df.hvplot.heatmap: Problem specifying value dimensions

[Sieboldianus]

This was originally asked on here but I'll report it here as a feature request by the request of philippjfr

I have problems specifying value dimensions for an existing simple dataframe when plotting a heatmap. I can do something pretty similar with:

df.style.background_gradient(cmap='summer')

The dataframe is pretty simple:

> df.index
Index(['ackerland', 'friedhof', 'gartenland', 'gehoelz', 'golfplatz',
       'gruenland', 'heide', 'kleingarten', 'laubholz', 'mischholz', 'moor',
       'nadelholz'],
      dtype='object')
> df.columns
Index(['hiking', 'biking', 'walking', 'sport', 'friends', 'family', 'picnic'], dtype='object')

According to the docs on heatmap it should be directly possible to plot this using df.hvplot.heatmap. But when I do:

>import hvplot.pandas
>df.hvplot.heatmap(colorbar=True)
ValueError: Dimensions must be defined as a tuple, string, dictionary or Dimension instance, found a NoneType type.

This does also not work:

>df.hvplot.heatmap(x=df.index, y=df.columns, colorbar=True)
ValueError: The truth value of a Index is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

I got it to work with Holoviews API:
hv.HeatMap({'x': df.columns, 'y': df.index, 'z': df}, ['x', 'y'], 'z'),
but the same syntax does not work in hvplot:

>df.hvplot.heatmap({'x': df.columns, 'y':df.index, 'z': df}, ['x', 'y'], 'z')
ValueError: Dimensions must be defined as a tuple, string, dictionary or Dimension instance, found a list type.