What is Matplotlib?

Matplotlib is a comprehensive 2D plotting library for the Python programming language.
It is widely used for creating static, animated and interactive visualizations in Python.
Matplotlib was developed by John D. Hunter and is now maintained by a huge team of developers.
It is open-source and freely available for use under the BSD license.

To install matplotlib type the following command in the terminal

pip install matplotlib

to Check the version of Matplotlib:

print('Matplotlib version:', matplotlib.__version__)

Matplotlib Backends

Matplotlib can use different backends for rendering plots. The default might not be the best for your needs. To check the current backend, use the following code:

print('Matplotlib backend:', matplotlib.get_backend())

Check the backend of Matplotlib

to check the current backend, use the following code:

print('Matplotlib backend:', matplotlib.get_backend())

To set a different backend

You can set a different backend using the following code:

import matplotlib matplotlib.use('TkAgg') # Example for TkAgg backend

Common backends include

The most common backends include:

TkAgg (default for Python’s Tkinter)
Qt5Agg (for Qt5)
Agg (for PNG and other file formats, no interactive window)

Set a different backend

You can set a different backend using the following code:

matplotlib.use('TkAgg')  # Example for TkAgg backend

Check the new backend of Matplotlib

to check the new backend, use the following code:

print('Matplotlib backend:', matplotlib.get_backend())

The Matplotlib Interface

Matplotlib has two interfaces:

MATLAB-style interface (stateful)
Object-oriented interface (stateless)

The object-oriented interface is recommended for more control and customization.

Import the pyplot module

The most common way to use Matplotlib is through the pyplot module. You can import it using the following code:

import matplotlib.pyplot as plt

# Create a simple plot
plt.plot([1, 2, 3, 4, 5], [1, 4, 9, 16, 25])
plt.show()

# Create a scatter plot
plt.scatter([1, 2, 3, 4, 5], [1, 4, 9, 16, 25])
plt.show()

# Create a bar plot
plt.bar([1, 2, 3, 4, 5], [1, 4, 9, 16, 25])
plt.show()

# Create a histogram
plt.hist([1, 2, 3, 4, 5])
plt.show()

# Create a pie chart
plt.pie([1, 2, 3, 4, 5])
plt.show()

# Create a box plot
plt.boxplot([1, 2, 3, 4, 5])
plt.show()

# Create a violin plot
plt.violinplot([1, 2, 3, 4, 5])
plt.show()

# Create a heatmap
plt.imshow([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
plt.colorbar()
plt.show()

Additional dependencies

Matplotlib can be used with other libraries like NumPy, SciPy, and Pillow to enhance its capabilities.

NumPy

NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

SciPy

SciPy is a free and open-source library for the Python programming language that adds support for scientific and technical computing. It builds on the capabilities of NumPy and provides a large number of higher-level functions that operate on NumPy arrays and are useful for different types of scientific and engineering applications.

Pillow (PIL)

Pillow is a free and open-source library for the Python programming language that adds support for opening, manipulating, and saving many different image file formats. It is a fork of the Python Imaging Library (PIL) and provides a more up-to-date and actively maintained version of the library.

Conclusion

Matplotlib is a powerful library for creating visualizations in Python. It is widely used for creating static, animated, and interactive plots. It has a MATLAB-style interface and an object-oriented interface. It can be used with other libraries like NumPy, SciPy, and Pillow to enhance its capabilities.

julioaranajr/using_matplotlib