cgeniepy.table
==============

.. py:module:: cgeniepy.table


Classes
-------

.. autoapisummary::

   cgeniepy.table.ScatterData


Module Contents
---------------

.. py:class:: ScatterData(data: Union[pandas.DataFrame, int, str], **kwargs)

   .. py:attribute:: modify_in_place
      :value: True


      ScatterData is a class to store non-gridded data with columns of coordinates.



   .. py:attribute:: data


   .. py:method:: __repr__()


   .. py:method:: __getitem__(item)


   .. py:method:: set_index(index)

      Tell the object which columns are the coordinates.        
              



   .. py:method:: reset_index()


   .. py:method:: detect_basin()

      use point-in-polygon strategy to detect modern ocean basin according to lon/lat column

      Example
      ----------
      >>> data = ScatterData(data)
      >>> data.set_index(['lon', 'lat'])
      >>> data.detect_basin()



   .. py:method:: to_xarray()

      convert to xarray dataset



   .. py:method:: to_GriddedData(var)

      convert to gridded data



   .. py:method:: interpolate(var)


   .. py:method:: to_geniebin(var, agg_method='mean')

      Regrid a dataframe within certain format to cGENIE grids.
      This method does not consider the land-sea mask. So if convert from a higher resolution data to GENIE grids,
      the land-sea mask could be different (Not a problem in comparison though).

      :param var: The variable to regrid.
      :param agg_method: The aggregation method to use when regridding.
      :return: An indexed data frame



   .. py:method:: drop_na(*args, **kwargs)

      drop rows with NA values



   .. py:method:: to_ScatterDataVis()

      convert to ScatterDataVis



   .. py:method:: plot(var, kind='scatter', *args, **kwargs)

      plot the data



   .. py:method:: compare(var1, var2, model_name=None, obs_name=None)

      compare two ScatterData objects



   .. py:method:: rolling(window, *args, **kwargs)

      apply rolling to the data