We recommend using IPython (see below). The pyplot module provides functions for explicitly creating figures that include interactive tools, a toolbar, a tool-tip, and key bindings: Creates a new empty Figure or selects an existing figure. Creates a new Figure and fills it with a grid of Axes. Get the current Figure.

Jan 10, 2013 · I am using IPython with --pylab=inline and would sometimes like to quickly switch to the interactive, zoomable matplotlib GUI for viewing plots (the one that pops up when you plot something in a terminal Python console). How could I do that? Preferably without leaving or restarting my notebook.

In this brief guide, we will walk you through creating interactive plots with matplotlib. Here's a requirements.txt file you can use to install all the libraries necessary to create an interactive plot:

Jun 6, 2023 · You can make your Matplotlib plots interactive by using an interactive backend like 'notebook' or 'widget'. In a Jupyter notebook, you can use the %matplotlib notebook magic command to enable interactive mode.

Apr 19, 2024 · Getting interactive plots in Spyder, IPython, and Matplotlib in Python 3 allows for a more engaging and dynamic data visualization experience. By enabling interactive mode and utilizing functions like set_data() and canvas.draw() , …

mpl_interactions’ aims to make it as easy as possible to create responsive Matplotlib plots. In particular, you can: Better understand a function’s change with respect to a parameter. Visualize your data interactively. To achieve this, mpl_interactions provides: A way to control the output of pyplot functions (e.g. plot() and hist()) with sliders.

We’ll explore how to move beyond static images and build truly clickable plots using Matplotlib, Flask, and other powerful tools. This will allow you to create dynamic and responsive charts that go far beyond simple PNG exports.

ipywidgets are interactive HTML elements that can be used in Jupyter Notebooks to interact with outputs such as tables and charts. This article briefly introduces ipywidgets and uses them to change the rolling day period in a chart for the rolling average of deaths from covid-19.

Mar 31, 2020 · To get started, we set the ipympl backend, which makes matplotlib plots interactive. We do this using a magic command , starting with %. We also import some libraries: matplotlib for plotting, NumPy to generate data, and ipywidgets for obvious reasons.

Sep 29, 2021 · But did you know that it is also possible to create interactive plots with matplotlib directly, provided you are using an interactive backend? This article will look at two such backends and how they render interactivity within the notebooks, using only matplotlib.