Issue 1:
sns.__version__, matplotlib.__version__
('0.11.1', '3.4.2')

This works

import seaborn as sns

titanic = sns.load_dataset("titanic")
sns.displot(
data=titanic,
x="age",
y='fare',
col="survived",
common_bins=True,
)

This does not

import seaborn as sns

titanic = sns.load_dataset("titanic")
sns.displot(
data=titanic,
x="age",
y='fare',
col="survived",
common_bins=False,
)

/home/samuel/miniconda3/envs/py38/lib/python3.8/site-packages/numpy/core/fromnumeric.py:87: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray
return ufunc.reduce(obj, axis, dtype, out, **passkwargs)

---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/tmp/ipykernel_10645/1850804617.py in <module>
2
3 titanic = sns.load_dataset("titanic")
----> 4 sns.displot(
5 data=titanic,
6 x="age",

~/miniconda3/envs/py38/lib/python3.8/site-packages/seaborn/distributions.py in displot(data, x, y, hue, row, col, weights, kind, rug, rug_kws, log_scale, legend, palette, hue_order, hue_norm, color, col_wrap, row_order, col_order, height, aspect, facet_kws, **kwargs)
2230
2231 _assign_default_kwargs(hist_kws, p.plot_bivariate_histogram, histplot)
-> 2232 p.plot_bivariate_histogram(**hist_kws)
2233
2234 elif kind == "kde":

~/miniconda3/envs/py38/lib/python3.8/site-packages/seaborn/distributions.py in plot_bivariate_histogram(self, common_bins, common_norm, thresh, pthresh, pmax, color, legend, cbar, cbar_ax, cbar_kws, estimate_kws, **plot_kws)
763 vmax = self._quantile_to_level(full_heights, pmax)
764 else:
--> 765 vmax = plot_kws.pop("vmax", np.max(full_heights))
766 else:
767 vmax = None

<__array_function__ internals> in amax(*args, **kwargs)

~/miniconda3/envs/py38/lib/python3.8/site-packages/numpy/core/fromnumeric.py in amax(a, axis, out, keepdims, initial, where)
2703 5
2704 """
-> 2705 return _wrapreduction(a, np.maximum, 'max', axis, None, out,
2706 keepdims=keepdims, initial=initial, where=where)
2707

~/miniconda3/envs/py38/lib/python3.8/site-packages/numpy/core/fromnumeric.py in _wrapreduction(obj, ufunc, method, axis, dtype, out, **kwargs)
85 return reduction(axis=axis, out=out, **passkwargs)
86
---> 87 return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
88
89

ValueError: could not broadcast input array from shape (16,53) into shape (16)

I thought asking for different bins size (in a more complicated example) would work, but apparently adding a y variable make stuff blows up. Asking only for a x variable or more rows/columns seems fine though, so I'm wondering if the bivariate case is supposed to 1. work or 2. is allowing something which is not supposed to be working and should instead report a warning/error for that case.

Issue 2:
I'm noticing a new behavior in clustermap. The top and bottom of the figure get clipped. The command used to produce complete squares a few months ago. Here's an example:

For your records, I ran the following code:

%matplotlib inline
import numpy as np
import seaborn as sns
np.random.seed(98)
x = np.random.rand(10,10)
sns.clustermap(x)

It just looks like a bug, so I thought I'd report it.

Thanks.