Lines Chart

A lines chart displays quantitative values across a continuous interval, typically over time. It is ideal for visualizing trends and understanding how data evolves.

When to use it

  • Display trends over time.
  • Show relationships or dependencies between variables.
  • Highlight highs and lows (e.g., performance, workload).
  • Compare multiple series over the same timeline.

When NOT to use

  • For comparing unrelated categories.
  • When data has no natural order.
  • When there are too many series (visual clutter).

Categories

  • Chart Type: Trend/ Time Series
  • Data Type: Continuous numeric values
  • Chart Family: Line-based
  • Purpose: Show trends, compare multiple series, highlight patterns

Data requirements

  • 1 ordered dimension (typically time)
  • ≥1 numeric measure
  • Multiple series optional but limited

Use cases

Linx

Lines charts are used to visualize how system usage and performance metrics, such as response time and error rate, evolve over time within Traxes. They make trends, peaks, and anomalies easy to identify, while also enabling clear comparisons between multiple services on a single timeline.

Accessibility

Do
  • Use high-contrast, color-blind-friendly palettes.
  • Differentiate lines using styles (eg: dashed, dotted) or markers, not color alone.
  • Add direct labels on lines and clear axis titles.
  • Provide alt text or summaries for screen readers.
  • Limit clutter; use small multiples when comparing many series.
Don't
  • Rely solely on color for differentiation.
  • Omit alternative indicators (eg: line styles, markers).
  • Remove axis labels or units.
  • Use similar colors for overlapping series.
  • Overload charts with too many lines.

  • Area Chart
    A line chart with the area beneath the line filled, emphasizing magnitude or volume over time.
  • Scatter Plot
    Displays relationships between two variables; when combined with time, can complement line charts for deeper analysis.
  • Heat Map
    Useful alternative when comparing intensity or patterns across two dimensions instead of continuous trends.