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.
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.
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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.
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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.
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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.
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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.
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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.
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Zoom Inset Axes
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.
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Matplotlib Event Handling Tutorial
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.
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Adjusting Matplotlib Drawing Order
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.
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Matplotlib Anchored Objects
In this lab, you will learn how to use Anchored Objects in Matplotlib. Anchored Objects are used to add auxiliary objects to a plot. These objects can be used to add annotations, scale bars, and legends to a plot.
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Add Angle Annotations to Matplotlib Arrows
In this lab, you will learn how to add angle annotations to bracket arrow styles created using FancyArrowPatch in Matplotlib. Angle annotations are useful for indicating the direction and size of angles in a plot. By the end of this lab, you will be able to create bracket arrow styles with angle annotations and customize them to fit your specific needs.
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Creating Animated Plots with Matplotlib
Matplotlib is a data visualization library used to create static, animated, and interactive visualizations in Python. In this lab, we will learn how to create an animated plot using Matplotlib. We will use the FuncAnimation class to create an animation of a decaying sine wave.
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Animated Histogram Using Matplotlib
In this lab, you will learn how to create an animated histogram using Matplotlib in Python. The animated histogram will simulate new data coming in and update the heights of rectangles with the new data.
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Simple Matplotlib Animation Tutorial
This tutorial will guide you through how to create a simple animation using matplotlib.pyplot. Animations can be useful for visualizing data that changes over time. In this tutorial, we will generate a random set of data and display it as an animation.
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Matplotlib Visualization Fundamentals
In this lab, you will learn how to use Matplotlib, a Python library for creating visualizations, to create a figure and annotate its anatomy. You will learn how to create a figure, plot data, set axis limits, add labels and titles, and annotate the figure with text and markers.
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Align Matplotlib Axis Labels
In data visualization, it is important to have clear and properly aligned labels for the x and y axes. Matplotlib provides several functions to help align these labels properly. In this lab, we will use the align_xlabels and align_ylabels functions to align the labels in our plot.
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Matplotlib Affine Transformation
This lab demonstrates how to use Matplotlib to perform affine transformation of an image. Affine transformations change the shape and orientation of an image. This lab shows how to use the transforms.Affine2D function to manipulate the shape and orientation of an image.
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Matplotlib Accented Text Visualization
Matplotlib is a library in Python used for data visualization. It supports accented characters via TeX mathtext or Unicode. This tutorial will demonstrate how to use accented text in Matplotlib.
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