Histogram Maker
Paste raw numerical data to create a frequency histogram instantly. Use automatic bins or control the bin count or width, review the frequency table, and download a PNG or SVG.
Create your histogram
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Or drop one file here. Up to 2 MB; nothing is uploaded to a server.
1. Enter data
Paste values from a spreadsheet or type them below. Rows, commas, tabs, spaces, and semicolons are accepted.
Preview
22 values · 5 bins · Freedman–Diaconis
Applies to PNG and SVG downloads. Dark labels work best on light backgrounds. The preview checkerboard is not exported.
Applies to PNG and SVG downloads. The preview matches the image proportions; wider images retain side padding to avoid distortion. SVG stays sharp when resized; some editors may substitute fonts.
Frequency table
| Bin range | Frequency | Percentage |
|---|---|---|
| [-4.5, -1.5) | 2 | 9.1% |
| [-1.5, 1.5) | 5 | 22.7% |
| [1.5, 4.5) | 6 | 27.3% |
| [4.5, 7.5) | 6 | 27.3% |
| [7.5, 10.5] | 3 | 13.6% |
Need the mean, standard deviation or quartiles before charting? Use the descriptive statistics calculator and open the same values here.
For a smaller dataset, a stem-and-leaf plot shows the distribution while retaining individual values.
How to make a histogram from data
- Enter numerical values. Paste a spreadsheet column or type numbers separated by rows, commas, tabs, spaces, or semicolons.
- Choose the bins. Start with automatic binning, or specify a bin count or width when your analysis requires fixed intervals.
- Check the frequencies. Use the table below the chart to verify every interval and its count.
- Finish and export. Add clear axis labels and a title, then download a PNG or SVG.
What is a histogram?
A histogram shows the distribution of numerical data. It divides a continuous range into intervals called bins and uses the height of each adjoining column to show how many observations fall inside that interval. This makes clusters, gaps, skew, spread, and possible peaks easier to see than they are in a raw list.
Histogram vs bar or column chart
Histograms group numerical measurements into ordered ranges, so neighboring bars touch and their position carries quantitative meaning. Bar and column charts compare distinct categories such as products or months; their bars are separated and can usually be reordered. Use a histogram for a distribution and a column chart for category comparisons.
Study histogram vs bar chart worked examples, practice questions, and a printable worksheet.
Bins, frequency, and bin width
A bin is an interval on the number line. Its frequency is the count of observations inside it, while bin width is the distance between its lower and upper boundaries. This maker uses left-inclusive intervals and assigns values on a boundary to the bin on the right; the final bin includes its upper boundary so the maximum value is always counted.
More narrow bins reveal local variation but may make random noise look important. Fewer wide bins create a smoother summary but can conceal clusters or gaps. When comparing histograms, use consistent bin boundaries so differences are not merely a result of different settings.
Cumulative count and percentage
Frequency counts each bin separately. Cumulative count adds that bin to all bins on its left; cumulative percentage divides the running count by the number of valid observations and multiplies by 100. The final bar reaches the total sample size or 100%.
For bin counts of 2, 3, and 5, cumulative counts are 2, 5, and 10, or 20%, 50%, and 100%. Each total counts values below the bin's upper boundary, except the final bin, which also includes that boundary. Empty bins keep the previous cumulative total. This is a grouped cumulative histogram, not an exact empirical cumulative distribution at every individual value.
Select the display under Customize. Bin boundaries and original values stay unchanged, and the frequency table includes both individual and cumulative totals. Default axis labels update with the mode; a custom axis label is kept for you to edit.
How automatic binning is calculated
Automatic mode uses the Freedman–Diaconis rule. It estimates a useful width from the interquartile range and the cube root of the sample size, making it less sensitive to extreme values than a rule based on the full range. The tool converts that width into no more than 50 practical bins.
If the IQR is zero—for example, when many values repeat—the tool uses Sturges' rule as a fallback. Automatic binning is a starting point, not a universal answer. Domain conventions or predefined reporting intervals may make a custom count or width more appropriate.
Reading a frequency histogram
Find the center
Look for the interval or cluster where observations are most concentrated.
Assess spread
Compare the occupied range and how quickly frequencies taper away from the center.
Notice shape
Look for skew, separated peaks, empty intervals, or isolated edge values worth investigating.
A histogram does not preserve the exact position of every observation because values are grouped. Use the accessible frequency table to confirm counts and retain the raw data when exact values still matter.
Histogram maker FAQ
How does automatic binning work?
ChartMaker uses the Freedman–Diaconis rule, which considers sample size and the interquartile range. If the data has no usable IQR, it falls back to Sturges' rule.
Can I set the number or width of bins?
Yes. Choose a custom number of bins or a custom numerical bin width. The frequency table updates with the same boundaries used by the chart.
Can a histogram include negative values and decimals?
Yes. Negative numbers, decimals, repeated values, and small datasets are supported. Invalid entries are identified and ignored without stopping valid data from being charted.
Is my histogram data uploaded?
No. The data is parsed, binned, rendered, and exported entirely in your browser.