# Stem and Leaf Plots in Python [Easy Guide]

Filed Under: Python Modules In this tutorial, we will learn about Stem and Leaf graphs and we will also look at their implementation. A `stem-and-leaf plot` is a chart that displays data by splitting up each data value in the dataset into a stem and a leaf before plotting the points. A stem-and-leaf plot is also called a `stemplot`.

## Importance of Stem and Leaf Plots

Stem-and-leaf plots are useful for displaying the `relative density` and help to give the reader a quick overview of the `distribution`. They are also useful for highlighting outliers and finding the mode of the dataset.

## Code Implementation for Stem and Leaf Plots in Python

We will be executing the following code snippets to create the plots for a dataset in Python. To create a stem-and-leaf plot for any dataset, we will make use of the `stemgraphic` library. You can install the same using the statement below.

```pip install stemgraphic
```

We will make use of `numpy` module and the `random.randint` function to get 20 numbers between 20 and 50.

```import numpy as np
data = np.random.randint(20, 50, 20)
print(data)
```

When we execute the above code, we get the dataset as follows.

```[33 28 21 22 37 45 23 45 36 24 20 45 43 24 45 21 20 43 21 47]
```

Next, we make use of the `stem_graphic` function of the `stemgraphic` module to automatically divide data into stems and leafs using the code below.

```import stemgraphic
fig, ax = stemgraphic.stem_graphic(data)
```

I bet you are not able to understand a thing about this plot and what exactly are you supposed to interpret from the plot. You can understand the interpretations from the following statements :

The red boxes display the minimum and the maximum number of the dataset where the bottom represents the minimum and the top represents the maximum.

The numbers in the far left display the `aggregated count` of values in the plot. Also, the numbers in the middle column represent the `stems` for the dataset. Lastly, the numbers in the far right column represent the `leaves` of the dataset.

## Another Illustration with the Complete Code

Let us have a look at another example and the complete code for the plotting of the stem-and-leaf plot in the Python programming language.

```import stemgraphic
import numpy as np

data = np.random.randint(20, 50, 20)
print(data)

fig, ax = stemgraphic.stem_graphic(data)
```