Stem and Leaf Plot Maker
Dataset 1 (Left)
Dataset 2 (Right)
Stem and Leaf Plot Examples
Click any example to load it into the tool above
What Is a Stem and Leaf Plot?
A stem and leaf plot (also called a stem and leaf diagram or stem plot) is a simple statistical display that organizes numerical data into an ordered, two-column layout. Each observation is split into a stem — the leading digit or digits — and a leaf — the final digit. The stems form a vertical column, and each corresponding leaf is written to the right, sorted in ascending order.
Unlike a histogram, a stem and leaf plot retains the exact value of every data point. This makes it uniquely useful for small-to-medium datasets (roughly n < 100) where you want to see both the shape of the distribution and the actual numbers at the same time. It was popularized by statistician John Tukey as part of his Exploratory Data Analysis (EDA) toolkit and remains a standard tool in introductory statistics education, quality control, and data inspection workflows.
The statistics fundamentals covered by a stem and leaf plot include distribution shape, center, spread, and the presence of outliers — all visible at a glance without any calculation.
How to Create a Stem and Leaf Plot: Step-by-Step
The following walkthrough uses the dataset: 22, 11, 15, 34, 25, 12, 22, 51, 27.
Sort the dataset in ascending order
Arrange all values from smallest to largest: 11, 12, 15, 22, 22, 25, 27, 34, 51. Every leaf row will be in order once you build from this sorted list.
Identify the stems and leaf unit
The data spans 11 to 51. Using the tens digit as the stem gives stems of 1, 2, 3, 4, and 5. The ones digit is the leaf. The key reads: stem | leaf = value, so 2 | 5 = 25.
Write the stems and map the sorted leaves
List every stem from minimum to maximum in a vertical column, including stems with no data. Place the leaves in sorted order next to each stem.
2 | 2 2 5 7
3 | 4
4 |
5 | 1
Add a key
Always include a key so the plot can be read unambiguously: Key: 1 | 2 = 12. Without it, the same plot could represent different scales.
Read the statistics directly from the plot
Count leaves to find n = 9. The median sits at the 5th leaf in order, which is 22. The minimum is 11, maximum is 51, and the mode is 22 (appears twice in the 2-row).
Types of Stem and Leaf Diagrams
Stem and Leaf Plot vs Other Visualizations
| Visualization | Exact Data | Best Dataset Size | Primary Use |
|---|---|---|---|
| Stem & Leaf Plot | Yes (100%) | n < 100 | Distribution shape + raw value inspection |
| Histogram | No (binned) | n > 100 | Density contour, large continuous data |
| Box Plot | No (5-number) | Any | Quartiles, skewness, outliers at a glance |
| Dot Plot | Yes | n < 50 | Discrete frequency, small count data |
| Scatter Plot | Yes | Any | Bivariate relationship between two variables |
Finding the Median and Quartiles from a Stem Plot
One of the most practical uses of a stem and leaf display is locating the median without calculation. Count the total number of leaves (n). The median position is (n + 1) / 2 for odd n, or the average of the n/2-th and (n/2 + 1)-th values for even n. Count through the leaves in order — across rows from top to bottom — until you reach that position.
For quartiles, split the ordered leaf list at the median and find the median of each half: Q1 is the median of the lower half and Q3 is the median of the upper half. The IQR = Q3 − Q1. Tukey's outlier fences are Q1 − 1.5 × IQR (lower) and Q3 + 1.5 × IQR (upper). Any value outside those fences is flagged as an outlier.
Outliers appear visually as isolated leaves separated from the main cluster by a gap in the rows — one of the strongest features of the stem plot format. You can cross-check outlier detection using the Descriptive Statistics Calculator.
Common Mistakes to Avoid
- Unsorted leaves: Leaves must be listed in ascending order within each row. Leaving them in the original data order makes the plot unreadable.
- Skipping empty stems: A stem with no data must still appear as a row with no leaves. Omitting it distorts the distribution shape and hides gaps.
- Leaves longer than one digit: Each leaf is always exactly one digit. If a value has multiple trailing digits, adjust the stem unit or round appropriately.
- Missing the key: The plot is ambiguous without a key. Always include something like Key: 2 | 3 = 23.
- Using it for large datasets: For n > 100, switch to a histogram. Long leaf strings destroy the visual advantage of the stem plot.
Related Topics
Sources & further reading:
- Tukey, J.W. (1977). Exploratory Data Analysis. Addison-Wesley. [Origin of the stem-and-leaf plot]
- NIST Engineering Statistics Handbook — Stem-and-Leaf Plots
- Khan Academy — Stem and Leaf Plots Review
- Verzani, J. (2014). Using R for Introductory Statistics. CRC Press.
Frequently Asked Questions
A stem and leaf plot maker is an interactive statistical tool that organizes raw numerical data into an ordered, split-column graphical display. It separates each value into a stem (leading digits) and a leaf (trailing digit), retaining all original values while revealing the distribution shape, frequency, and center of the dataset. This tool supports standard, split, and back-to-back formats with full descriptive statistics output.
Count the total number of leaves (n). For an odd count, the median sits at position (n+1)/2 — count sequentially through the ordered leaves, left to right across each row and top to bottom, until you reach that position. For an even count, average the values at positions n/2 and n/2+1. The plot's ordered layout makes this count straightforward without any additional sorting.
A standard stem plot uses one row per stem value. A split stem plot divides each stem into two rows: one for leaves 0–4 and one for leaves 5–9. Use the split format when a standard row contains so many leaves that the distribution shape is obscured. For example, a stem of 7 with leaves 0,1,1,2,2,3,4,5,6,7,8,9 is cleaner when split into 7(0–4): 0 1 1 2 2 3 4 and 7(5–9): 5 6 7 8 9.
In a back-to-back plot, the stem column sits in the center. The right dataset's leaves are read normally (left to right). The left dataset's leaves are read in reverse — from the stem outward to the left. So if the left side shows 4 2 1 | 3, you read those leaves as 31, 32, and 34. This lets you compare two groups directly: the row lengths show relative frequency, and the leaf positions show where values cluster.
Stem and leaf plots work best for small-to-medium datasets (n < 100). With larger datasets, leaf rows become so long they lose all visual meaning. For n > 100, a histogram communicates distribution shape far more clearly. Also avoid stem plots when the data spans a very wide range with many empty stems, or when comparing more than two groups (a box plot handles multiple-group comparison better).
Yes. For data like 12.3, 12.8, 13.1, the stem is the integer part (12, 13) and the leaf is the first decimal digit (3, 8, 1). The key would read: 12 | 3 = 12.3. This tool auto-detects decimal data and sets the leaf unit accordingly. You can also manually select the leaf unit in the settings if you want to control the precision.