__init__.py

def _line_division(chart, ax):
    """Convert encodings, manipulate data if needed, plot on ax.
    Parameters
    ----------
    chart : altair.Chart
        The Altair chart object
    ax
        The Matplotlib axes object
    Notes
    -----
    Fill isn't necessary until mpl-altair can handle multiple plot types in one plot.
    Size is unsupported by both Matplotlib and Altair.
    When both Color and Stroke are provided, color is ignored and stroke is used.
    Shape is unsupported in line graphs unless another plot type is plotted at the same time.
    Opacity still needs to be implemented.
    """
    if chart.to_dict()['encoding'].get('opacity'):
        raise NotImplementedError("Still need to implement.")
        # dtype = _locate_channel_dtype(chart, 'opacity')
        # normalize opacity values to (0,1)
        # mapping['kwargs'] = {'alpha': normalized_vals}  # ish (not really going to work)

    if chart.to_dict()['encoding'].get('stroke'):
        grouping = chart.to_dict()['encoding']['stroke']['field']
    elif chart.to_dict()['encoding'].get('color'):  # If both color and stroke are encoded, color is ignored.
        grouping = chart.to_dict()['encoding']['color']['field']
    else:
        mapping = _convert(chart)
        ax.plot(*mapping['args'])
        return

    for lab, subset in chart.data.groupby(grouping):
        tmp_chart = chart
        tmp_chart.data = subset
        mapping = _convert(tmp_chart)
        mapping['kwargs'] = {'label': lab}  # for legend purposes later on

_convert.py

_line_mapping = {
    'x': lambda d: ('x', d),
    'y': lambda d: ('y', d),
    'args': lambda x, y: [x, y]
}

def _convert(chart):
    """Convert an altair encoding to a Matplotlib figure
    Parameters
    ----------
    chart
        The Altair chart.
    Returns
    -------
    mapping : dict
        Mapping from parts of the encoding to the Matplotlib artists.  This is
        for later customization.
    """
    mapping = {}

    if not chart.to_dict().get('encoding'):
        raise ValueError("Encoding not provided with the chart specification")

    for enc_channel, enc_spec in chart.to_dict()['encoding'].items():
        if not _allowed_ranged_marks(enc_channel, chart.to_dict()['mark']):
            raise ValueError("Ranged encoding channels like x2, y2 not allowed for Mark: {}".format(chart['mark']))

    for channel in chart.to_dict()['encoding']:
        data = _locate_channel_data(chart, channel)
        dtype = _locate_channel_dtype(chart, channel)
        # FROM AXIS-NUMERIC============================================================================================
        if dtype == 'temporal':
            data = _convert_to_mpl_date(data)
        # END STUFF FROM AXIS-NUMERIC==================================================================================
        """
        if dtype == 'temporal':
            try:
                data = mdates.date2num(data)  # Convert dates to Matplotlib dates
            except AttributeError:
                raise
        """

        if chart.mark in ['point', 'circle', 'square']:
            mapping[_mappings[channel](dtype, data)[0]] = _mappings[channel](dtype, data)[1]
        elif chart.mark == 'line' and channel in ['x', 'y']:
            mapping[_line_mapping[channel](data)[0]] = _line_mapping[channel](data)[1]

    if chart.mark == 'line':
        mapping['args'] = _line_mapping['args'](mapping['x'], mapping['y'])  # plot() doesn't take kwargs for x and y
    
    return mapping