Data Visualization Using Matplotlib and Seaborn

Introduction

We explore how to do various visualizations using the matplolib and seaborn libraries in Python.

We shall learn the following in this tutorial:

The fundamentals of plotting figures
Creating sub-plots in Python
Creating animations in Python

To decide which software to use between R and Python for data visualization you can watch this video.

Fundamentals of Plots in Python

The first step is to install and import the libraries matplolib.pylot module that is used for basic plots like line and bar charts. It is often imported with the alias plt.

We shall use the seaborn module for more advanced plots that is imported as sns

To install use

!pip install seaborn

on the Jupyter Notebook Environment.

To call the module to the environment use

import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline

The purpose of the command %matplotlib inline is to ensure that the plots are shown and embedded within the Jupyter Notebook Itself.

Without the command the plots may sometimes show in pop-up windows.

Line Graph

import matplotlib.pyplot as plt
import seaborn as sns
yield_maize = [0.895, 0.91, 0.919, 0.926, 0.929, 0.931]
plt.plot(yield_maize)
plt.show()

Customizing the x-axis

We can add the year in the x-axis and have

year = [2021,2022,2023,2024,2025,2026]
yield_maize = [0.895, 0.91, 0.919, 0.926, 0.929, 0.931]
plt.plot(year,yield_maize)
plt.show()

Axis Labels

plt.plot(year, yield_maize)
plt.xlabel("Year")
plt.ylabel("Yield")
plt.title("Yield Harvest per year")

Text(0.5, 1.0, 'Yield Harvest per year')

Line Markers

For line graphs, you can have markers for the line you are plotting. See full details of line markers in matplotlib

plt.plot(year, yield_maize, marker = "o")
plt.xlabel("Year")
plt.ylabel("Yield")
plt.title("Yield Harvest per year")

Text(0.5, 1.0, 'Yield Harvest per year')

Styling the Lines

The function plt.plot supports many arguments for styling markers and the lines

color or c This sets the line color
ls Gives you to choose between solid or dashed line
lw sets the line width

To see more details of the function see the documentation

Using Seaborn

To make your chart more appeasing you use some default styles form Seaborn library.

Whitegrid style

sns.set_style("whitegrid")
plt.plot(year, yield_maize, marker = "o")
plt.xlabel("Year")
plt.ylabel("Yield")
plt.title("Yield Harvest per year")

Text(0.5, 1.0, 'Yield Harvest per year')

darkgrid style

sns.set_style("darkgrid")
plt.plot(year, yield_maize, marker = "o")
plt.xlabel("Year")
plt.ylabel("Yield")
plt.title("Yield Harvest per year")

Text(0.5, 1.0, 'Yield Harvest per year')