Download Matplotlib for Python Developers by Sandro Tosi PDF

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By Sandro Tosi

This can be a functional, hands-on ebook, with loads of code and pictures. It provides the genuine code that generates each snapshot and describes virtually each line of it, so you understand precisely what is going on. Introductory, descriptive, and theoretical elements are combined with examples, in order that examining and knowing them is simple. all the examples construct steadily with code snippets, their factors, and plot photographs the place worthy with the whole code and output awarded on the finish. This ebook is largely for Python builders who've a superb wisdom of Python; no wisdom of Matplotlib is needed. you may be growing 2nd plots utilizing Matplotlib very quickly in any respect.

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Extra info for Matplotlib for Python Developers

Example text

Click on this button to enable it, and move the mouse into the figure area. The two views are described as follows: • Pan: Click on the left mouse button and hold it to pan the figure, dragging it to a new position. Once we're happy with the position, release the mouse button. While panning, if we press (or hold) the x or y key, then the panning is limited to the selected axis. • Zoom: Click on the right mouse button and hold it to zoom the figure, dragging it to a new position. Movement to the right or to the left generates a proportional zoom in or out of the X-axis of the figure.

We might be also interested in the keyword argument transparent, which if set to True will generate a file with a transparent background. This could be useful if, for example, we're going to include that image in a web page which has a colored background. Interactive navigation toolbar If you have tried some of the book examples proposed so far, then you may have already noticed the interactive navigation toolbar (because when using matplotlib. show() It's worth taking the time to learn more about this window, since it provides basic elaboration and manipulation functions for interactive plotting.

Summary If you've arrived here, now you know: • How to create single or multiline plots handling the axes limits • How to add information to the plot such as legends, labels, and titles • How to save plots to a file for reuse • How to use the toolbar that the interactive window provides • Why IPython is so useful in collaboration with Matplotlib • How to customize Matplotlib to your needs (both from configuration files and from Python code) But we have only scratched the surface of what Matplotlib can do.

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