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Create scatter plots from CSV or JSON data with customizable colors
Create scatter plots instantly with our free online scatter chart generator. This tool helps researchers and data scientists visualize correlations between variables with customizable scatter plots. Simply enter your coordinate data to generate professional scatter charts in real-time.
Scatter plot generator creates visualizations showing relationships between two numeric variables. Each point represents one observation with x and y coordinates. Essential for correlation analysis, outlier detection, clustering identification, and exploring variable relationships in data science and research.
Input data as x-y coordinate pairs. The generator plots each point on a Cartesian plane. Customize point size, color (optionally mapped to a third variable), shape, and opacity. Add trend lines (linear, polynomial, LOESS) to highlight relationships. Interactive features enable point identification.
Scatter plots use two continuous linear scales. Correlation direction: positive (up-right), negative (up-left), or none (random scatter). Overplotting (many overlapping points) can be addressed with transparency, jittering, or density-based coloring. Point size can encode a third variable (bubble chart).
Explore relationships between variables like height vs weight.
Positive correlation: taller people tend to weigh moreIdentify unusual observations that deviate from patterns.
Visualize natural groupings in data before formal clustering.
Plot residuals to check model assumptions.
const ctx = document.getElementById('chart').getContext('2d');
new Chart(ctx, {
type: 'scatter',
data: {
datasets: [{
label: 'Height vs Weight',
data: [
{x: 165, y: 55}, {x: 170, y: 62},
{x: 175, y: 68}, {x: 180, y: 75},
{x: 185, y: 82}, {x: 168, y: 58},
{x: 172, y: 65}, {x: 178, y: 72}
],
backgroundColor: 'rgba(54, 162, 235, 0.6)'
}]
},
options: {
scales: {
x: {
title: { display: true, text: 'Height (cm)' }
},
y: {
title: { display: true, text: 'Weight (kg)' }
}
}
}
});
// Add trendline with chartjs-plugin-trendlineScatter plots require x-y data objects. Add axis labels to clarify what each dimension represents.
Use scatter plots to explore relationships between two numeric variables, identify correlations, detect outliers, and discover clusters. Best for continuous data where relationship patterns are important.
Positive correlation: points trend upward left-to-right. Negative: downward trend. Strong correlation: tight clustering around a line. Weak: dispersed points. Zero correlation: random scatter with no pattern.