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Description:

datagif 0.1.1

A Python package for easily making clean animated gifs of data plots, datagif is built on top
of seaborn to manage the plot generation, and
imageio to manage creating the animated gif.

Example GIF
Code for this example can be found in the examples directory.

How to use datagif
The method you need is named after the package, so use the following import statement
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
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:

plt_funcs (Functions that are normally called like plt.title())
seaborn_funcs (Functions that are normally called like sns.set_theme())
seaborn_args (Arguments to add to the plot functions)
imageio_args (Arguments for the imageio 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 nth entry of
these other arguments will be used for the nth plot.

Helpful Tips
It is strongly recommended to use the tight_layout method in the plt_funcs argument.
This will help prevent small differences between the plots produced, leading to a much
cleaner GIF.