<p dir="auto">With PANDAS 1.5.3 (and Seaborn 0.11.2, Matplotlib 3.7.1), the following code works fine:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="import seaborn as sns
sns.jointplot(x=[1,3,2], y=[1,2,3])"><pre class="notranslate"><code class="notranslate">import seaborn as sns
sns.jointplot(x=[1,3,2], y=[1,2,3])
</code></pre></div>
<p dir="auto">But with PANDAS 2.0.0 the identical code raises an exception:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="OptionError: No such keys(s): 'mode.use_inf_as_null'"><pre class="notranslate"><code class="notranslate">OptionError: No such keys(s): 'mode.use_inf_as_null'
</code></pre></div>
<p dir="auto">Here's the full output:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="File ~/.../venv/lib/python3.10/site-packages/seaborn/_decorators.py:46, in _deprecate_positional_args.&lt;locals&gt;.inner_f(*args, **kwargs)
     36     warnings.warn(
     37         &quot;Pass the following variable{} as {}keyword arg{}: {}. &quot;
     38         &quot;From version 0.12, the only valid positional argument &quot;
   (...)
     43         FutureWarning
     44     )
     45 kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---&gt; 46 return f(**kwargs)

File ~/.../venv/lib/python3.10/site-packages/seaborn/axisgrid.py:2254, in jointplot(x, y, data, kind, color, height, ratio, space, dropna, xlim, ylim, marginal_ticks, joint_kws, marginal_kws, hue, palette, hue_order, hue_norm, **kwargs)
   2251         marginal_kws.setdefault(&quot;fill&quot;, True)
   2253     marginal_kws.setdefault(&quot;color&quot;, color)
-&gt; 2254     grid.plot_marginals(marg_func, **marginal_kws)
   2256 elif kind.startswith(&quot;hist&quot;):
   2257 
   2258     # TODO process pair parameters for bins, etc. and pass
   2259     # to both jount and marginal plots
   2261     joint_kws.setdefault(&quot;color&quot;, color)

File ~/.../venv/lib/python3.10/site-packages/seaborn/axisgrid.py:1857, in JointGrid.plot_marginals(self, func, **kwargs)
   1854     orient_kw_y = {&quot;vertical&quot;: True}
   1856 if seaborn_func:
-&gt; 1857     func(x=self.x, ax=self.ax_marg_x, **kwargs)
   1858 else:
   1859     plt.sca(self.ax_marg_x)

File ~/.../venv/lib/python3.10/site-packages/seaborn/distributions.py:1462, in histplot(data, x, y, hue, weights, stat, bins, binwidth, binrange, discrete, cumulative, common_bins, common_norm, multiple, element, fill, shrink, kde, kde_kws, line_kws, thresh, pthresh, pmax, cbar, cbar_ax, cbar_kws, palette, hue_order, hue_norm, color, log_scale, legend, ax, **kwargs)
   1451 estimate_kws = dict(
   1452     stat=stat,
   1453     bins=bins,
   (...)
   1457     cumulative=cumulative,
   1458 )
   1460 if p.univariate:
-&gt; 1462     p.plot_univariate_histogram(
   1463         multiple=multiple,
   1464         element=element,
   1465         fill=fill,
   1466         shrink=shrink,
   1467         common_norm=common_norm,
   1468         common_bins=common_bins,
   1469         kde=kde,
   1470         kde_kws=kde_kws,
   1471         color=color,
   1472         legend=legend,
   1473         estimate_kws=estimate_kws,
   1474         line_kws=line_kws,
   1475         **kwargs,
   1476     )
   1478 else:
   1480     p.plot_bivariate_histogram(
   1481         common_bins=common_bins,
   1482         common_norm=common_norm,
   (...)
   1492         **kwargs,
   1493     )

File ~/.../venv/lib/python3.10/site-packages/seaborn/distributions.py:428, in _DistributionPlotter.plot_univariate_histogram(self, multiple, element, fill, common_norm, common_bins, shrink, kde, kde_kws, color, legend, line_kws, estimate_kws, **plot_kws)
    418     densities = self._compute_univariate_density(
    419         self.data_variable,
    420         common_norm,
   (...)
    424         warn_singular=False,
    425     )
    427 # First pass through the data to compute the histograms
--&gt; 428 for sub_vars, sub_data in self.iter_data(&quot;hue&quot;, from_comp_data=True):
    429 
    430     # Prepare the relevant data
    431     key = tuple(sub_vars.items())
    432     sub_data = sub_data.dropna()

File ~/.../venv/lib/python3.10/site-packages/seaborn/_core.py:983, in VectorPlotter.iter_data(self, grouping_vars, reverse, from_comp_data)
    978 grouping_vars = [
    979     var for var in grouping_vars if var in self.variables
    980 ]
    982 if from_comp_data:
--&gt; 983     data = self.comp_data
    984 else:
    985     data = self.plot_data

File ~/.../venv/lib/python3.10/site-packages/seaborn/_core.py:1054, in VectorPlotter.comp_data(self)
   1050 axis = getattr(ax, f&quot;{var}axis&quot;)
   1052 # Use the converter assigned to the axis to get a float representation
   1053 # of the data, passing np.nan or pd.NA through (pd.NA becomes np.nan)
-&gt; 1054 with pd.option_context('mode.use_inf_as_null', True):
   1055     orig = self.plot_data[var].dropna()
   1056 comp_col = pd.Series(index=orig.index, dtype=float, name=var)

File ~/.../venv/lib/python3.10/site-packages/pandas/_config/config.py:441, in option_context.__enter__(self)
    440 def __enter__(self) -&gt; None:
--&gt; 441     self.undo = [(pat, _get_option(pat, silent=True)) for pat, val in self.ops]
    443     for pat, val in self.ops:
    444         _set_option(pat, val, silent=True)

File ~/.../venv/lib/python3.10/site-packages/pandas/_config/config.py:441, in &lt;listcomp&gt;(.0)
    440 def __enter__(self) -&gt; None:
--&gt; 441     self.undo = [(pat, _get_option(pat, silent=True)) for pat, val in self.ops]
    443     for pat, val in self.ops:
    444         _set_option(pat, val, silent=True)

File ~/.../venv/lib/python3.10/site-packages/pandas/_config/config.py:135, in _get_option(pat, silent)
    134 def _get_option(pat: str, silent: bool = False) -&gt; Any:
--&gt; 135     key = _get_single_key(pat, silent)
    137     # walk the nested dict
    138     root, k = _get_root(key)

File ~/.../venv/lib/python3.10/site-packages/pandas/_config/config.py:121, in _get_single_key(pat, silent)
    119     if not silent:
    120         _warn_if_deprecated(pat)
--&gt; 121     raise OptionError(f&quot;No such keys(s): {repr(pat)}&quot;)
    122 if len(keys) &gt; 1:
    123     raise OptionError(&quot;Pattern matched multiple keys&quot;)

OptionError: No such keys(s): 'mode.use_inf_as_null'"><pre class="notranslate"><code class="notranslate">File ~/.../venv/lib/python3.10/site-packages/seaborn/_decorators.py:46, in _deprecate_positional_args.&lt;locals&gt;.inner_f(*args, **kwargs)
     36     warnings.warn(
     37         "Pass the following variable{} as {}keyword arg{}: {}. "
     38         "From version 0.12, the only valid positional argument "
   (...)
     43         FutureWarning
     44     )
     45 kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---&gt; 46 return f(**kwargs)

File ~/.../venv/lib/python3.10/site-packages/seaborn/axisgrid.py:2254, in jointplot(x, y, data, kind, color, height, ratio, space, dropna, xlim, ylim, marginal_ticks, joint_kws, marginal_kws, hue, palette, hue_order, hue_norm, **kwargs)
   2251         marginal_kws.setdefault("fill", True)
   2253     marginal_kws.setdefault("color", color)
-&gt; 2254     grid.plot_marginals(marg_func, **marginal_kws)
   2256 elif kind.startswith("hist"):
   2257 
   2258     # TODO process pair parameters for bins, etc. and pass
   2259     # to both jount and marginal plots
   2261     joint_kws.setdefault("color", color)

File ~/.../venv/lib/python3.10/site-packages/seaborn/axisgrid.py:1857, in JointGrid.plot_marginals(self, func, **kwargs)
   1854     orient_kw_y = {"vertical": True}
   1856 if seaborn_func:
-&gt; 1857     func(x=self.x, ax=self.ax_marg_x, **kwargs)
   1858 else:
   1859     plt.sca(self.ax_marg_x)

File ~/.../venv/lib/python3.10/site-packages/seaborn/distributions.py:1462, in histplot(data, x, y, hue, weights, stat, bins, binwidth, binrange, discrete, cumulative, common_bins, common_norm, multiple, element, fill, shrink, kde, kde_kws, line_kws, thresh, pthresh, pmax, cbar, cbar_ax, cbar_kws, palette, hue_order, hue_norm, color, log_scale, legend, ax, **kwargs)
   1451 estimate_kws = dict(
   1452     stat=stat,
   1453     bins=bins,
   (...)
   1457     cumulative=cumulative,
   1458 )
   1460 if p.univariate:
-&gt; 1462     p.plot_univariate_histogram(
   1463         multiple=multiple,
   1464         element=element,
   1465         fill=fill,
   1466         shrink=shrink,
   1467         common_norm=common_norm,
   1468         common_bins=common_bins,
   1469         kde=kde,
   1470         kde_kws=kde_kws,
   1471         color=color,
   1472         legend=legend,
   1473         estimate_kws=estimate_kws,
   1474         line_kws=line_kws,
   1475         **kwargs,
   1476     )
   1478 else:
   1480     p.plot_bivariate_histogram(
   1481         common_bins=common_bins,
   1482         common_norm=common_norm,
   (...)
   1492         **kwargs,
   1493     )

File ~/.../venv/lib/python3.10/site-packages/seaborn/distributions.py:428, in _DistributionPlotter.plot_univariate_histogram(self, multiple, element, fill, common_norm, common_bins, shrink, kde, kde_kws, color, legend, line_kws, estimate_kws, **plot_kws)
    418     densities = self._compute_univariate_density(
    419         self.data_variable,
    420         common_norm,
   (...)
    424         warn_singular=False,
    425     )
    427 # First pass through the data to compute the histograms
--&gt; 428 for sub_vars, sub_data in self.iter_data("hue", from_comp_data=True):
    429 
    430     # Prepare the relevant data
    431     key = tuple(sub_vars.items())
    432     sub_data = sub_data.dropna()

File ~/.../venv/lib/python3.10/site-packages/seaborn/_core.py:983, in VectorPlotter.iter_data(self, grouping_vars, reverse, from_comp_data)
    978 grouping_vars = [
    979     var for var in grouping_vars if var in self.variables
    980 ]
    982 if from_comp_data:
--&gt; 983     data = self.comp_data
    984 else:
    985     data = self.plot_data

File ~/.../venv/lib/python3.10/site-packages/seaborn/_core.py:1054, in VectorPlotter.comp_data(self)
   1050 axis = getattr(ax, f"{var}axis")
   1052 # Use the converter assigned to the axis to get a float representation
   1053 # of the data, passing np.nan or pd.NA through (pd.NA becomes np.nan)
-&gt; 1054 with pd.option_context('mode.use_inf_as_null', True):
   1055     orig = self.plot_data[var].dropna()
   1056 comp_col = pd.Series(index=orig.index, dtype=float, name=var)

File ~/.../venv/lib/python3.10/site-packages/pandas/_config/config.py:441, in option_context.__enter__(self)
    440 def __enter__(self) -&gt; None:
--&gt; 441     self.undo = [(pat, _get_option(pat, silent=True)) for pat, val in self.ops]
    443     for pat, val in self.ops:
    444         _set_option(pat, val, silent=True)

File ~/.../venv/lib/python3.10/site-packages/pandas/_config/config.py:441, in &lt;listcomp&gt;(.0)
    440 def __enter__(self) -&gt; None:
--&gt; 441     self.undo = [(pat, _get_option(pat, silent=True)) for pat, val in self.ops]
    443     for pat, val in self.ops:
    444         _set_option(pat, val, silent=True)

File ~/.../venv/lib/python3.10/site-packages/pandas/_config/config.py:135, in _get_option(pat, silent)
    134 def _get_option(pat: str, silent: bool = False) -&gt; Any:
--&gt; 135     key = _get_single_key(pat, silent)
    137     # walk the nested dict
    138     root, k = _get_root(key)

File ~/.../venv/lib/python3.10/site-packages/pandas/_config/config.py:121, in _get_single_key(pat, silent)
    119     if not silent:
    120         _warn_if_deprecated(pat)
--&gt; 121     raise OptionError(f"No such keys(s): {repr(pat)}")
    122 if len(keys) &gt; 1:
    123     raise OptionError("Pattern matched multiple keys")

OptionError: No such keys(s): 'mode.use_inf_as_null'
</code></pre></div>
<p dir="auto">I am making a joint plot using command -</p>
<p dir="auto">sns.jointplot(xdata,ydata,kind='reg', order=1,color='k',ylim=[-0.62,0.22],xlim=[-16,15],annot_kws={"loc": 4})</p>
<p dir="auto">With the annot_kws, I can move around where the annotation appears, but cannot change the font size. Also, can you select what stats you want to appear?</p>
<p dir="auto">Thanks!</p>