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Line Widget

Line Widget

Overview

The Line widget displays connected data points as a line, perfect for showing time series data, trends over periods and visualizing continuous data development. It's one of the most commonly used widgets for temporal data.

Use Cases

  • Time Series - Display measurements over time
  • Trend Analysis - Identify trends and patterns
  • Multiple Measurements - Compare multiple measures simultaneously
  • Historical Data - Review historical trends
  • Real-Time Monitoring - Track live data streams

Key Features

  • Smooth line rendering
  • Multiple line series
  • Area fill option
  • Zoom and pan
  • Time-based X-axis
  • Interactive legends

Configuration

Basic Settings

FieldRequiredDescription
Title❌ NoDisplay name for the widget
Thing✅ YesSelect Thing to display data from (not required for Thing Type dashboards)
Mode✅ YesChoose 'Line' or 'Area' display mode
Timeframe✅ YesTime range for data display
Measures✅ YesAdd measures to display as lines. Each measure requires: measure, aggregation, line type and color

Chart Settings

FieldRequiredDescription
Y-Axis Min❌ NoMinimum value for Y-axis
Y-Axis Max❌ NoMaximum value for Y-axis
Gapfill❌ NoHandle missing data (NONE, TIME, LOCF)
Bucket type✅ YesChoose 'Dynamic' or 'Fixed' time bucket aggregation
Bucketsize / Data density✅ YesAggregation interval (depends on bucket type)
Thresholds❌ NoDefine threshold lines with colors and values

Display Options

FieldRequiredDescription
Show chart markers❌ NoDisplay data point markers on the line
Zoom allowed❌ NoEnable zoom functionality (default: true)
Show Table❌ NoDisplay data in table format below the chart
Display mode❌ NoChoose chart, table, or split view
Override❌ NoUse widget-specific time settings instead of dashboard defaults
Transparent❌ NoRemove widget background
Border color❌ NoCustom border color
Background Color❌ NoCustom background color

Best Practices

  1. Appropriate Timeframes - Match time range to data frequency
  2. Multiple Lines - Limit to 3-5 lines for readability
  3. Color Distinction - Use distinct colors for each line
  4. Axis Scaling - Set appropriate Y-axis ranges
  5. Gap Filling - Choose appropriate method for missing data

What's Next?