Purpose-fit chart selection
The AI can choose axis ranges, apply category colors, add a trend line when appropriate, and label only notable observations to reduce clutter.
AI chart maker
Explore relationships and outliers with an AI scatter plot
Choose two numeric fields and let ExcelDashboard AI plot every observation, color meaningful groups, identify outliers, and summarize the visible relationship without treating correlation as proof of causation.
Create a scatter plotFree to start · No credit card required
- Upload Excel or CSV
- Editable chart output
- No code required
Generated chart
Scatter Plot Maker
Why it matters
When to use a scatter plot
Examining the relationship between two numeric variables, the spread of observations, clusters, and unusual points.
Avoid aggregating away individual observations, using categorical values on numeric axes, or claiming that a visible correlation proves one variable caused the other.
Capabilities
What you can do with AI Scatter Plot Maker
Explicit data mapping
Two numeric columns for x and y, an optional category for color, and a stable row-level identifier for investigating notable points.
Aggregation you can review
Specify sums, averages, counts, rates, time intervals, and filters so the values behind the visual remain inspectable.
Editable reporting output
Refine titles, labels, colors, annotations, and chart type, then reuse the visual in a dashboard or report.
How it works
Go from source data to a useful result in three steps
- 1
Upload or paste the data
Start with Excel, CSV, or a table and confirm that headers, numeric values, categories, and dates were interpreted correctly.
- 2
Describe the comparison
Two numeric columns for x and y, an optional category for color, and a stable row-level identifier for investigating notable points. Explain the audience and the question the chart should answer.
- 3
Validate and refine the chart
Check the values, labels, scale, and filters. Avoid aggregating away individual observations, using categorical values on numeric axes, or claiming that a visible correlation proves one variable caused the other.
Common use cases
Built around real reporting work
Price and demand
Explore how unit price relates to sales volume across products or periods.
Campaign efficiency
Compare spend with conversions, revenue, or return across campaigns.
Operational outliers
Find cases with unusual combinations of duration, volume, cost, or quality.
Example prompts
Try a request like this
“Plot ad spend on the x-axis and conversions on the y-axis, colored by channel, and identify outliers.”
“Create a scatter plot of unit price versus quantity sold and add a trend line with a cautious interpretation.”
“Compare processing time and defect rate by facility, labeling only the five most unusual observations.”
Frequently asked questions
Questions about AI Scatter Plot Maker
What is a scatter plot maker?+
It is a tool that turns supplied data into a scatter plot and lets you refine the visual without manually configuring every chart setting.
When should I use a scatter plot?+
Examining the relationship between two numeric variables, the spread of observations, clusters, and unusual points.
What data do I need?+
Two numeric columns for x and y, an optional category for color, and a stable row-level identifier for investigating notable points.
When is another chart type better?+
Avoid aggregating away individual observations, using categorical values on numeric axes, or claiming that a visible correlation proves one variable caused the other.
Can I edit the generated chart?+
Yes. Review the data mapping first, then adjust the chart type, titles, labels, colors, annotations, and surrounding report content.
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Start with your own data
Upload a spreadsheet or describe the result you need. Build the first useful draft with AI, then review and refine it.