Metadata-Version: 2.1
Name: datagif
Version: 0.1.1
Summary: Make animated gifs out of multiple data plots.
Home-page: https://github.com/Matyasz/datagif
Author: Taylor Matyasz
Author-email: tjmatyasz@gmail.com
License: GNU GPLv3
Description: *******
        datagif
        *******
        
        .. role:: pyt(code)
           :language: python
        
        .. image:: https://badge.fury.io/py/datagif.svg
            :target: https://badge.fury.io/py/datagif
        
        A Python package for easily making clean animated gifs of data plots, `datagif` is built on top
        of `seaborn <https://seaborn.pydata.org/>`_ to manage the plot generation, and
        `imageio <https://imageio.github.io/>`_ to manage creating the animated gif.
        
        Example GIF
        ***********
        Code for this example can be found in the `examples directory <https://github.com/Matyasz/datagif/blob/master/examples/scatterplot.py>`_.
        
        .. image:: https://raw.githubusercontent.com/Matyasz/datagif/master/readme_assets/gaussian_scatter.gif
            :align: center
            :width: 500px
            :height: 500px
        
        How to use `datagif`
        ####################
        The method you need is named after the package, so use the following import statement
        
        
        .. code-block:: python
        
           from datagif import datagif
        
        
        Your data will need to be in the form of a `pandas` DataFrame, with at least three columns.
        Select one to be the time dimension, and then the simplest example looks like the following
        
        .. code-block:: python
        
            datagif(
                plots='scatterplot',
                save_dir='/path/to/plot/dir',
                name='GIF',
                data=df,
                x='x',
                y='y',
                t='time'
            )
        
        
        Customizing your GIF
        ####################
        There are four important arguments for customizing your GIF and the plots that make it up:
        
        - :pyt:`plt_funcs` (Functions that are normally called like :pyt:`plt.title()`)
        - :pyt:`seaborn_funcs` (Functions that are normally called like :pyt:`sns.set_theme()`)
        - :pyt:`seaborn_args` (Arguments to add to the plot functions)
        - :pyt:`imageio_args` (Arguments for the imageio :pyt:`get_writer()` method)
        
        For the ``_funcs`` arguments, these should be in the form of a dict where the keys are strings of the
        names of the functions you want to call, and the values should be the arguments you want to pass to
        the functions. These values can themselves be 
        
        - a single value, like a string
        - a list to be unpacked and passed to the function
        - a dictionary to be unpacked and passed to the function as keyword arguments
        
        For the ``_args`` arguments, these should be in the form of a dict that will be passed to the
        plotting and imageio functions as keyword arguments.
        
        Using multiple plots in one GIF
        ###############################
        As in the example above, you can layer multiple plots in one GIF! To do this, simply make the
        ``plots`` argument a list of valid strings. Then also make the ``x``, ``y``, ``seaborn_args`` arguments
        into lists of valid values the same length as the `plots` list, and the n\ :sup:`th`\  entry of
        these other arguments will be used for the n\ :sup:`th`\  plot.
        
        Helpful Tips
        ############
        It is strongly recommended to use the :pyt:`tight_layout` method in the :pyt:`plt_funcs` argument.
        This will help prevent small differences between the plots produced, leading to a much
        cleaner GIF.
Keywords: python,data,science,data science,animated,gif,matplotlib,seaborn,imageio
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Framework :: Flake8
Classifier: Framework :: Matplotlib
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Environment :: MacOS X
Classifier: Operating System :: POSIX
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Artistic Software
Classifier: Topic :: Multimedia
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development :: Libraries
Provides-Extra: docs
Provides-Extra: test
Provides-Extra: interactive
Provides-Extra: dev
