> For the complete documentation index, see [llms.txt](https://docs.labii.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.labii.com/widgets/dashboard-widgets/reports/data-driven-charts/chart-by-numeric-x.md).

# Chart By Numeric X

## Specs

| Label                     | Value                         |
| ------------------------- | ----------------------------- |
| **Version**               | 1.1.0 (updated on 2026-04-28) |
| **Developer**             | Labii Inc.                    |
| **Type**                  | Dashboard                     |
| **Support Configuration** | Yes                           |

## Overview

The Chart By Numeric X dashboard widget visualizes relationships between numeric variables by plotting numeric values on both the X and Y axes. It is designed for dashboards that need more analytical depth than category-based summaries, allowing laboratory teams to explore trends, correlations, time-based measurements, calibration behavior, or performance relationships directly from workspace dashboards. With optional regression support through **Scatter with fit**, the widget can display a best-fit line, equation, and R-squared value to support data-driven interpretation and monitoring.

## Use Cases

* **Calibration dashboards**: Plot standard concentration versus instrument response to monitor calibration behavior.
* **Time-series monitoring**: Show numeric measurements over elapsed time, cycle number, or sample sequence.
* **Correlation analysis**: Compare variables such as temperature versus reaction rate, OD versus protein yield, or concentration versus response.
* **Quality control review**: Track drift, variance, or expected-versus-observed measurements across runs.
* **Process performance dashboards**: Compare throughput, duration, cost, or utilization metrics against another numeric driver.
* **Research analytics**: Explore trends in assay results, kinetic data, growth curves, or dose-response relationships.

## Configuration

This widget requires numeric data on both axes and supports one or more numeric series against a numeric X axis.

### Initial Setup

{% stepper %}
{% step %}
Open the dashboard where you want to place the widget.
{% endstep %}

{% step %}
Click **Add Widget** and select **Chart By Numeric X** from the **Data Driven Charts** category.
{% endstep %}

{% step %}
Open the widget settings and choose the source **Table**.
{% endstep %}

{% step %}
Select a numeric **X axis**, one or more numeric **Series**, and the remaining display options, then click **Save**.
{% endstep %}
{% endstepper %}

### Required Settings

* **Table**: Select the table that contains the numeric data to visualize.
* **X axis**: Choose a numeric column for the X axis. Use a [Number](/widgets/column-widgets/form/text-inputs.md#number) or [Formula](/widgets/column-widgets/calculation.md#formula) column that returns numeric values.
* **Series**: Choose one or more numeric columns for the Y-axis data series. These columns must also use [Number](/widgets/column-widgets/form/text-inputs.md#number) or [Formula](/widgets/column-widgets/calculation.md#formula) widgets.

{% hint style="info" %}
This widget is intended for numeric-to-numeric visualization. Text, date, and category-style columns are not appropriate for the X axis or numeric series.
{% endhint %}

### Optional Settings

#### Data Filtering

* **Filter**: Specify a filter to limit the result set. Leave it empty to use the full dataset.

#### Numeric Summarization

* **Data aggregation**: Choose how matching values are summarized.
  * **None**: Do not apply an aggregation.
  * **Average**: Use the mean value.
  * **Max**: Use the largest value.
  * **Median**: Use the middle value.
  * **Min**: Use the smallest value.

#### Display Settings

* **Chart title**: Provide the title shown above the visualization.
* **Height**: Set chart height in pixels. The default is 250 px.

{% hint style="info" %}
Use filters to isolate a single experiment type, cohort, date window, or operating condition when you want the chart to reveal a clearer numeric relationship.
{% endhint %}

### Display Configuration

{% stepper %}
{% step %}
Click the widget's **Configure** button after adding it to the dashboard.
{% endstep %}

{% step %}
Choose the **Table** and optional **Filter** to define which records are included.
{% endstep %}

{% step %}
Set the numeric **X axis**, then select one or more numeric **Series** and an optional **Data aggregation** method.
{% endstep %}

{% step %}
Provide a **Chart title**, adjust **Height**, and click **Save** to generate the chart.
{% endstep %}
{% endstepper %}

### Data Source Configuration

Use the widget settings to align the chart with the intended analysis:

{% stepper %}
{% step %}
Select the source **Table** that contains the numeric measurements.
{% endstep %}

{% step %}
Apply a **Filter** when you need to limit the chart to a subset such as one project, instrument, analyst, batch, or date window.
{% endstep %}

{% step %}
Choose a numeric **X axis** that represents the independent variable, sequence, or scale for comparison.
{% endstep %}

{% step %}
Add one or more numeric **Series** that represent dependent variables or outcomes.
{% endstep %}
{% endstepper %}

{% hint style="warning" %}
When you plot multiple series with very different value ranges, one series can visually dominate the chart. Consider separate widgets or normalized values when readability becomes poor.
{% endhint %}

### Advanced Configuration

{% stepper %}
{% step %}
Use multiple widget instances with different **Filter** values to compare conditions side by side on the same dashboard.
{% endstep %}

{% step %}
Configure multiple **Series** when you want to compare several numeric outcomes against the same X axis.
{% endstep %}

{% step %}
Switch to **Scatter with fit** when you want regression analysis rather than simple plotting.
{% endstep %}

{% step %}
Increase **Height** for dense data sets so point clusters and fit lines remain legible.
{% endstep %}
{% endstepper %}

## Readonly View

Dashboard widgets display data in read-only mode, and Chart By Numeric X is optimized for analytical review of numeric relationships from a dashboard context.

<figure><img src="/files/D3zejqneXncSQ0AtM6Sk" alt="Chart By Numeric X widget displaying numeric data on both axes with scatter and fit options"><figcaption><p>The widget displays numeric relationships with scatter-style visualization and optional regression analysis for dashboard review.</p></figcaption></figure>

### Display Features

* **Numeric X-Y plotting**: The chart plots numeric values on both axes to show how one variable changes relative to another.
* **Multiple chart styles**: Users can switch among supported chart types to emphasize point distribution, trends, or regression.
* **Multi-series display**: More than one Y-axis series can be plotted against the same X axis when comparative analysis is needed.
* **Dashboard visibility**: The widget keeps analytical charts visible on shared or personal dashboards without opening detailed reports.

### Visual Elements

* **X axis**: Displays numeric values for the selected independent variable or numeric scale.
* **Y-axis series**: Displays one or more numeric outcomes plotted against the X axis.
* **Chart title**: A descriptive title appears above the visualization when configured.
* **Fit line and equation**: When **Scatter with fit** is selected, the chart displays the best-fit line and regression formula.

### Data Indicators

* **Point distribution**: Scatter layouts help users see clusters, outliers, and spread.
* **Trend direction**: Line or area views can make upward, downward, or stable movement easier to interpret.
* **Regression strength**: R-squared indicates how well a linear relationship explains the data when fit mode is used.
* **Aggregated values**: When aggregation is applied, the chart reflects summarized rather than raw point values.

### Interactive Features

* **Chart type selection**: Switch visualization style based on the analytical question.
* **Hover details**: Inspect precise plotted values directly on the chart.
* **Download**: Export the underlying chart data for further analysis.

{% hint style="info" %}
**R-squared (R²)** is the coefficient of determination. It represents the proportion of variation in the dependent variable that can be predicted from the independent variable. Values closer to 1 indicate stronger linear relationships.
{% endhint %}

## Additional Functions

### Chart Type Selection

The widget supports multiple visualization modes for numeric analysis:

* **Scatter**: Shows individual numeric points without connecting lines.
* **Line**: Connects points to emphasize sequence or progression.
* **Area**: Fills beneath the plotted line to emphasize magnitude.
* **Scatter with fit**: Adds a best-fit regression line with equation and R-squared value.

{% stepper %}
{% step %}
Open the dashboard and locate the **Chart By Numeric X** widget.
{% endstep %}

{% step %}
Use the chart type selector in the widget interface to switch visualization style.
{% endstep %}

{% step %}
Select **Scatter with fit** when you want linear regression analysis.
{% endstep %}
{% endstepper %}

### R-squared Prediction and Regression Analysis

The **Scatter with fit** option provides visual and statistical support for interpreting numeric relationships.

* **Best-fit line**: Shows the linear regression through the plotted points.
* **Regression equation**: Displays the line formula for reference and prediction.
* **R-squared value**: Indicates how strongly the line explains the observed variation.

{% stepper %}
{% step %}
Configure the widget with a numeric **X axis** and one or more numeric **Series**.
{% endstep %}

{% step %}
Generate the chart and select **Scatter with fit**.
{% endstep %}

{% step %}
Review the displayed fit line, equation, and R-squared value on the chart.
{% endstep %}

{% step %}
Use the regression output to assess correlation strength or approximate predictions.
{% endstep %}
{% endstepper %}

{% hint style="warning" %}
R-squared assumes a linear relationship. A low value may mean weak linear correlation, but it can also indicate that the underlying relationship is non-linear rather than absent.
{% endhint %}

### Data Export

{% stepper %}
{% step %}
Open the dashboard and find the **Chart By Numeric X** widget.
{% endstep %}

{% step %}
Click **Download** to export the chart data currently being displayed.
{% endstep %}

{% step %}
Save the exported file for spreadsheets, statistical analysis, or presentation use.
{% endstep %}
{% endstepper %}

### Multi-Series Comparison

When multiple numeric series are configured, the widget helps compare several outcomes against a shared numeric X axis within one dashboard tile.

## Best Practices

### Dashboard Design

* Use this widget on analytical dashboards where users need to interpret relationships, not just category counts.
* Give the chart a precise title that states both variables being compared.
* Allocate enough vertical space when plotting dense point clouds or multiple series.

### Statistical Interpretation

* Use **Scatter** for exploratory review and **Scatter with fit** for quantified linear analysis.
* Interpret high R-squared values as stronger linear fit, not automatic proof of causation.
* Check whether the relationship appears linear before relying on the fit line.

### Data Preparation

* Use filters to isolate comparable records and avoid mixing incompatible conditions.
* Prefer clean numeric columns with consistent units and data quality.
* Separate unrelated metrics into different widgets when scales or meanings differ substantially.

### Performance and Readability

* Avoid overloading one widget with too many series.
* Increase chart height for larger datasets to reduce visual crowding.
* Revisit filters and chart usage as workflows or table structures evolve.

## Related Widgets

* [Chart By Category X](/widgets/dashboard-widgets/reports/data-driven-charts/chart-by-category-x.md): Use when the X axis should represent categories instead of numeric values.
* [Composed Chart By Category X](/widgets/dashboard-widgets/reports/data-driven-charts/composed-chart-by-category-x.md): Use when you need mixed chart types and category-based multi-series comparison.
* [Chart By Numeric X](/widgets/section-widgets/report/data-driven-charts/chart-by-numeric-x.md): Use the section widget version when numeric analysis should stay scoped to a specific record context.