Function violin_colorscale

plotly/figure_factory/_violin.py:261–359

Refer to FigureFactory.create_violin() for docstring. Returns fig for violin plot with colorscale.

(
    data,
    data_header,
    group_header,
    colors,
    use_colorscale,
    group_stats,
    rugplot,
    sort,
    height,
    width,
    title,
)

def violin_colorscale(
    data,
    data_header,
    group_header,
    colors,
    use_colorscale,
    group_stats,
    rugplot,
    sort,
    height,
    width,
    title,
):
    """
    Refer to FigureFactory.create_violin() for docstring.

    Returns fig for violin plot with colorscale.

    """

    # collect all group names
    group_name = []
    for name in data[group_header]:
        if name not in group_name:
            group_name.append(name)
    if sort:
        group_name.sort()

    # make sure all group names are keys in group_stats
    for group in group_name:
        if group not in group_stats:
            raise exceptions.PlotlyError(
                "All values/groups in the index "
                "column must be represented "
                "as a key in group_stats."
            )

    gb = data.groupby([group_header])
    L = len(group_name)

    fig = make_subplots(
        rows=1, cols=L, shared_yaxes=True, horizontal_spacing=0.025, print_grid=False
    )

    # prepare low and high color for colorscale
    lowcolor = clrs.color_parser(colors[0], clrs.unlabel_rgb)
    highcolor = clrs.color_parser(colors[1], clrs.unlabel_rgb)

    # find min and max values in group_stats
    group_stats_values = []
    for key in group_stats:
        group_stats_values.append(group_stats[key])

    max_value = max(group_stats_values)
    min_value = min(group_stats_values)

    for k, gr in enumerate(group_name):
        vals = np.asarray(gb.get_group(gr)[data_header], float)