Stem and Leaf Plot Calculator

Paste a list of numbers to build a sorted stem-and-leaf plot and read off the count, minimum, maximum, median, and mode.

Quick Facts

Method
Split each value into a stem (leading digits) and a leaf (last digit)
Leaves are sorted within each stem, so the plot is a sorted histogram made of the real digits.

Your Results

Calculated
Count (n)
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How many values
Minimum
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Smallest value
Maximum
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Largest value
Median
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Middle value
Stem-and-leaf plot
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Ready

Enter your numbers and select Build Plot.

What a stem-and-leaf plot is

A stem-and-leaf plot (also called a stemplot) is a way of displaying a small-to-medium set of numbers so that you can see the shape of the data and still recover every original value. Each number is split into two parts: the leaf is the final digit, and the stem is everything to the left of it. The stems are written in a column, and the leaves for each stem are listed to the right in increasing order. The result looks like a sideways histogram, except the bars are made of the actual digits instead of blank rectangles.

For example, the values 42, 44, and 47 all share the stem 4 and produce the row 4 | 2 4 7. Reading it back, you reattach each leaf to its stem to get 42, 44, and 47.

How each value is split

  • Two-digit numbers (10–99): tens digit is the stem, units digit is the leaf. So 63 becomes stem 6, leaf 3.
  • Three-digit numbers (100–999): the first two digits are the stem and the last digit is the leaf. So 128 becomes stem 12, leaf 8.
  • One-digit numbers (0–9): the stem is 0 and the digit itself is the leaf. So 7 becomes stem 0, leaf 7.

The key rule is consistency: every value must be split at the same place value so the stems line up and the length of each row honestly reflects how many values fall in that interval.

Why it is useful

Unlike a bar chart or histogram, the stem-and-leaf plot loses no information — the raw data is still readable. In one glance you can see the overall shape (symmetric, skewed, or bimodal), spot gaps and clusters, find the minimum and maximum, and locate the median simply by counting inward from both ends. It is a favorite in introductory statistics because it is quick to draw by hand and doubles as a sorted list.

Reading center and spread from the plot

  • Median: because the leaves are already sorted, the median is the middle value — count in from either end. With an even count, average the two middle values.
  • Mode: the value (or values) that appear most often; a repeated leaf in the same row signals it.
  • Range: maximum minus minimum, both read directly off the top and bottom rows.
  • Shape: a long tail of leaves toward the larger stems indicates right skew; toward the smaller stems, left skew.

Frequently Asked Questions

How do you read a stem-and-leaf plot?
Each row is a stem (the leading digit or digits) followed by its leaves (the final digit of every value in that range). To rebuild a value, attach a leaf to its stem: a stem of 4 with a leaf of 7 means 47. The leaves in each row are written in increasing order, so the plot is really a sorted list of the data drawn sideways as a histogram made of the actual digits.
What is the difference between a stem and a leaf?
The leaf is always the last digit of the number; the stem is everything to its left. For 63 the stem is 6 and the leaf is 3. For 128 the stem is 12 and the leaf is 8. Every value in the dataset must be split at the same place value so the stems line up and the row lengths honestly show how many values fall in each interval.
Can a stem-and-leaf plot handle decimals or large numbers?
Yes, with a chosen key. For decimals like 3.4, 3.7, 4.1 you can let the whole number be the stem and the tenths be the leaf (stem 3, leaves 4 and 7). For large numbers you round or truncate to two significant places — e.g. 1,240 and 1,270 become stem 12, leaves 4 and 7 with a key of "12 | 4 = 1,200s." This calculator splits at the units digit, so it is best suited to whole numbers roughly in the 0–9,999 range.
When should I use a stem-and-leaf plot instead of a histogram?
Use a stemplot for small datasets (roughly 15–100 values) when you want to keep the exact numbers visible and sort the data at the same time. Switch to a histogram when you have hundreds or thousands of values, or when the digits themselves do not matter and you only care about the shape of the distribution.

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