From 20c7ecb9ff9f07eb078c034c288a84cff9f96fee Mon Sep 17 00:00:00 2001
From: htjworld <116538001+htjworld@users.noreply.github.com>
Date: Sat, 2 May 2026 11:32:55 +0900
Subject: [PATCH] gh-149259: Fix median_grouped() exception chaining and error
 messages

Split the single try/except block into two, add `from exc` chaining so
the original ValueError is visible in tracebacks, and improve the error
messages to identify whether `interval` or the data value failed the
float conversion.
---
 Lib/statistics.py                             | 11 +++++++++--
 Lib/test/test_statistics.py                   | 19 +++++++++++++++++++
 ...-05-02-11-32-35.gh-issue-149259.rJ6MXk.rst |  3 +++
 3 files changed, 31 insertions(+), 2 deletions(-)
 create mode 100644 Misc/NEWS.d/next/Library/2026-05-02-11-32-35.gh-issue-149259.rJ6MXk.rst

diff --git a/Lib/statistics.py b/Lib/statistics.py
index 32fcf2313a815a..0e5f4aee93ccc8 100644
--- a/Lib/statistics.py
+++ b/Lib/statistics.py
@@ -453,9 +453,16 @@ def median_grouped(data, interval=1.0):
     # Coerce to floats, raising a TypeError if not possible
     try:
         interval = float(interval)
+    except ValueError as exc:
+        raise TypeError(
+            f'interval must be a real number, got {interval!r}'
+        ) from exc
+    try:
         x = float(x)
-    except ValueError:
-        raise TypeError(f'Value cannot be converted to a float')
+    except ValueError as exc:
+        raise TypeError(
+            f'data sequence must contain real numbers, found {x!r}'
+        ) from exc
 
     # Interpolate the median using the formula found at:
     # https://www.cuemath.com/data/median-of-grouped-data/
diff --git a/Lib/test/test_statistics.py b/Lib/test/test_statistics.py
index 677a87b51b9192..9c92a6093bfd31 100644
--- a/Lib/test/test_statistics.py
+++ b/Lib/test/test_statistics.py
@@ -1799,6 +1799,25 @@ def test_data_type_error(self):
         interval = b""
         self.assertRaises(TypeError, self.func, data, interval)
 
+    def test_exception_chaining_and_messages(self):
+        # TypeError raised for bad interval should chain the original ValueError
+        # and identify the problematic parameter.
+        data = [1, 2, 3]
+        with self.assertRaises(TypeError) as cm:
+            self.func(data, interval="bad")
+        exc = cm.exception
+        self.assertIsInstance(exc.__cause__, ValueError)
+        self.assertIn("interval", str(exc))
+
+        # TypeError raised for non-numeric data should chain the original ValueError
+        # and identify that the data is the problem.
+        data = ["a", "b", "c"]
+        with self.assertRaises(TypeError) as cm:
+            self.func(data)
+        exc = cm.exception
+        self.assertIsInstance(exc.__cause__, ValueError)
+        self.assertIn("data", str(exc))
+
 
 class TestMode(NumericTestCase, AverageMixin, UnivariateTypeMixin):
     # Test cases for the discrete version of mode.
diff --git a/Misc/NEWS.d/next/Library/2026-05-02-11-32-35.gh-issue-149259.rJ6MXk.rst b/Misc/NEWS.d/next/Library/2026-05-02-11-32-35.gh-issue-149259.rJ6MXk.rst
new file mode 100644
index 00000000000000..80e643eeb1d121
--- /dev/null
+++ b/Misc/NEWS.d/next/Library/2026-05-02-11-32-35.gh-issue-149259.rJ6MXk.rst
@@ -0,0 +1,3 @@
+Fix :func:`statistics.median_grouped` to chain the original :exc:`ValueError`
+when coercing *interval* or the median data value to ``float`` fails, and
+improve the error message to identify which parameter caused the failure.