PairGrid errors with `hue` assigned in `map`
In seaborn version 0.9.0 I was able to use the following Code to plot scatterplots across a PairGrid with categorical hue. The reason I am not using the "hue" keyword in creating the PairGrid is, that I want one regression line (with regplot) and not one regression per hue-category.
```python
import seaborn as sns
iris = sns.load_dataset("iris")
g = sns.PairGrid(iris, y_vars=["sepal_length","sepal_width"], x_vars=["petal_length","petal_width"])
g.map(sns.scatterplot, hue=iris["species"])
g.map(sns.regplot, scatter=False)
```

However, since I updated to searbon 0.11.1 the following Error message occurs:
```
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
~/.Software/miniforge3/envs/py3.9/lib/python3.8/site-packages/seaborn/_core.py in _lookup_single(self, key)
    143             # Use a value that's in the original data vector
--> 144             value = self.lookup_table[key]
    145         except KeyError:

KeyError: 'setosa'

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
~/.Software/miniforge3/envs/py3.9/lib/python3.8/site-packages/seaborn/_core.py in _lookup_single(self, key)
    148             try:
--> 149                 normed = self.norm(key)
    150             except TypeError as err:

TypeError: 'NoneType' object is not callable

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
<ipython-input-3-46dd21e9c95a> in <module>
      2 iris = sns.load_dataset("iris")
      3 g = sns.PairGrid(iris, y_vars=["sepal_length","sepal_width"], x_vars=["petal_length","species"])
----> 4 g.map(sns.scatterplot, hue=iris["species"])
      5 

~/.Software/miniforge3/envs/py3.9/lib/python3.8/site-packages/seaborn/axisgrid.py in map(self, func, **kwargs)
   1263         row_indices, col_indices = np.indices(self.axes.shape)
   1264         indices = zip(row_indices.flat, col_indices.flat)
-> 1265         self._map_bivariate(func, indices, **kwargs)
   1266 
   1267         return self

~/.Software/miniforge3/envs/py3.9/lib/python3.8/site-packages/seaborn/axisgrid.py in _map_bivariate(self, func, indices, **kwargs)
   1463             if ax is None:  # i.e. we are in corner mode
   1464                 continue
-> 1465             self._plot_bivariate(x_var, y_var, ax, func, **kws)
   1466         self._add_axis_labels()
   1467 

~/.Software/miniforge3/envs/py3.9/lib/python3.8/site-packages/seaborn/axisgrid.py in _plot_bivariate(self, x_var, y_var, ax, func, **kwargs)
   1503         kwargs.setdefault("hue_order", self._hue_order)
   1504         kwargs.setdefault("palette", self._orig_palette)
-> 1505         func(x=x, y=y, **kwargs)
   1506 
   1507         self._update_legend_data(ax)

~/.Software/miniforge3/envs/py3.9/lib/python3.8/site-packages/seaborn/_decorators.py in inner_f(*args, **kwargs)
     44             )
     45         kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---> 46         return f(**kwargs)
     47     return inner_f
     48 

~/.Software/miniforge3/envs/py3.9/lib/python3.8/site-packages/seaborn/relational.py in scatterplot(x, y, hue, style, size, data, palette, hue_order, hue_norm, sizes, size_order, size_norm, markers, style_order, x_bins, y_bins, units, estimator, ci, n_boot, alpha, x_jitter, y_jitter, legend, ax, **kwargs)
    818     p._attach(ax)
    819 
--> 820     p.plot(ax, kwargs)
    821 
    822     return ax

~/.Software/miniforge3/envs/py3.9/lib/python3.8/site-packages/seaborn/relational.py in plot(self, ax, kws)
    626         # Apply the mapping from semantic variables to artist attributes
    627         if "hue" in self.variables:
--> 628             c = self._hue_map(data["hue"])
    629 
    630         if "size" in self.variables:

~/.Software/miniforge3/envs/py3.9/lib/python3.8/site-packages/seaborn/_core.py in __call__(self, key, *args, **kwargs)
     61         """Get the attribute(s) values for the data key."""
     62         if isinstance(key, (list, np.ndarray, pd.Series)):
---> 63             return [self._lookup_single(k, *args, **kwargs) for k in key]
     64         else:
     65             return self._lookup_single(key, *args, **kwargs)

~/.Software/miniforge3/envs/py3.9/lib/python3.8/site-packages/seaborn/_core.py in <listcomp>(.0)
     61         """Get the attribute(s) values for the data key."""
     62         if isinstance(key, (list, np.ndarray, pd.Series)):
---> 63             return [self._lookup_single(k, *args, **kwargs) for k in key]
     64         else:
     65             return self._lookup_single(key, *args, **kwargs)

~/.Software/miniforge3/envs/py3.9/lib/python3.8/site-packages/seaborn/_core.py in _lookup_single(self, key)
    149                 normed = self.norm(key)
    150             except TypeError as err:
--> 151                 if np.isnan(key):
    152                     value = (0, 0, 0, 0)
    153                 else:

TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
```

My further observations are:
- the error does not occur when using the "hue" keyword when creating PairGrid
- the error does not occur for numerical values for hue
- changing the dtype to "categorical" does not help

Edit:
I tried all versions between 0.9.0 and the current release (0.11.1) and the error only occurs in the current release. If I use 0.11.0, the plot seems to work.