From d41d30350345a1c180b39e57fbcdc81d9b2891dc Mon Sep 17 00:00:00 2001
From: Vikram M <vikramm@ibm.com>
Date: Wed, 21 Oct 2026 11:26:48 +0530
Subject: [PATCH] Fix datetime64 dtype assertion for big-endian platforms

The test hardcoded the little-endian dtype literal "<M8[ns]", which
fails on big-endian platforms where numpy naturally produces
big-endian arrays from this conversion path. Compare against
dates_array.dtype directly instead, which is endian-agnostic.
---
 .../test_plotly_utils/validators/test_pandas_series_input.py  | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/tests/test_plotly_utils/validators/test_pandas_series_input.py b/tests/test_plotly_utils/validators/test_pandas_series_input.py
index 0eded11d806..04e41a722d2 100644
--- a/tests/test_plotly_utils/validators/test_pandas_series_input.py
+++ b/tests/test_plotly_utils/validators/test_pandas_series_input.py
@@ -180,7 +180,7 @@ def test_data_array_validator_dates_series(
     assert isinstance(res, np.ndarray)
 
     # Check dtype
-    assert res.dtype == "<M8[ns]"
+    assert res.dtype == dates_array.dtype
 
     # Check values
     np.testing.assert_array_equal(res, dates_array)
@@ -196,7 +196,7 @@ def test_data_array_validator_dates_dataframe(
     assert isinstance(res, np.ndarray)
 
     # Check dtype
-    assert res.dtype == "<M8[ns]"
+    assert res.dtype == dates_array.dtype
 
     # Check values
     np.testing.assert_array_equal(res, dates_array.reshape(len(dates_array), 1))