How to Make a Stem-and-Leaf Plot from CSV or Excel Data

What data does a stem-and-leaf plot need?

Use one row per observation:

Inspect the basic sample CSV or back-to-back sample CSV. Keep unit symbols and notes outside the numeric value column.

Step 1: Decide whether the dataset is small enough

Stem-and-leaf plots are most useful for small or moderate datasets when preserving every value matters. They help with classroom demonstrations, quality-control batches, compact clinical measurements, and exploratory checks. If the rows no longer fit comfortably in a figure, choose a Histogram Maker or ECDF Plot Generator.

Step 2: Upload CSV or Excel data

Open the Stem-and-Leaf Plot Generator, choose an example, or upload CSV, TSV, TXT, XLSX, or XLS. Excel imports the first worksheet. Remove totals, merged cells, footnotes, and text from the numeric measurement column.

Step 3: Set the stem unit and check the key

Generate the plot and reconstruct several values manually. If the key says 12 | 4 = 12.4, then the leaf 4 represents the tenths digit. Negative values, decimal values, and measurements that span several orders of magnitude deserve particular attention.

Leaves should normally be ordered within each stem. Repeated leaves are not an error: they show repeated observations. Empty stems can be retained when they reveal a meaningful gap, but excessive empty rows waste space.

Step 4: Compare groups carefully

A back-to-back stem-and-leaf plot places two groups on opposite sides of the same stems. It makes differences in center, spread, and gaps visible while retaining the raw values.

Use the same stem unit for both sides and label their reading direction. Continue in SciVis to improve spacing, headings, the key, and annotations without changing the underlying values.

How to interpret a stem-and-leaf plot

The stem holds the leading digit or digits; each leaf supplies the final digit at the scale defined by the key. Read the distribution by checking:

1. Where most leaves are concentrated.
2. How far the smallest and largest values extend.
3. Whether the shape is symmetric or skewed.
4. Whether gaps, clusters, or isolated observations appear.
5. Whether group differences persist on the same scale.

The display describes the sample. It does not establish normality, identify an observation as erroneous, or test a difference between groups.

Stem-and-leaf plot or histogram?

• Use a stem-and-leaf plot when the dataset is compact and readers should be able to recover every value.
• Use a histogram when bin counts and overall shape are more important than individual observations.
• Use a box plot for a compact comparison of median, quartiles, and potential outliers.
• Use a beeswarm plot when every observation should remain visible in a more flexible publication layout.

FAQ

Can I make a stem-and-leaf plot without calculating it by hand?

Yes. Upload a supported data file to the Stem-and-Leaf Plot Generator, verify the scale and key, and refine the display in SciVis.

How do I handle decimal values?

Choose a stem and leaf scale that preserves the necessary precision, then state it explicitly in the key. Do not silently round away scientifically relevant digits.

Can a stem-and-leaf plot include negative values?

Yes, but the sign, ordering, and key must be unambiguous. Reconstruct several negative observations from the finished display before export.

What sample size is too large?

There is no universal cutoff. When rows become dense, leaves wrap, or readers cannot compare stems quickly, a histogram, ECDF, or density plot is likely a better choice.

Create the figure

Start with the Stem-and-Leaf Plot Generator, verify several reconstructed values, and consult the scientific data visualization guide if the dataset needs a more scalable chart.