By Sandro Tosi
ISBN-10: 1847197906
ISBN-13: 9781847197900
This booklet is ready Matplotlib, a Python package deal for second plotting that generates creation caliber graphs. Its number of output codecs, numerous chart kinds, and potential to run both interactively (from Python or IPython consoles) and non-interactively (useful, for instance, whilst integrated into net applications), makes Matplotlib compatible to be used in lots of diverse occasions.
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Extra info for Matplotlib for Python Developers
Sample text
Consider these two buttons and the home one just like the buttons in a web browser: Home takes you back to the first view, while the back and forward buttons navigate between the views defined during this session (they have no effect if nothing has been done so far). We can use this button in two different modes: pan and zoom. 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.
Adding labels Now that we know how to manage the axes dimensions, another important piece of information to add to a plot is the axes labels, since they usually specify what kind of data we are plotting. show() [ 31 ] Getting Started with Matplotlib Note how we have defined the labels between the plot() call and the actual show() of the image. During this interval, many annotations are possible, and labels are just an example. Titles and legends We are about to introduce two other important plot features—titles and legends.
Control marker styles Markers are, by default, drawn as point markers. They are just a location on the figure where segments join. Matplotlib provides a lot of customization options for markers. The following table contains a list of the available styles: Marker abbreviation .