Plotting
========

Once all the data is parsed into the dataframe, seaborn_ provides a nice interface to allow simple plotting of different properties.
Below is an example chosen almost at random, so I'm not trying to demonstrate a new discovery.

After populating the default mass table we slice on all Tin (Z=50) isotopes from the 2020 table and keep the 'A', 'N', 'AMEMassExcess' and 'Experimental' columns.
We then create a new column flagging if the N value is even.
We know Z is even as we selected only those rows with Z=50.
With this newly filtered dataframe, we can plot how the AME Mass Excess varies for Sn across its isotopic chain using colour to highlight the even-even and even-odd isotopes and symbol to differentiate experimentally measured from theoretical values.
As can be seen from the call to relplot_, this is simply achieved by passing the column names we wish to use as the differentiator(s).

.. _seaborn:  https://seaborn.pydata.org/
.. _relplot: https://seaborn.pydata.org/generated/seaborn.relplot.html#seaborn.relplot

.. code-block:: python

   import seaborn as sns
   import matplotlib.pyplot as plt

   from nuclearmasses.mass_table import MassTable

   table = MassTable().data

   sliced_table = table[(table['Z'] == 50) & (table['TableYear'] == 2020)][['A', 'N', 'AMEMassExcess', 'Experimental']]
   sliced_table['is_even_N'] = (sliced_table['N'] % 2 == 0).astype("Int64") 

   sns.relplot(data=sliced_table, x='A', y='AMEMassExcess', hue='is_even_N', style='Experimental')
   plt.show()
   

.. image:: /_static/images/usage/ame_me_tin_even_odd_colouring.png
   :alt: AME Mass Excess plot for Sn