Scatter Chart
Free Online Scatter Chart Maker
What is a Scatter Chart?
A scatter chart plots individual data points across two axes to reveal relationships between two variables. Each dot represents one observation — its horizontal position shows one value, its vertical position shows another. Use scatter charts when you want to see whether two variables move together, diverge, or show no pattern at all. They are especially effective at surfacing clusters, trends, and outliers that tables and summaries would hide.
Key Features
Correlation Detection
Plot two variables against each other to immediately see positive, negative, or no correlation — without running a formula.
Outlier Identification
Individual data points are always visible, so anomalies and extreme values stand out at a glance rather than getting averaged away.
Variable Point Sizing
Encode a third dimension by adjusting dot size per point, turning a basic scatter plot into a bubble-style view when needed.
Reference Lines
Add horizontal or vertical reference lines to mark thresholds, targets, or averages and give each data point meaningful context.
Labeled Data Points
Optionally display a name or value next to each dot so viewers can identify specific observations without hovering.
Custom Axis Labels
Name both axes clearly so your audience always knows what each dimension represents, even outside the chart.
Best For
When to Use
- You have two numeric variables and want to see if they are related
- Your dataset has individual observations that matter, not just aggregates
- You suspect outliers exist and want to make them visible
- You need to compare actual vs. predicted values point by point
- You want to show distribution density across two dimensions
- A line chart would be misleading because your X axis is not time-ordered
Common Mistakes
- !Connecting dots with lines when the X axis is not a continuous sequence
- !Omitting axis labels so viewers cannot tell what the variables actually are
- !Plotting categorical data on one axis, which distorts the apparent relationship
- !Overloading the chart with hundreds of overlapping points without transparency or jitter
- !Assuming a visual cluster proves causation rather than correlation
- !Using inconsistent dot sizes when size is not encoding a meaningful third variable
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Templates
Start with professionally designed templates
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Reveal the relationship between two variables across time periods with a clean, labeled connected scatter plot.
View All Templates
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