![]() We also set the blit parameter to True, which improves the performance of the animation. It then updates the line object using the set_data method and returns the line object.įinally, we create an animation object using the FuncAnimation class and pass in the figure, the update function, and the range of frames. The function appends the frame number to the x_data list and the square of the frame number to the y_data list. We then define the update function, which takes the frame number as an argument. We also define a line object using the plot method of the axis object. We define two empty lists, x_data and y_data, which will store the x and y coordinates of the plot. We then create a figure and an axis object using the subplots method. We first import the necessary modules, including matplotlib.pyplot and matplotlib.animation. In this example, we create a simple animation that plots the square of the frame number. set_data ( x_data, y_data ) return line, animation = FuncAnimation ( fig, update, frames = range ( 10 ), blit = True ) display ( HTML ( animation. subplots () x_data = y_data = line, = ax. Import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation fig, ax = plt. This function is called the update function. ![]() To create an animation in Matplotlib, you need to define a function that updates the data at each frame. Matplotlib provides an Animation class that allows you to create animations in Python. Creating an Animation in MatplotlibĪnimations are a great way to visualize data over time. Jupyter Notebook is widely used in data science to create and share interactive reports. It supports a variety of programming languages, including Python, R, and Julia. Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. Matplotlib is widely used in the scientific community for creating visualizations of data. It provides a wide range of customization options and supports a variety of data formats. Matplotlib is a data visualization library that allows you to create a variety of charts and plots in Python. ![]() ![]() In this article, we will discuss how to create and visualize animations in Matplotlib using Jupyter Notebook. Matplotlib is a popular library that allows you to create visualizations in Python. | Miscellaneous How to Visualize Matplotlib Animation in Jupyter NotebookĪs a data scientist or software engineer, you may often need to visualize data in various formats. ![]()
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