Chart By Numeric X
Visualize numeric relationships with scatter plots, trend lines, and optional R-squared regression analysis for dashboard-based monitoring
Specs
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
Open the dashboard where you want to place the widget.
Click Add Widget and select Chart By Numeric X from the Data Driven Charts category.
Open the widget settings and choose the source Table.
Select a numeric X axis, one or more numeric Series, and the remaining display options, then click Save.
Required Settings
Table: Select the table that contains the numeric data to visualize.
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.
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.
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.
Display Configuration
Click the widget's Configure button after adding it to the dashboard.
Choose the Table and optional Filter to define which records are included.
Set the numeric X axis, then select one or more numeric Series and an optional Data aggregation method.
Provide a Chart title, adjust Height, and click Save to generate the chart.
Data Source Configuration
Use the widget settings to align the chart with the intended analysis:
Select the source Table that contains the numeric measurements.
Apply a Filter when you need to limit the chart to a subset such as one project, instrument, analyst, batch, or date window.
Choose a numeric X axis that represents the independent variable, sequence, or scale for comparison.
Add one or more numeric Series that represent dependent variables or outcomes.
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.
Advanced Configuration
Use multiple widget instances with different Filter values to compare conditions side by side on the same dashboard.
Configure multiple Series when you want to compare several numeric outcomes against the same X axis.
Switch to Scatter with fit when you want regression analysis rather than simple plotting.
Increase Height for dense data sets so point clusters and fit lines remain legible.
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.
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.
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.
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.
Open the dashboard and locate the Chart By Numeric X widget.
Use the chart type selector in the widget interface to switch visualization style.
Select Scatter with fit when you want linear regression analysis.
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.
Configure the widget with a numeric X axis and one or more numeric Series.
Generate the chart and select Scatter with fit.
Review the displayed fit line, equation, and R-squared value on the chart.
Use the regression output to assess correlation strength or approximate predictions.
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.
Data Export
Open the dashboard and find the Chart By Numeric X widget.
Click Download to export the chart data currently being displayed.
Save the exported file for spreadsheets, statistical analysis, or presentation use.
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: Use when the X axis should represent categories instead of numeric values.
Composed Chart By Category X: Use when you need mixed chart types and category-based multi-series comparison.
Chart By Numeric X: Use the section widget version when numeric analysis should stay scoped to a specific record context.
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