The Inner Radius is a number in the percentage of the outer radius that defines the size of a hole in the center of the plot.

The Start Angle is a number in arcdegree that defines the rotation of the plot clockwise. Full rotation is 360 degrees. In all the polar plot demos, this property is set to 90.

The Sweep is a number in arcdegree from 0 to 360 that determines the arc length occupied by the plot. In all the polar plot demos, this property is set to 360, the default value.

The Clipping Mode indicates the manner that the plot area draws a plot:

  • Fit value means that the plot area should use all the available space to fit the plot. All the polar plot demos use this value.
  • Clip value means that the plot area cuts off the plot on the edge of its right or bottom padding
  • None value equals to Fit

The line properties in the Style section determine the appearance of circular sectors borders.

The color expression in the Background section sets the fill color of circular sectors and overwrites the Color Encoding described earlier.

Tooltip and Labels Template

Circular bars can display tooltips and labels with the following content that you can set up using the Tooltip Template and Label Text Template expressions, respectively.

You can choose one of the following values in the drop-down list.

  • Value Field Name usually means the field name bound to a Data Value.
  • Value Field Value means the current Data Value within the containing Category or Details.
  • Percentage In Details means the percentage share of the current Data Value among all the values with the same Details.
  • Details Field Name usually means the field name bound to the Details Encoding.
  • Details Field Value means the current Details Encoding value.
  • Color Field Name usually means the field name bound to the Color Encoding.
  • Color Field Value means the current Color Encoding value.

Also, you could use the template's Expression Editor to set the formatting for these values using the interpolation syntax and supported formatted strings. For instance, you can set the Label Text Template to {valueField.value:C2} in one of the polar plot demos to display Sales Amount values as currency.

Labels Appearance

A subset of text properties in the Label Text section and the line properties in the Label Border section allow you to set up the corresponding visual parameters of the plot labels.

The Label Position and an optional Offset in pixels determine the location of labels relative to a parent circular sector:

  • Inside - on the edge
  • Outside - outside
  • Center - inside, on the center
  • Auto - equals to Outside

The Overlapping Labels property indicates the handling of overlapping labels. Possible values are:

  • Auto - hides some labels to prevent the overlapping
  • Show - shows all labels even if the overlapping persists

The line properties in the Label Line section allows you to add the connecting lines between labels and their parent circular bars. The Label Line Position determines the starting point of the line relative to the sector:

  • Auto - on the edge
  • Center - on the center

Action

This properties determine the Interactive Action when a report reader clicks inside a circular sector. You can use bound field references to pass parameters in a drill-through report or configure a dynamic bookmark or URL. The field value is evaluated in the scope of the current detail. Visit the Drill-Through Reports Walkthrough for more information. It explains how to set up the drill-through column plot, but the same technique applies to a polar plot.