LabEx
Log InJoin For Free

Matplotlib Tutorials

Matplotlib offers a structured learning path for Python data visualization. Our tutorials cover various plot types, customization options, and best practices, suitable for both beginner and intermediate data scientists. With free labs and practical examples, you'll gain hands - on experience in creating informative and attractive visualizations. Our data visualization playground allows you to experiment with Matplotlib functions and see immediate graphical results.

Other Skill Trees

LinuxDevOpsCybersecurityDatabasePythonDockerKubernetesRed Hat Enterprise LinuxGitShellNmapWiresharkHydraJavaSQLitePostgreSQLMySQLRedisMongoDBGolangC++CAnsibleData ScienceMachine LearningPandasNumPyscikit-learnWeb DevelopmentHTMLCSSJavaScriptReactKali Linux
Customizing Matplotlib Visualizations

Customizing Matplotlib Visualizations

This lab will guide you through the process of customizing Matplotlib using style sheets and rcParams. Matplotlib is a powerful library for creating visualizations in Python. By customizing the properties and default styles of Matplotlib, you can create unique and visually appealing plots.
MatplotlibPython
Matplotlib Pyplot Interface Tutorial

Matplotlib Pyplot Interface Tutorial

This tutorial provides a step-by-step guide to using the pyplot interface in Matplotlib. The pyplot module is a collection of functions that make Matplotlib work like MATLAB, allowing you to easily create and customize plots. This tutorial assumes you have a basic understanding of Matplotlib and its concepts.
MatplotlibPython
Simple Axis Pad

Simple Axis Pad

This lab will teach you how to use the add_floating_axis function in Matplotlib to add floating axes to a plot, which can be used to display additional information about the plot. Specifically, you will learn how to adjust the padding of tick labels and axis labels, as well as how to adjust the position of ticks on the floating axes.
PythonMatplotlib
The Lifecycle of a Plot

The Lifecycle of a Plot

In this lab, we will explore the lifecycle of a plot using Matplotlib. We will start with raw data and end by saving a customized visualization. We will learn how to create a plot, control its style, customize its appearance, combine multiple visualizations, and save the plot to disk.
PythonMatplotlib
Image Plotting with Matplotlib

Image Plotting with Matplotlib

In this lab, you will learn how to plot and manipulate images using the Matplotlib library in Python. You will learn how to import image data into NumPy arrays, plot numpy arrays as images, apply pseudocolor schemes, add color scale references, examine specific data ranges, and explore different interpolation schemes.
MatplotlibPython
Create a Line Plot with Matplotlib

Create a Line Plot with Matplotlib

In this lab, we will learn how to create a line plot using Matplotlib. Line plots are a basic visualization that can be used to represent data points connected by straight line segments. We will use the Matplotlib library in Python to create a line plot.
PythonMatplotlib
Creating Matplotlib Subplots in Python

Creating Matplotlib Subplots in Python

Matplotlib is a Python library used for creating visualizations such as line plots, scatter plots, bar plots, and subplots, among others. In this lab, you will learn how to create a figure with two subplots using .pyplot.subplot.
PythonMatplotlib
Matplotlib 3D Quiver Plot

Matplotlib 3D Quiver Plot

In this lab, you will learn how to create a 3D quiver plot using Python Matplotlib. A quiver plot displays a vector field as arrows. The arrows point in the direction of the vectors and their length represents the magnitude of the vectors.
PythonMatplotlib
Matplotlib Rain Simulation

Matplotlib Rain Simulation

This lab is a step-by-step tutorial on how to create a rain simulation using Python's Matplotlib library. The simulation will animate the scale and opacity of 50 scatter points to simulate raindrops falling on a surface.
PythonMatplotlib
Vector Graphics Rasterization with Python

Vector Graphics Rasterization with Python

In this lab, you will learn about rasterization for vector graphics. Rasterization is a process of converting vector graphics into a raster image (pixels). It can speed up rendering and produce smaller files for large data sets, but comes at the cost of a fixed resolution. We will be using Python Matplotlib library to illustrate the concept of rasterization.
PythonMatplotlib
Matplotlib Text Object Concatenation

Matplotlib Text Object Concatenation

In this lab, you will learn how to concatenate text objects with different properties using Matplotlib. Concatenation is the process of combining multiple text objects into a single string. This can be useful when creating annotations or labels for visualizations.
PythonMatplotlib
Creating a Bezier Curve

Creating a Bezier Curve

In this tutorial, we will learn how to create a Bezier Curve using Python's Matplotlib library. A Bezier Curve is a mathematical curve that is commonly used in computer graphics to create smooth and aesthetically pleasing shapes. We will create a simple example of a Bezier Curve using Matplotlib's PathPatch object.
PythonMatplotlib
Create Radar Charts with Python Matplotlib

Create Radar Charts with Python Matplotlib

In this lab, you will learn how to create a radar chart using Python's Matplotlib library. A radar chart, also known as a spider or star chart, is a graphical method of displaying multivariate data in the form of a two-dimensional chart of three or more quantitative variables represented on axes starting from the same point. It is often used to compare different products or solutions based on several factors.
PythonMatplotlib
Matplotlib Radio Button Sine Wave Visualization

Matplotlib Radio Button Sine Wave Visualization

Radio buttons are a type of input element that allows users to select one option from a group of predefined options. In this lab, we will use the matplotlib library to create a visualization with radio buttons that let the user choose between different sine waves to be shown in the plot.
PythonMatplotlib
Matplotlib QuadMesh Plotting Tutorial

Matplotlib QuadMesh Plotting Tutorial

This tutorial will guide you through the usage of the Matplotlib library to create a QuadMesh plot. QuadMesh is a faster generalization of the pcolor function, but with some restrictions. The demo in this tutorial will illustrate a bug in QuadMesh with masked data.
PythonMatplotlib
Thresholding an Image with RangeSlider

Thresholding an Image with RangeSlider

This lab will demonstrate how to use the RangeSlider widget in Matplotlib to control the thresholding of an image. The purpose of thresholding is to convert a grayscale image into a binary image, where the pixels are either black or white. This is useful for image segmentation, where we want to extract certain features from the image.
PythonMatplotlib
Drawing Shapes with Matplotlib Widgets

Drawing Shapes with Matplotlib Widgets

In this lab, we will learn how to use the RectangleSelector and EllipseSelector widgets in Matplotlib to draw a rectangle or ellipse from the initial click position to the current mouse position.
PythonMatplotlib
Matplotlib Quiver Plot

Matplotlib Quiver Plot

This lab will guide you through how to create a quiver plot using Matplotlib in Python. A quiver plot displays vector fields as arrows. It is useful in visualizing fluid flows, electric and magnetic fields, and other types of vector fields.
PythonMatplotlib
  • Prev
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • ...
  • 28
  • Next