File inf_as_na.patch of Package failed_python-seaborn
From 23860365816440b050e9211e1c395a966de3c403 Mon Sep 17 00:00:00 2001
From: Matthew Roeschke <10647082+mroeschke@users.noreply.github.com>
Date: Sat, 19 Aug 2023 03:41:57 -1000
Subject: [PATCH] Address inf_as_na pandas deprecation (#3424)
* Address inf_as_na pandas deprecation
* Add -np.inf, add import
* flake8
* Make copy
* Use mask instead of replace
---
seaborn/_base.py | 14 +++++++-------
seaborn/_core/plot.py | 34 +++++++++++++++++++---------------
2 files changed, 26 insertions(+), 22 deletions(-)
Index: seaborn-0.12.2/seaborn/_oldcore.py
===================================================================
--- seaborn-0.12.2.orig/seaborn/_oldcore.py
+++ seaborn-0.12.2/seaborn/_oldcore.py
@@ -1116,13 +1116,13 @@ class VectorPlotter:
parts = []
grouped = self.plot_data[var].groupby(self.converters[var], sort=False)
for converter, orig in grouped:
- with pd.option_context('mode.use_inf_as_na', True):
- orig = orig.dropna()
- if var in self.var_levels:
- # TODO this should happen in some centralized location
- # it is similar to GH2419, but more complicated because
- # supporting `order` in categorical plots is tricky
- orig = orig[orig.isin(self.var_levels[var])]
+ orig = orig.mask(orig.isin([np.inf, -np.inf]), np.nan)
+ orig = orig.dropna()
+ if var in self.var_levels:
+ # TODO this should happen in some centralized location
+ # it is similar to GH2419, but more complicated because
+ # supporting `order` in categorical plots is tricky
+ orig = orig[orig.isin(self.var_levels[var])]
comp = pd.to_numeric(converter.convert_units(orig))
if converter.get_scale() == "log":
comp = np.log10(comp)
Index: seaborn-0.12.2/seaborn/_core/plot.py
===================================================================
--- seaborn-0.12.2.orig/seaborn/_core/plot.py
+++ seaborn-0.12.2/seaborn/_core/plot.py
@@ -20,6 +20,7 @@ import matplotlib as mpl
from matplotlib.axes import Axes
from matplotlib.artist import Artist
from matplotlib.figure import Figure
+import numpy as np
from seaborn._marks.base import Mark
from seaborn._stats.base import Stat
@@ -1488,21 +1489,24 @@ class Plotter:
axes_df = self._filter_subplot_data(df, view)
- with pd.option_context("mode.use_inf_as_na", True):
- if keep_na:
- # The simpler thing to do would be x.dropna().reindex(x.index).
- # But that doesn't work with the way that the subset iteration
- # is written below, which assumes data for grouping vars.
- # Matplotlib (usually?) masks nan data, so this should "work".
- # Downstream code can also drop these rows, at some speed cost.
- present = axes_df.notna().all(axis=1)
- nulled = {}
- for axis in "xy":
- if axis in axes_df:
- nulled[axis] = axes_df[axis].where(present)
- axes_df = axes_df.assign(**nulled)
- else:
- axes_df = axes_df.dropna()
+ axes_df_inf_as_nan = axes_df.copy()
+ axes_df_inf_as_nan = axes_df_inf_as_nan.mask(
+ axes_df_inf_as_nan.isin([np.inf, -np.inf]), np.nan
+ )
+ if keep_na:
+ # The simpler thing to do would be x.dropna().reindex(x.index).
+ # But that doesn't work with the way that the subset iteration
+ # is written below, which assumes data for grouping vars.
+ # Matplotlib (usually?) masks nan data, so this should "work".
+ # Downstream code can also drop these rows, at some speed cost.
+ present = axes_df_inf_as_nan.notna().all(axis=1)
+ nulled = {}
+ for axis in "xy":
+ if axis in axes_df:
+ nulled[axis] = axes_df[axis].where(present)
+ axes_df = axes_df_inf_as_nan.assign(**nulled)
+ else:
+ axes_df = axes_df_inf_as_nan.dropna()
subplot_keys = {}
for dim in ["col", "row"]:
