Enter data and click Generate to visualize your histogram
Or load a sample dataset above ↑
Create stunning frequency distribution histograms online. Customize bins, colors, labels, overlays, and export in PNG or SVG — no signup needed.
Enter data and click Generate to visualize your histogram
Or load a sample dataset above ↑
Everything you need to analyze and visualize frequency distributions professionally.
Instant chart rendering as you adjust settings. Live preview eliminates guesswork and speeds up your analysis workflow.
Auto-bin using Sturges' rule for statistically optimal grouping, or set bins manually from 2 to 60 for full precision.
Compare your data against a theoretical normal distribution with a smooth Gaussian curve plotted over your bars.
Mean, median, mode, standard deviation, variance, skewness, kurtosis, min/max, range — all computed automatically.
Choose from 6 color themes or define custom fill/border colors. Adjust opacity, font size, labels, and display toggles.
Download your histogram as a high-resolution PNG, scalable SVG vector, or export frequency data as a CSV file.
Upload your own dataset file directly. Supports comma-separated CSV and plain TXT files for fast data loading.
View a detailed breakdown table with bin ranges, absolute frequency, relative percentage, and cumulative percentage.
A histogram is one of the most powerful and widely-used data visualization tools in statistics. Unlike a bar chart which compares distinct categories, a histogram displays the frequency distribution of continuous numerical data across adjacent, non-overlapping intervals known as bins. Each bar's height reveals how many data points fall within that interval, making it easy to spot patterns, clusters, gaps, and outliers in your dataset.
Use a histogram whenever you want to understand the shape of your data. Are values normally distributed (bell curve)? Skewed to one side? Bimodal with two peaks? Histograms answer these questions instantly. They're essential in quality control, finance, research, machine learning, and everyday data analysis.
Bar charts compare separate categories with gaps between bars. Histograms show the distribution of continuous numerical data — bins are adjacent with no gaps, because the intervals are connected ranges, not distinct groups.
Bin selection is both science and art. Common rules include Sturges' Rule (best for normal data, n < 200), Scott's Rule (minimizes MSE), and the Freedman-Diaconis Rule (robust against outliers). Our tool auto-applies Sturges' rule when you check "Auto Bins", or you can manually slide to the perfect count for your data.
Disclaimer: Excel® is a registered trademark of Microsoft Corporation. "Chart.js" is open-source software licensed under MIT. SEOWebChecker is not affiliated with Microsoft Corporation or any charting library vendors.
Everything you need to know about histograms and using this tool.
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