From 1268cebae53815b961e575bc9c63d54958d22875 Mon Sep 17 00:00:00 2001
From: theOehrly <23384863+theOehrly@users.noreply.github.com>
Date: Sun, 8 Oct 2023 18:41:16 +0200
Subject: [PATCH 1/3] FIX: handle potential TypeError when determining variable
 type

---
 seaborn/_base.py | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/seaborn/_base.py b/seaborn/_base.py
index e312923f5d..b659300078 100644
--- a/seaborn/_base.py
+++ b/seaborn/_base.py
@@ -1520,8 +1520,13 @@ def variable_type(vector, boolean_type="numeric"):
         warnings.simplefilter(
             action='ignore', category=(FutureWarning, DeprecationWarning)
         )
-        if np.isin(vector, [0, 1]).all():
-            return VariableType(boolean_type)
+        try:
+            if np.isin(vector, [0, 1]).all():
+                return VariableType(boolean_type)
+        except TypeError:
+            # .isin comparison is not guaranteed to be possible under NumPy
+            # casting rules, depending on the (unknown) dtype of 'vector'
+            pass
 
     # Defer to positive pandas tests
     if pd.api.types.is_numeric_dtype(vector):

From 91828baf25f1c343674ae758b36dedfdc584eb9f Mon Sep 17 00:00:00 2001
From: Michael Waskom <mwaskom@gmail.com>
Date: Sat, 4 Nov 2023 12:56:43 -0400
Subject: [PATCH 2/3] Handle edge case in duplicated _core code

---
 seaborn/_core/rules.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/seaborn/_core/rules.py b/seaborn/_core/rules.py
index 5057221f65..de6c651d97 100644
--- a/seaborn/_core/rules.py
+++ b/seaborn/_core/rules.py
@@ -97,7 +97,12 @@ def variable_type(
                 boolean_dtypes = ["bool"]
             boolean_vector = vector.dtype in boolean_dtypes
         else:
-            boolean_vector = bool(np.isin(vector, [0, 1]).all())
+            try:
+                boolean_vector = bool(np.isin(vector, [0, 1]).all())
+            except TypeError:
+                # .isin comparison is not guaranteed to be possible under NumPy
+                # casting rules, depending on the (unknown) dtype of 'vector'
+                boolean_vector = False
         if boolean_vector:
             return VarType(boolean_type)
 

From 3b6e1a7faabff0c184846b9caeadf17252cac610 Mon Sep 17 00:00:00 2001
From: Michael Waskom <mwaskom@gmail.com>
Date: Sat, 4 Nov 2023 12:56:48 -0400
Subject: [PATCH 3/3] Add tests

---
 tests/_core/test_rules.py | 8 ++++++++
 tests/test_base.py        | 5 +++++
 2 files changed, 13 insertions(+)

diff --git a/tests/_core/test_rules.py b/tests/_core/test_rules.py
index 714d5ead5c..161d2af292 100644
--- a/tests/_core/test_rules.py
+++ b/tests/_core/test_rules.py
@@ -52,6 +52,11 @@ def test_variable_type():
     assert variable_type(s, boolean_type="categorical") == "categorical"
     assert variable_type(s, boolean_type="boolean") == "boolean"
 
+    # This should arguably be datmetime, but we don't currently handle it correctly
+    # Test is mainly asserting that this doesn't fail on the boolean check.
+    s = pd.timedelta_range(1, periods=3, freq="D").to_series()
+    assert variable_type(s) == "categorical"
+
     s_cat = s.astype("category")
     assert variable_type(s_cat, boolean_type="categorical") == "categorical"
     assert variable_type(s_cat, boolean_type="numeric") == "categorical"
@@ -61,6 +66,9 @@ def test_variable_type():
     assert variable_type(s, boolean_type="boolean") == "boolean"
     assert variable_type(s, boolean_type="boolean", strict_boolean=True) == "numeric"
 
+    s = pd.Series([1, 0, 0])
+    assert variable_type(s, boolean_type="boolean") == "boolean"
+
     s = pd.Series([pd.Timestamp(1), pd.Timestamp(2)])
     assert variable_type(s) == "datetime"
     assert variable_type(s.astype(object)) == "datetime"
diff --git a/tests/test_base.py b/tests/test_base.py
index eea967cf93..4dfb3edfb4 100644
--- a/tests/test_base.py
+++ b/tests/test_base.py
@@ -1508,6 +1508,11 @@ def test_variable_type(self):
         assert variable_type(s.to_numpy()) == "categorical"
         assert variable_type(s.to_list()) == "categorical"
 
+        # This should arguably be datmetime, but we don't currently handle it correctly
+        # Test is mainly asserting that this doesn't fail on the boolean check.
+        s = pd.timedelta_range(1, periods=3, freq="D").to_series()
+        assert variable_type(s) == "categorical"
+
         s = pd.Series([True, False, False])
         assert variable_type(s) == "numeric"
         assert variable_type(s, boolean_type="categorical") == "categorical"