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Yes, it is possible to create a stem-and-leaf plot in Python. This can be done by using the stemgraphic package, which is a library that provides functions for creating a stem-and-leaf plot from a list of numerical data. The package also provides various options for customizing the plot, such as adjusting the stem width and leaf size. Additionally, the package allows for the data to be automatically sorted, so that the stem-and-leaf plot can be generated quickly and easily.
A stem-and-leaf plot is a chart that displays data by splitting up each value in a dataset into a stem and a leaf. It’s a unique plot because it helps us visualize the shape of a distribution while still displaying the raw individual data values.
This tutorial explains how to create a stem-and-leaf plot in Python.
Example: Stem-and-Leaf Plot in Python
Suppose we have the following dataset in Python:
x = [32, 34, 35, 41, 44, 46, 47, 52, 52, 53, 56, 61, 62]
To create a stem-and-leaf plot for this dataset, we can use the stemgraphic library:
pip install stemgraphic
Once this is installed, we can use the following code to create a stem-and-leaf plot for our dataset:
import stemgraphic #create stem-and-leaf plot fig, ax = stemgraphic.stem_graphic(x)
The way to interpret this plot is as follows:
- The number in the red box at the bottom of the plot displays the minimum number in the dataset (32).
- The number in the red box at the top of the plot displays the maximum number in the dataset (62).
- The numbers in the far left display the aggregated count of values in the plot. For example, the first row contains 2 aggregated values, the second row contains 3 aggregated values, the third row contains 5 aggregated values, and so on.
- The numbers in the middle column display the stems, which are 3, 4, 5, and 6.
- The numbers in the far right column display the leaves.
This single plot provides us with a ton of information about the distribution of values in this dataset.
An Introduction to Stem-and-Leaf Plots
Stem-and-Leaf Plot Generator