DataClock

Summary

Data clocks visually summarize temporal data into two dimensions to reveal seasonal or cyclical patterns and trends over time.

Learn more about data clocks in ArcGIS Pro

Discussion

When creating a chart object, optional arguments for the class constructor must be specified using the argument name; they cannot be specified by argument position. See the code sample section for an example of how to specify arguments using keywords.

Syntax

DataClock (dateField, {numberField}, {timeUnitsRingWedge}, {aggregation}, {nullPolicy}, {classificationMethod}, {classCount}, {title}, {description}, {dataSource}, {displaySize})
ParameterExplanationData Type
dateField

The name of the date field that is used to create the chart.

String
numberField

The name of the field that is aggregated and used to determine the color of the chart cells.

String
timeUnitsRingWedge

The description for the time-unit pair supported in the data clock chart. The following options are supported:

  • YEARS_MONTHS
  • YEARS_WEEKS
  • YEARS_DAYS
  • WEEKS_DAYS
  • DAYS_HOURS

String
aggregation

The statistical calculation applied to values aggregated into each cell. Supported statistics are COUNT, SUM, MEAN, MEDIAN, MIN, and MAX.

String
nullPolicy

How summarized cells returning a null value are displayed. Supported options are null and zero.

String
classificationMethod

The classification method used to visualize cell color. Supported options are equalIntervals, geometricalIntervals, naturalBreaks, and quantiles

String
classCount

The number of classes used in the classification method.

Integer
title

Sets the title of the chart. The title text appears at the top of the chart view and is used as the label for the chart in the Contents pane.

String
description

Sets the description of the chart. The description text appears at the bottom of the chart view.

String
dataSource

Sets the data source of the chart. When a chart is exported using the exportToSVG method or displayed in an ArcGIS Notebook, the data source is read and rendered on the chart. Valid data sources include paths to datasets, including local datasets, UNC paths, and service URLs, and arcpy.mp Layer objects.

Object
displaySize
[displaySize,...]

Sets the size of the chart when exported using the exportToSVG method or displayed in an ArcGIS Notebook. The value must be specified as a two-item list, where the first item is the width of the chart and the second item is the height of the chart.

List

Properties

PropertyExplanationData Type
aggregation
(Read and Write)

The statistical calculation applied to values aggregated into each cell. Supported statistics are COUNT, SUM, MEAN, MEDIAN, MIN, and MAX.

String
classCount
(Read and Write)

The number of classes used in the classification method.

Integer
classificationMethod
(Read and Write)

The classification method used to visualize cell color. Supported options are equalIntervals, geometricalIntervals, naturalBreaks, and quantiles.

String
dataSource
(Read and Write)

Sets the data source of the chart. When a chart is exported using the exportToSVG method or displayed in an ArcGIS Notebook, the data source is read and rendered on the chart. Valid data sources include paths to datasets, including local datasets, UNC paths, and service URLs, and arcpy.mp Layer objects.

Object
dateField
(Read and Write)

The name of the date field that is used to create the chart.

String
description
(Read and Write)

Sets the description of the chart. The description text appears at the bottom of the chart view.

String
displaySize
(Read and Write)

Sets the size of the chart when exported using the exportToSVG method or displayed in an ArcGIS Notebook. The value must be specified as a two-item list, where the first item is the width of the chart and the second item is the height of the chart.

List
legend
(Read and Write)

Sets the properties of the chart legend.

  • visible—Indicates whether the legend is visible in the chart view. True displays the legend. False hides the legend.
  • title—The title to display for the legend.
Object
nullPolicy
(Read and Write)

How summarized cells returning a null value are displayed. Supported options are null and zero.

String
numberField
(Read and Write)

The name of the field that is aggregated and used to determine the color of the chart cells.

String
timeUnitsRingWedge
(Read and Write)

The description for the time-unit pair supported in the data clock chart. The following options are supported:

  • YEARS_MONTHS
  • YEARS_WEEKS
  • YEARS_DAYS
  • WEEKS_DAYS
  • DAYS_HOURS

String
title
(Read and Write)

Sets the title of the chart. The title text appears at the top of the chart view and is used as the label in the Contents pane on the List By Drawing Order tab List By Drawing Order.

String
type
(Read Only)

The string value indicating the chart type.

String

Method Overview

MethodExplanation
addToLayer (layer_or_layerfile)

Adds the chart object to a layer or stand-alone table.

exportToSVG (path, width, height)

Exports the chart to SVG format.

updateChart ()

Updates chart properties to sync changes between the object and the chart previously added to a layer.

Methods

addToLayer (layer_or_layerfile)
ParameterExplanationData Type
layer_or_layerfile

The chart will be added to the target object. The layer_or_layerfile argument can be a Layer or a Table object.

Object

Often the final step after defining chart properties is to add the chart object to a layer or table using the addToLayer method.

Add a chart to an existing layer.

import arcpy

aprx = arcpy.mp.ArcGISProject("current")
map = aprx.listMaps()[0]
censusLayer = map.listLayers('Census Block Groups')[0]

# Add chart object to a layer
chart.addToLayer(censusLayer)
exportToSVG (path, width, height)
ParameterExplanationData Type
path

The path where the chart will be exported in SVG format.

String
width

The width of the output graphic.

Integer
height

The height of the output graphic.

Integer

In some cases, you may want to save the chart as a graphic that can be shared and viewed outside of ArcGIS Pro. Exporting to the SVG graphic format is beneficial, as the chart elements and text are stored as vector elements that can be independently modified in a vector graphics software. An SVG graphic can also be resized to any scale without pixelation or loss in quality.

Export a chart that has a project layer data source to an .svg file.

import arcpy

aprx = arcpy.mp.ArcGISProject('current')
censusLayer = aprx.listMaps()[0].listLayers('Census Block Groups')[0]

# Set data source of chart object to a layer within current project
chart.dataSource = censusLayer

# Save the chart to file with dimensions width=500, height=500
chart.exportToSVG('populationByState.svg', 500, 500)

Export a chart that has a feature service data source to an .svg file.

featureServiceURL = r'https://services1.arcgis.com/hLJbHVT9ZrDIzK0I/arcgis/rest/services/CrimesChiTheft/FeatureServer/0'

# Set data source of chart object to a feature service URL
chart.dataSource = featureServiceURL

# Save the chart to file with dimensions width=800, height=600
chart.exportToSVG('theftsPerBeat.svg', 800, 600)
updateChart ()

Often the final step after defining chart properties is to add the chart object to a layer using the addToLayer method.

To further modify the chart properties, you can modify the properties of the original chart instead of starting from scratch with a new chart. You can then use the updateChart method to synchronize any changes into the chart that was added to the layer. This will allow the changes you make to be presented in the Chart properties pane and chart view.

Use the updateChart method to synchronize chart property changes into a layer.

chart.addToLayer(myLayer)

# Further modification is necessary
chart.description = "Data from the U.S. Census Bureau"
chart.updateChart()

Code sample

Create a data clock chart using a layer in the current project and export the chart to an .svg file.

import arcpy
lyr = arcpy.mp.ArcGISProject("current").listMaps()[0].listLayers("car_accidents")[0]
chart = arcpy.charts.DataClock(dateField="Date", aggregation="count", 
                               timeUnitsRingWedge="WEEKS_DAYS", dataSource=lyr)
chart.exportToSVG("data_clock.svg", width=750, height=500)