Describe your data and get a clean, labeled histogram in seconds. Bins, axes, titles, and frequency counts are all handled for you, whether you need a quick class chart or a polished report visual.
Browse histograms made with Figviz, or generate your own above
A straightforward frequency histogram with clearly labeled axes and equal-width bins, the ideal starting point for any data set.
A symmetric histogram with bars rising to a central peak and falling evenly on both sides, illustrating a normal distribution.
A right-skewed histogram where most values cluster at the low end and a long tail extends to the right, common in income or response-time data.
A histogram with a smooth frequency curve drawn over the bars to highlight the underlying distribution shape.
A classroom histogram mapping exam scores to grade bands (A, B, C, D, F) so teachers and students can see the grade distribution at a glance.
A side-by-side visual showing the key structural difference: histogram bars touch (continuous data), bar chart bars have gaps (categorical data).
Describe the measurement, bin boundaries, and labels to get a histogram that is ready to teach or present.
A print-ready classroom chart with equal-width score bins.
Create a histogram titled "Grade 8 Science Test Scores" for 80 students. Use adjacent 10-point bins: 40-49, 50-59, 60-69, 70-79, 80-89, and 90-100. Frequencies are 3, 7, 14, 24, 21, and 11. Label the x-axis "Test score" and the y-axis "Number of students". Show the count above each bar. Clean classroom style, white background.
A distribution example with a clear long right tail.
Create a histogram titled "Monthly Household Income Distribution" showing a right-skewed distribution. Use adjacent bins in thousands of dollars: 0-2, 2-4, 4-6, 6-8, 8-10, 10-12, and 12-14+, with frequencies 28, 35, 22, 12, 7, 4, and 2. Label both axes and add a small annotation noting the long right tail. Professional statistics textbook style, white background.
Use a smooth overlay to discuss the shape of a data set.
Create a histogram titled "Human Reaction Times" for 120 trials, using adjacent 50 ms bins from 150 ms to 450 ms. Show a roughly bell-shaped distribution peaking at 250-300 ms, with a smooth frequency curve over the bars. Label the x-axis "Reaction time (ms)" and y-axis "Frequency". Clear scientific chart style, white background.
A histogram maker is a tool that turns raw data descriptions into a frequency distribution chart: adjacent bars that show how many values fall within each equally-spaced bin. Unlike a bar chart, the bars in a histogram touch because the data is continuous, not categorical. Figviz builds the chart from a plain description, so you can specify your bin ranges, axis labels, and distribution shape without touching a spreadsheet or charting library.
The defining difference is whether the bars touch. A histogram displays continuous data grouped into bins, so the bars are adjacent with no gaps, forming a shape that reveals the distribution (normal, skewed, bimodal). A bar chart displays categorical or discrete data, so the bars are separated by gaps to signal that the categories are independent. If you are plotting exam scores or measurements, you need a histogram. If you are plotting survey responses or fruit sales by type, you need a bar chart.
The point of a histogram is the outline, not the individual bars. A symmetric mound with one peak suggests an approximately normal distribution, and overlaying a curve makes that easier to judge; the Bell Curve Generator draws that comparison directly. A long tail to the right, common in incomes, waiting times, and counts, is right-skewed, and here the mean sits above the median. A long left tail is left-skewed, with the mean below the median. Two separate peaks usually mean two populations have been mixed together, such as two classes or two machine settings, and the fix is to split the data rather than to re-bin it. A flat profile across the range suggests values are roughly uniform. Isolated bars separated by empty bins are candidate outliers and deserve a look at the raw records before you draw any conclusion.
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