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The dependencies are `matplotlib <https://matplotlib.org/>`_ and `numpy <http://www.numpy.org/>`_. The optional geographic mapping features require `cartopy <https://scitools.org.uk/cartopy/docs/latest/>`_ and/or `basemap <https://matplotlib.org/basemap/index.html>`_.
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Documentation
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-------------
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The documentation is published `here <https://lukelbd.github.io/proplot>`_.
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Overview
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--------
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import proplot as plot
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Most of the features derive from the `subplots` command, inspired
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by the pyplot `subplots` command.
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Most of the features derive from the ``subplots`` command, inspired
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by the pyplot command of the same name.
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The next most important utility is the `format` method, available on every axes generated by `subplots`. Use this method to fine-tune your axis properties, titles, labels, limits, and much more.
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The next most important utility is the ``format`` method, available on every axes generated by ``subplots``. Use this method to fine-tune your axis properties, titles, labels, limits, and much more.
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Here are some highlights of the remaining features:
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scaling.
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* Perceptually distinct named colors with easy-to-remember names,
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a ton of beautiful new colormaps, new property cycle colors.
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* Tools for making new make new merged colormaps and "perceptually
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uniform colormaps" on-the-fly. Tools for slicing and modifying existing
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* Tools for merging existing colormaps and making new "perceptually
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uniform" colormaps on-the-fly. Tools for slicing and modifying existing
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colormaps.
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* Making colorbars from lists of lines
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or colors. Making axes "inset" colorbars. Making legends with centered
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rows instead of aligned columns.
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* Integration with basemap and cartopy. Generate arbitrary
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grids of map projections in one go. Switch between the cartopy and
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basemap backends painlessly. Using the axes methods directly for basemap
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plotting, instead of the `Basemap` object.
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* Ability to add geographical features with the `format` command.
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Formatting geographic gridlines and labels.
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grids of arbitrary map projections in one go. Switch between the cartopy and
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basemap backends painlessly. Use the axes methods directly for basemap
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plotting, instead of the ``Basemap`` object.
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* Add geographic features with the ``format`` command.
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Customize geographic gridlines and gridline labels.
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Shout out to `bradyrx <https://github.com/bradyrx>`__ for being the
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guinea pig and helping me fix a lot of the initial bugs. Check out his `decadal climate prediction package <https://github.com/bradyrx/climpred>`_.
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While parts of ProPlot were inspired by seaborn (in particular much
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of ``colors.py`` is drawn from seaborn’s ``palettes.py``), the goal for
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this project was quite different: It is intended to simplify the task
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of making publication-quality figures, and no more.
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this project was likely very different: It is intended to help you make
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publication-quality figures, and no more.
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Seaborn largely attempts to merge the tasks of data analysis and
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visualization. ProPlot contains no analysis tools – it is expected
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that you analyze your data on your own time. Anyway, both `pandas`
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and `xarray` already have great built-in tools for visualizing
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that you analyze your data on your own time. Anyway, both ``pandas``
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and ``xarray`` already have great built-in tools for visualizing
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tabulated and geophysical data --
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and if ProPlot is imported, these tools will even work with its new
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colormaps. I was also able
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colormaps. This narrow focus also allowed me
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to integrate my features very closely with the matplotlib API (usually
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as enhancements of existing `Axes` and
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`Figure` methods),
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while the `seaborn` features are only accessible from commands on the module
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as enhancements of existing ``Axes`` and
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``Figure`` methods),
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while ``seaborn`` features are only accessible from commands on the module
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itself.
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By focusing on this single task, I've added a number of
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powerful features well beyond the scope of `seaborn`.
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In summary, this is a package for academics and others that need compact, fine-tuned figures for use in professional settings. As such, it provides a number of powerful, easy-to-use features well beyond the scope of `seaborn`.
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