Visualisation definition Line timeseries chart
The line-timeseries chart visualisation type represents data as a line chart showing historic data.
When to use
Use a line‑timeseries chart when you need to show how a value changes over time. This chart type emphasizes trends, cycles, seasonality, and long‑term movement, making it ideal for temporal datasets.
Choose a line‑timeseries chart when:
- Your data represents values over time (e.g., days, weeks, months, years).
- You want to highlight temporal trends, such as growth, decline, volatility, or periodic patterns.
- Time order is crucial, and the spacing or frequency of data points matters.
- You’re comparing multiple time‑based series, such as performance metrics or daily counts.
- You have many data points, and other chart types would become cluttered.
Use a line‑timeseries chart when helping users understand how something evolves or behaves through time.
When not to use
Avoid using a line‑timeseries chart when:
- The data isn’t related to time — use a standard line chart or another type entirely.
- Time intervals are inconsistent or categorical (e.g., “Phase 1, Phase 2”), which breaks the assumption of temporal continuity.
- You need to compare single points in time rather than trends — a bar or column chart works better.
- Your dataset has only a couple of timestamps, not enough to show a meaningful trend.
- You’re dealing with non‑continuous or event‑based timelines, where a dot plot, scatter, or bar chart may be clearer.
- Precision on individual values matters more than overall trend, as line charts can obscure exact readings.
How it works
- Line‑timeseries charts detect partial time periods (e.g., the first or last month in a range that isn’t a full month).
- Partial periods are shown with a dotted line to distinguish them from complete data.
- This indicates that these values don’t represent a full time unit at the chosen granularity.
- Standard line charts don’t handle partial dates, so all points appear as fully complete.
Definition
{
id: 'id',
type: 'line-timeseries',
display: 'name',
description: 'description',
column: {
...
}
}
See the Targeting data for and how to target data with the column
Data assumptions
- The dataset must include a column with the ID
ts, containing timestamp values. - The
tsvalues should already be formatted exactly as you want them displayed — the visualisation will render them as‑is without additional formatting.
Examples
Example Dataset
| Date | est_id | no_metric_one | no_metric_two | no_metric_three |
|--------|--------|----------------|----------------|------------------|
| Aug 24 | ABC | 781 | 754 | 802 |
| Aug 24 | GHI | 610 | 589 | 633 |
| Aug 24 | DEF | 499 | 472 | 518 |
| Sep 24 | ABC | 514 | 538 | 497 |
| Sep 24 | GHI | 518 | 492 | 531 |
| Sep 24 | DEF | 521 | 549 | 505 |
| Oct 24 | ABC | 598 | 612 | 580 |
| Oct 24 | GHI | 676 | 702 | 661 |
| Oct 24 | DEF | 687 | 655 | 712 |
| Nov 24 | ABC | 522 | 499 | 548 |
| Nov 24 | GHI | 790 | 768 | 812 |
| Nov 24 | DEF | 713 | 689 | 727 |
| Dec 24 | ABC | 431 | 452 | 408 |
| Dec 24 | GHI | 536 | 522 | 561 |
| Dec 24 | DEF | 590 | 574 | 613 |
| Jan 25 | ABC | 614 | 643 | 609 |
| Jan 25 | GHI | 713 | 695 | 740 |
| Jan 25 | DEF | 682 | 668 | 701 |
Example 1
Prisoner totals for missing MetricOne by establishment over time
Definition
{
id: 'mockMetricOneLineChartTimeseries',
type: 'line-timeseries',
display: 'Missing MetricOne timeseries chart',
description: 'Prisoner totals for missing MetricOne by establishment over time',
columns: {
keys: [
{
id: 'establishment_id',
display: 'Establishment ID',
},
],
measures: [
{
id: 'ts',
display: 'Date',
},
{
id: 'no_metric_one',
display: 'Has no MetricOne',
},
],
expectNulls: false,
},
}
Visualisation dataset
This definition will return the following dataset
| ts | est_id | no_metric_one |
|--------|--------|----------------|
| Aug 24 | ABC | 781 |
| Aug 24 | GHI | 610 |
| Aug 24 | DEF | 499 |
| Sep 24 | ABC | 514 |
| Sep 24 | GHI | 518 |
| Sep 24 | DEF | 521 |
| Oct 24 | ABC | 598 |
| Oct 24 | GHI | 676 |
| Oct 24 | DEF | 687 |
| Nov 24 | ABC | 522 |
| Nov 24 | GHI | 790 |
| Nov 24 | DEF | 713 |
| Dec 24 | ABC | 431 |
| Dec 24 | GHI | 536 |
| Dec 24 | DEF | 590 |
| Jan 25 | ABC | 614 |
| Jan 25 | GHI | 713 |
| Jan 25 | DEF | 682 |
see here for more info on targeting data
Visualisation
Example 2
Prisoner totals for missing MetricOne by single establishment over time, using filters
Definition
{
id: 'mockMetricOneLineChartTimeseries',
type: 'line-timeseries',
display: 'Missing MetricOne timeseries chart',
description: 'Prisoner totals for missing MetricOne by establishment over time',
columns: {
keys: [
{
id: 'establishment_id',
display: 'Establishment ID',
},
],
measures: [
{
id: 'ts',
display: 'Date',
},
{
id: 'no_metric_one',
display: 'Has no MetricOne',
},
],
filters: [
{
id: 'establishment_id',
equals: 'ABC',
},
],
expectNulls: false,
},
}
Visualisation dataset
This definition will return the following dataset
| ts | est_id | no_metric_one |
|--------|--------|----------------|
| Aug 24 | ABC | 781 |
| Sep 24 | ABC | 514 |
| Oct 24 | ABC | 598 |
| Nov 24 | ABC | 522 |
| Dec 24 | ABC | 431 |
| Jan 25 | ABC | 614 |
see here for more info on targeting data
Visualisation
