Histograms are extremely useful when you want to do some data exploration.

With boxplot, you can have visual representation of a distribution and can determine what kind of data you are looking at.

Is there an observable minima and maxima, what is the sample average you can get if you randomly take some observations ?

Here is a simple example of an boxplot, using the matplotlib library.

import matplotlib.pyplot as plt
import pandas as pd

# We read a sample dataset from the web.
df = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv')

fig, axes = plt.subplots(1,1, figsize=(8,6))

# We do a boxplot plot on the axes
axes.boxplot(df["sepal_length"])

# We set a title
axes.set_title("Sepal Length Histogram")

# Fixing the layout to fit the size
fig.tight_layout()

# Showing the plot
plt.show()

As we can see we are using the axes.boxplot() method that will plot an boxplot given a list or pd.Series of values.

In this example, we are plotting the histogram of the sepal_length column.

Here is the result.

Here you are ! You now know how to make boxplots.

More on plots

If you want to know more about how to add labels, plot different types of plots, etc... checkout the other articles I wrote on the topic, just here :

Matplotlib - The Python You Need

We gathered the only Python essentials that you will probably ever need.

The Python You Need