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Chart Visualization ​

Transform spatial data into visual charts and graphs for analysis and reporting.

Overview ​

Built on Chart.js with integration to ArcGIS API for JavaScript v4.34.8, supporting 5 chart types and multi-series visualization.

Technical Foundation:

  • Chart Engine: Chart.js with ArcGIS data integration
  • Chart Types: 5 types (category-based and scatter charts)
  • Performance: Client-side processing up to 2000 features
  • Category Limit: Maximum 50 categories per chart
  • Color Palette: 10 ArcGIS-compatible colors

Chart Capabilities:

  • 5 chart types: Bar, Pie, Line, Scatter, Radar
  • Multi-series support: Combine data from multiple layers with independent filtering
  • 5 aggregation functions: Count, Sum, Average, Min, Max
  • Layer compatibility: All layer types for category-based charts; pure FeatureLayer required for histogram/scatter/boxPlot
  • Field type support: Category fields (string, integer, date, oid), Value fields (integer, double, single)
  • Filtering per series: Independent SQL-based filters for each data series
  • Category value selection: Choose which category values to include in visualization

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Access Chart Visualization ​

Location: Analysis toolbar → Chart icon

How to Open:

  1. Click Chart Visualization icon in toolbar
  2. Panel opens
  3. Add series to build chart

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Chart Types (10 Available Types) ​

Category-Based Charts (Work with All Layer Types) ​

Bar Chart ​

Best For: Comparing values across categories

Field Requirements:

  • Category fields: 1 required (string, integer, date, oid)
  • Numeric fields: 1+ (multi-select for multi-series)
  • Aggregation: Required (count, sum, avg, min, max)

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Examples:

  • Property counts by zoning type (aggregation: count)
  • Total land area by suburb (aggregation: sum)
  • Average property value by zone (aggregation: avg)

Technical: Supports multiple numeric fields for multi-series comparison.

Line Chart ​

Best For: Display trends over sequence (time series or ordered categories)

Field Requirements:

  • Category fields: 1 required (typically date or sequential field)
  • Numeric fields: 1+ (multi-select for multi-series)
  • Aggregation: Required

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Examples:

  • Development applications by year
  • Monthly inspection completions
  • Asset condition trend over time

Technical: Supports multiple numeric fields for trend comparison.

Pie Chart ​

Best For: Show part-to-whole relationships

Field Requirements:

  • Category fields: 1 required
  • Numeric fields: 0+ (optional - can use count aggregation)
  • Aggregation: Required

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Examples:

  • Zoning distribution percentages
  • Asset type proportions (using count aggregation)
  • Land use breakdown by area

Technical: Best with 3-7 categories for readability (maximum 50 categories enforced).

Radar Chart ​

Best For: Multi-variable comparison across categories

Field Requirements:

  • Category fields: 1 required
  • Numeric fields: 1+ (multi-select for multi-dimensional view)
  • Aggregation: Required

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Examples:

  • Asset condition scores across multiple criteria
  • Development compliance metrics
  • Service quality ratings by department

Technical: Displays multiple numeric fields as axes radiating from center.

Specialized Charts (Work with All Layer Types) ​

Gauge ​

Best For: KPI or single value display with min/max range

Field Requirements:

  • Category fields: 0 (no categories)
  • Numeric fields: 1 (single-select only)
  • Aggregation: Required

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Examples:

  • Total property value in district
  • Asset count reaching threshold
  • Budget utilization percentage

Technical: Single numeric value with visual gauge representation.

Heat Chart ​

Best For: Cross-tabulation of two categories showing magnitude

Field Requirements:

  • Category fields: 2 required (X and Y axes)
  • Numeric fields: 1 (single-select only)
  • Aggregation: Required

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Examples:

  • Asset type vs. condition rating (showing count)
  • Suburb vs. zoning type (showing total area)
  • Department vs. inspection status (showing count)

Technical: Matrix visualization with color intensity representing aggregated values.

Combo Bar-Line ​

Best For: Compare series with bars and lines (e.g., actual vs. target)

Field Requirements:

  • Category fields: 1 required
  • Numeric fields: 2+ (first as bars, subsequent as lines)
  • Aggregation: Required

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Examples:

  • Actual vs. planned inspections by month
  • Property sales (bars) vs. median price trend (line)
  • Asset replacements (bars) vs. budget allocation (line)

Technical: Combines bar chart for primary data and line overlay for comparison.

Feature-Only Charts (Require Pure FeatureLayer) ​

Histogram ​

Best For: Display value distributions and frequency

Field Requirements:

  • Category fields: 0 (bins auto-generated from value distribution)
  • Numeric fields: 1 (single-select only)
  • Aggregation: Not shown (automatic binning)

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Examples:

  • Property value distribution
  • Asset age distribution
  • Land parcel size frequency

Technical: Requires FeatureLayer (not MapImageLayer). Automatically bins numeric values into ranges.

Scatter Plot ​

Best For: Show correlation between two numeric fields

Field Requirements:

  • Category fields: 0 (each point is a feature)
  • Numeric fields: 2 (X and Y axes)
  • Aggregation: Not shown (plots individual features)

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Examples:

  • Property size vs. value correlation
  • Distance from CBD vs. sale price
  • Asset age vs. maintenance cost

Technical: Requires FeatureLayer. Plots raw feature values without aggregation.

Box Plot ​

Best For: Statistical distribution by category (quartiles, median, outliers)

Field Requirements:

  • Category fields: 1 required
  • Numeric fields: 1+ (multi-select for multiple distributions)
  • Aggregation: Not shown (calculates quartiles automatically)

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Examples:

  • Property values by suburb (showing median, quartiles, outliers)
  • Asset condition scores by asset type
  • Inspection times by inspector

Technical: Requires FeatureLayer. Shows statistical distribution with min, Q1, median, Q3, max, and outliers.

Building Charts ​

Basic Workflow ​

Step 1: Add Chart Series

  1. Click "Add Series" button
  2. Series card appears
  3. Configure series settings

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Step 2: Select Data Source

  1. Choose layer from dropdown
  2. Only visible layers available

Step 3: Configure Fields

  1. Category Field: X-axis grouping (e.g., ZONE_CODE, SUBURB)
  2. Value Fields: Y-axis data (numeric fields)

Step 4: Choose Aggregation (5 aggregation types available)

  • Count: Count of features per category
  • Sum: Total of values in category
  • Average: Mean value per category
  • Minimum: Lowest value in category
  • Maximum: Highest value in category

Technical Notes:

  • Aggregation applies to each category independently
  • Count aggregation doesn't require numeric field selection
  • Other aggregations require numeric field types: integer, double, single, small-integer, long

Step 5: Select Chart Type Choose from dropdown: Bar, Pie, Line, Scatter, Radar

Step 6: Generate Chart Click "Generate Chart" button

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Multi-Series Charts ​

Purpose ​

Combine data from multiple layers or field combinations in one chart.

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Use Cases:

  • Compare zoning across multiple suburbs
  • Show asset conditions for different asset types
  • Overlay planned vs. actual values

How to Add Multiple Series ​

Steps:

  1. Configure first series (Layer A, Field X)
  2. Click "Add Series" again
  3. Configure second series (Layer B, Field Y)
  4. Each series shown with distinct color
  5. Legend identifies each series

Example: Zoning Comparison

Series 1:
├── Layer: Zoning
├── Category: ZONE_CODE
├── Value: AREA_HA
├── Aggregation: Sum
└── Label: "Existing Zoning"

Series 2:
├── Layer: Proposed_Zoning
├── Category: ZONE_CODE
├── Value: AREA_HA
├── Aggregation: Sum
└── Label: "Proposed Zoning"

Result: Side-by-side bars comparing existing vs. proposed

Filtering Chart Data ​

Per-Series Filtering ​

Each series can have independent filter.

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Filter Options:

  • Enable/Disable filter
  • Choose field to filter on
  • Select operation (=, >, <, etc.)
  • Enter filter value

Example: High-Value Properties Only

Series: Property Parcels
Filter: LAND_VALUE > 500000

Result: Chart shows only properties valued over $500k

Category Value Filtering ​

Select which category values appear in chart.

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Use Cases:

  • Remove "Unknown" or "N/A" categories
  • Focus on top 5 categories only
  • Compare specific suburbs only

Chart Customization ​

Titles and Labels ​

Auto-Generated Titles:

  • Format: "Layer Name - Field Name"
  • Can be customized per series

Axis Labels:

  • X-axis: Category field name
  • Y-axis: Aggregation type + field name

Colors ​

Default Color Palette (10 ArcGIS-compatible colors):

  1. #007ac2 - ArcGIS Blue
  2. #00a884 - Teal
  3. #e4a839 - Gold
  4. #d83020 - Red
  5. #8a5a83 - Purple
  6. #4d9221 - Green
  7. #c4652d - Orange
  8. #2b83ba - Light Blue
  9. #d7191c - Bright Red
  10. #fdae61 - Light Orange

Series Colors:

  • Auto-assigned from palette in sequence
  • Colors cycle if more than 10 series
  • Customizable per series in chart configuration

Best Practices:

  • Use contrasting colors for multiple series
  • Default palette optimized for accessibility and print
  • Avoid red/green for colorblind accessibility

Legend ​

Interactive Legend:

  • Appears above or beside chart
  • Click legend item to hide/show series
  • Hidden series excluded from calculations

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Export and Share ​

Export Chart as Image ​

Formats:

  • PNG (recommended)
  • JPG

How to Export:

  1. Generate chart
  2. Right-click chart
  3. Select "Save image as..."
  4. Choose location and filename

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Chart Workflows ​

Workflow 1: Zoning Area Summary ​

Scenario: Show zoning distribution for planning report

Steps:

  1. Add series: Layer=Zoning, Category=ZONE_CODE, Value=AREA_HA, Agg=Sum
  2. Select chart type: Pie
  3. Filter category values (remove "N/A")
  4. Generate chart
  5. Export as PNG

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Workflow 2: Asset Condition Comparison ​

Scenario: Compare asset conditions across different asset types

Steps:

  1. Add series for each asset type with filter
  2. Chart type: Bar (grouped)
  3. Generate chart
  4. Export for presentation

Performance Tips ​

Technical Limits:

  • Features: 2000 features maximum for client-side processing
  • Categories: 50 categories maximum per chart for performance
  • Exceeding these limits may cause slow rendering or browser performance issues

For Large Datasets:

  • Apply layer filters before charting to reduce feature count below 2000
  • Limit category values to top 10-20 for readability (enforced at 50 max)
  • Use Count aggregation (fastest - no numeric field processing)
  • Avoid too many series (recommended max 5-7 for chart clarity)
  • Use server-side queries when possible to pre-aggregate data
  • Consider using definition queries on layers to permanently filter data

Field Type Selection:

  • Category fields: string, integer, small-integer, oid, date
  • Value fields: integer, double, single, small-integer, long
  • Invalid field types automatically excluded from field selectors

Troubleshooting ​

"No data to display" ​

Causes:

  • Layer has no features
  • Filter too restrictive
  • Value field empty

Solutions:

  • Check layer has visible features
  • Remove or broaden filter
  • Choose different value field

"Chart looks cluttered" ​

Causes:

  • Too many categories
  • Too many series

Solutions:

  • Filter to top N categories
  • Use category value selection
  • Reduce number of series

Summary ​

Chart Visualization transforms GIS data into visual insights using ArcGIS Charts Components.

10 Chart Types:

  • Category-based (all layers): Bar, Line, Pie, Radar
  • Specialized (all layers): Gauge, Heat Chart, Combo Bar-Line
  • Feature-only (FeatureLayer required): Histogram, Scatter Plot, Box Plot

Technical Specifications:

  • Performance limits: 2000 features max, 50 categories max
  • 5 aggregation types: Count, Sum, Average, Min, Max
  • 10-color palette: ArcGIS-compatible colors
  • Field type support: Category (string, integer, date, oid), Value (integer, double, single)
  • Layer compatibility: FeatureLayer, MapImageLayer, and all other layer types for category-based charts

Key Features:

  • Multi-series support with independent configuration
  • Per-series filtering with SQL expressions
  • Category value selection (include/exclude specific values)
  • Interactive legends (click to hide/show series)
  • Automatic chart generation from layer attributes
  • Export as PNG/JPG images

Best For:

  • Planning reports with zoning statistics
  • Executive summaries with KPI gauges
  • Trend analysis over time
  • Asset condition comparisons
  • Property value distribution analysis
  • Multi-dimensional performance metrics
  • Budget presentations
  • Asset management

Remember: Keep charts simple (3-7 categories), use appropriate chart types, and apply filters to focus on relevant data.