Matplotlib Tutorials

This lab is designed to provide a step-by-step guide for using Matplotlib, a Python library for creating visualizations. Matplotlib is a popular data visualization tool in the scientific and engineering communities. This tutorial will walk you through the process of creating visualizations using Matplotlib.

This lab is designed to introduce you to the basics of data visualization using Matplotlib. Matplotlib is a popular data visualization library for Python that provides a wide range of options for creating plots, graphs, and charts.

In this tutorial, you will learn how to use Matplotlib to create visualizations in Python. Matplotlib is a popular data visualization library in Python used to create a variety of charts and graphs. With Matplotlib, you can create line plots, scatter plots, bar plots, histograms, and many other types of visualizations.

Hi there, welcome to LabEx! In this first lab, you'll learn the classic 'Hello, World!' program in Matplotlib.

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.

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.

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.

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.

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.

Matplotlib is a data visualization library that provides various tools to create 2D and 3D plots. It is built on top of the NumPy library and its main purpose is to visualize data in a simple and effective way. In this tutorial, we will learn how to create two different types of plots using the xkcd style from the XKCD webcomic.

This lab is a step-by-step tutorial on how to connect events in one window, for example, a mouse press, to another figure window in Python Matplotlib.

The purpose of this lab is to demonstrate the use of cross-correlation and auto-correlation plots using the Python Matplotlib library. Cross-correlation and auto-correlation are mathematical tools used to measure the similarity between two signals. Cross-correlation measures the similarity between two different signals, while auto-correlation measures the similarity between a signal and a time-delayed version of itself. These tools are commonly used in signal processing, image analysis, and time series analysis.

Matplotlib is a Python library used for creating static, animated, and interactive visualizations in Python. It is a powerful tool for data visualization, and it is widely used in the scientific community. In this lab, we will learn how to create a zoomed-in region in a Matplotlib plot.

In this tutorial, we will learn about the drawing order of artists in Matplotlib and how to adjust the order using the zorder attribute. We will also explore how to change the order for individual artists and the default value of zorder for different types of artists.

In this lab, we will learn how to animate a 3D wireframe plot using Matplotlib, a popular data visualization library in Python.

This lab will guide you through creating a 3D wireframe plot using Python's Matplotlib library. A wireframe plot is a visual representation of a 3D surface where lines are drawn between each point on the surface. This type of plot is useful for visualizing complex 3D data and can be customized to create impressive visualizations.

This lab is designed to show you how to create a 3D wireframe plot in Python using Matplotlib. A wireframe plot is a visual representation of a three-dimensional surface that displays the structure of the surface using lines. In this lab, we will show how to set the rstride and cstride parameters to control the density of the lines in the plot.

This tutorial will guide you through the process of adding a cursor in WX to report data coordinates. We will be using Matplotlib, a plotting library for Python that provides tools to create a variety of plots, charts, and graphs.