AttributeError when using name of column as color argument for bar plot with Matplotlib backend

[MarcSkovMadsen]

I would expect to be able to use the name of a column as color argument for a bar plot with Matplotlib backend just as I can for the Bokeh backend. But I cannot because an AttributeError is raised.

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
File C:\repos\private\hvplot\.venv\lib\site-packages\IPython\core\formatters.py:972, in MimeBundleFormatter.__call__(self, obj, include, exclude)
    969     method = get_real_method(obj, self.print_method)
    971     if method is not None:
--> 972         return method(include=include, exclude=exclude)
    973     return None
    974 else:

File c:\repos\private\tmp\holoviews\holoviews\core\dimension.py:1293, in Dimensioned._repr_mimebundle_(self, include, exclude)
   1286 def _repr_mimebundle_(self, include=None, exclude=None):
   1287     """
   1288     Resolves the class hierarchy for the class rendering the
   1289     object using any display hooks registered on Store.display
   1290     hooks.  The output of all registered display_hooks is then
   1291     combined and returned.
   1292     """
-> 1293     return Store.render(self)

File c:\repos\private\tmp\holoviews\holoviews\core\options.py:1426, in Store.render(cls, obj)
   1424 data, metadata = {}, {}
   1425 for hook in hooks:
-> 1426     ret = hook(obj)
   1427     if ret is None:
   1428         continue

File c:\repos\private\tmp\holoviews\holoviews\ipython\display_hooks.py:277, in pprint_display(obj)
    275 if not ip.display_formatter.formatters['text/plain'].pprint:
    276     return None
--> 277 return display(obj, raw_output=True)

File c:\repos\private\tmp\holoviews\holoviews\ipython\display_hooks.py:247, in display(obj, raw_output, **kwargs)
    245 elif isinstance(obj, (CompositeOverlay, ViewableElement)):
    246     with option_state(obj):
--> 247         output = element_display(obj)
    248 elif isinstance(obj, (Layout, NdLayout, AdjointLayout)):
    249     with option_state(obj):

File c:\repos\private\tmp\holoviews\holoviews\ipython\display_hooks.py:141, in display_hook.<locals>.wrapped(element)
    139 try:
    140     max_frames = OutputSettings.options['max_frames']
--> 141     mimebundle = fn(element, max_frames=max_frames)
    142     if mimebundle is None:
    143         return {}, {}

File c:\repos\private\tmp\holoviews\holoviews\ipython\display_hooks.py:187, in element_display(element, max_frames)
    184 if type(element) not in Store.registry[backend]:
    185     return None
--> 187 return render(element)

File c:\repos\private\tmp\holoviews\holoviews\ipython\display_hooks.py:68, in render(obj, **kwargs)
     65 if renderer.fig == 'pdf':
     66     renderer = renderer.instance(fig='png')
---> 68 return renderer.components(obj, **kwargs)

File c:\repos\private\tmp\holoviews\holoviews\plotting\renderer.py:380, in Renderer.components(self, obj, fmt, comm, **kwargs)
    378     plot = obj
    379 else:
--> 380     plot, fmt = self._validate(obj, fmt)
    382 if not isinstance(plot, Viewable):
    383     html = self._figure_data(plot, fmt, as_script=True, **kwargs)

File c:\repos\private\tmp\holoviews\holoviews\plotting\renderer.py:309, in Renderer._validate(self, obj, fmt, **kwargs)
    306     plot = HoloViewsPane(obj, center=self.center, backend=self.backend,
    307                          renderer=self)
    308 else:
--> 309     plot = self.get_plot(obj, renderer=self, **kwargs)
    311 all_formats = set(fig_formats + holomap_formats)
    312 if fmt not in all_formats:

File c:\repos\private\tmp\holoviews\holoviews\plotting\renderer.py:240, in Renderer.get_plot(self_or_cls, obj, doc, renderer, comm, **kwargs)
    237     defaults = [kd.default for kd in plot.dimensions]
    238     init_key = tuple(v if d is None else d for v, d in
    239                      zip(plot.keys[0], defaults))
--> 240     plot.update(init_key)
    241 else:
    242     plot = obj

File c:\repos\private\tmp\holoviews\holoviews\plotting\mpl\plot.py:249, in MPLPlot.update(self, key)
    247 def update(self, key):
    248     if len(self) == 1 and ((key == 0) or (key == self.keys[0])) and not self.drawn:
--> 249         return self.initialize_plot()
    250     return self.__getitem__(key)

File c:\repos\private\tmp\holoviews\holoviews\plotting\mpl\plot.py:45, in mpl_rc_context.<locals>.wrapper(self, *args, **kwargs)
     43 def wrapper(self, *args, **kwargs):
     44     with _rc_context(self.fig_rcparams):
---> 45         return f(self, *args, **kwargs)

File c:\repos\private\tmp\holoviews\holoviews\plotting\mpl\chart.py:893, in BarPlot.initialize_plot(self, ranges)
    890 ranges = self.compute_ranges(self.hmap, key, ranges)
    891 ranges = match_spec(element, ranges)
--> 893 self.handles['artist'], xticks, xdims = self._create_bars(axis, element, ranges, style)
    894 kwargs = {'yticks': xticks} if self.invert_axes else {'xticks': xticks}
    895 return self._finalize_axis(key, ranges=ranges, element=element,
    896                            dimensions=[xdims, vdim], **kwargs)

File c:\repos\private\tmp\holoviews\holoviews\plotting\mpl\chart.py:992, in BarPlot._create_bars(self, axis, element, ranges, style)
    989                 labels.append(label)
    991 # Draw bars
--> 992 bars = [getattr(axis, plot_fn)(**bar_spec) for bar_spec in bar_data.values()]
    994 # Generate legend and axis labels
    995 ax_dims = [gdim]

File c:\repos\private\tmp\holoviews\holoviews\plotting\mpl\chart.py:992, in <listcomp>(.0)
    989                 labels.append(label)
    991 # Draw bars
--> 992 bars = [getattr(axis, plot_fn)(**bar_spec) for bar_spec in bar_data.values()]
    994 # Generate legend and axis labels
    995 ax_dims = [gdim]

File C:\repos\private\hvplot\.venv\lib\site-packages\matplotlib\__init__.py:1423, in _preprocess_data.<locals>.inner(ax, data, *args, **kwargs)
   1420 @functools.wraps(func)
   1421 def inner(ax, *args, data=None, **kwargs):
   1422     if data is None:
-> 1423         return func(ax, *map(sanitize_sequence, args), **kwargs)
   1425     bound = new_sig.bind(ax, *args, **kwargs)
   1426     auto_label = (bound.arguments.get(label_namer)
   1427                   or bound.kwargs.get(label_namer))

File C:\repos\private\hvplot\.venv\lib\site-packages\matplotlib\axes\_axes.py:2462, in Axes.bar(self, x, height, width, bottom, align, **kwargs)
   2453 for l, b, w, h, c, e, lw, htch, lbl in args:
   2454     r = mpatches.Rectangle(
   2455         xy=(l, b), width=w, height=h,
   2456         facecolor=c,
   (...)
   2460         hatch=htch,
   2461         )
-> 2462     r._internal_update(kwargs)
   2463     r.get_path()._interpolation_steps = 100
   2464     if orientation == 'vertical':

File C:\repos\private\hvplot\.venv\lib\site-packages\matplotlib\artist.py:1186, in Artist._internal_update(self, kwargs)
   1179 def _internal_update(self, kwargs):
   1180     """
   1181     Update artist properties without prenormalizing them, but generating
   1182     errors as if calling `set`.
   1183 
   1184     The lack of prenormalization is to maintain backcompatibility.
   1185     """
-> 1186     return self._update_props(
   1187         kwargs, "{cls.__name__}.set() got an unexpected keyword argument "
   1188         "{prop_name!r}")

File C:\repos\private\hvplot\.venv\lib\site-packages\matplotlib\artist.py:1160, in Artist._update_props(self, props, errfmt)
   1158             func = getattr(self, f"set_{k}", None)
   1159             if not callable(func):
-> 1160                 raise AttributeError(
   1161                     errfmt.format(cls=type(self), prop_name=k))
   1162             ret.append(func(v))
   1163 if ret:

AttributeError: Rectangle.set() got an unexpected keyword argument 'vmin'

import pandas as pd
import hvplot.pandas  # noqa

from bokeh.sampledata.autompg import autompg_clean as autompg

autompg.head()

autompg_long_form = autompg.groupby("yr").mean(numeric_only=True).reset_index()
autompg_long_form.head()

autompg_multi_index = autompg.query("yr<=80").groupby(['yr', 'origin']).mean(numeric_only=True)
autompg_wide = autompg_multi_index.reset_index().pivot(index='yr', columns='origin', values='mpg')
autompg_wide.head()

hvplot.extension("bokeh")
autompg_long_form.hvplot.bar(y='mpg', color="weight", colorbar=True, clabel="Weight", cmap="bmy", width=1000)

hvplot.extension("matplotlib")
autompg_long_form.hvplot.bar(y='mpg', color="weight", colorbar=True, clabel="Weight", cmap="bmy", width=1000)