Scatter Plot Maker — Create XY Scatter Charts Online
Visualize relationships between two variables with an interactive scatter plot. Paste your CSV data, customize point appearance, and export as PNG. All data stays in your browser — nothing leaves your device.
How to Use the Scatter Plot Maker
- Enter data — type or paste CSV data with x,y pairs, one per line.
- Customize appearance — use the color picker to set point color and the slider to adjust point size.
- View stats — the overview cards show point count, value ranges, and correlation.
- Export — download the chart as a PNG image for presentations or reports.
Why Scatter Plots Matter
Scatter plots are one of the most powerful tools for exploring relationships between two numerical variables. They reveal patterns, clusters, outliers, and correlations that summary statistics alone can hide.
Whether you're analyzing test scores vs. study time, price vs. demand, or height vs. weight, a scatter plot gives you an instant visual understanding of how two variables relate to each other. It's the first chart you should reach for when investigating any bivariate relationship.
Frequently Asked Questions
Enter one data point per line in CSV format: x,y. For example, 1,10 means x=1 and y=10. You can also add a header line like Height,Weight which will be skipped.
The Pearson correlation coefficient (r) measures the linear relationship between x and y. Values range from -1 (perfect negative) to +1 (perfect positive), with 0 meaning no linear relationship.
This tool is designed for single-series scatter plots. For multiple series, consider using the Radar Chart tool or splitting data into separate scatter plots for comparison.
Use Cases
Academic Research
Visualize correlations between study hours and exam scores, or any other pair of measured variables in scientific experiments.
Business Analytics
Plot ad spend vs. revenue, price vs. sales volume, or employee satisfaction vs. productivity to find optimal business levers.
Quality Control
Identify outliers and trends in manufacturing data by plotting measurements against specifications or time.
Survey Data Analysis
Explore relationships in survey responses, like income vs. satisfaction or age vs. spending habits across demographic groups.