The chart you can rebuild the data from
A stem-and-leaf plot splits each value into a stem (all digits but the last) and a leaf (the last digit). Stems run down the left; leaves, sorted, run right. The result reads as a sideways histogram with a rare property: every original value survives inside it. From the leaves you can reconstruct the dataset exactly, recompute anything, and check anyone's summary against the raw evidence.
The twenty commute times, 22 to 38 minutes. Stem 2 collects leaves 2 3 4 4 6 6 7 7 7 7 8 8 9 9; stem 3 collects 0 1 1 3 5 8. Read sideways: a heavy pile in the twenties, a thinning run through the thirties, and the shape matches the histogram of the same data. The key line "2 | 4 means 24" anchors the scale; forget the key and the plot is a riddle.
Where stem-and-leaf still earns its keep
Exams love it because it tests ordering and place value at once. Analysts used it in the pre-software era because it could be drawn by hand while data arrived. Today its niche is transparency: small datasets presented in full, in reports where the reader should be able to audit every number. Sorting leaves as you write them is the discipline: unsorted leaves make a plot that technically contains the data and practically hides it.
Choosing stems that produce one giant row. If all values share a stem (everything between 100 and 199, stem 1), split stems: 10, 11, 12 as separate rows, or drop a digit and use the hundreds as leaves in pairs. The plot should spread the data over five to fifteen rows to show shape.
Decimals and negatives
The split point is a modelling choice: 3.7 can be stem 3, leaf 7 (key: 3 | 7 = 3.7) or stem 0, leaves 37 with a different key. This tool rounds to whole numbers and uses tens as stems, the textbook default; the key printed with the plot always states the convention.
Frequently asked questions
How do I read a stem-and-leaf plot?
Join stem and leaf back together: stem 2 with leaf 4 is 24. The key line on any good plot states the scale. Leaves are read in sorted order along each row.
What is the difference from a histogram?
Same sideways shape, but the leaves are the actual data digits. A histogram only preserves counts per bin; the stem-and-leaf preserves every value and lets you rebuild the dataset.
Why are my values rounded?
Leaves are single digits, so values are rounded to whole numbers to form them. For finer data, the stem takes more digits; this tool follows the standard tens split.