Fix for issue #57268 - ENH: Preserve input start/end type in interval… (#57399)

* Fix for issue #57268 - ENH: Preserve input start/end type in interval_range * issue #57268 - github actions resolution * Use generated datatype from breaks * Ruff - Pre-commit issue fix * Fix for issue #57268 - floating point support * int - float dtype compatability * whatsnew documentation update * OS based varaible access * Fixing failed unit test cases * pytest - interval passsed * Python backwards compatability * Pytest * Fixing PyLint and mypy issues * dtype specification * Conditional statement simplification * remove redundant code blocks * Changing whatsnew to interval section * Passing expected in parameterize * Update doc/source/whatsnew/v3.0.0.rst Co-authored-by: Matthew Roeschke <10647082+mroeschke@users.noreply.github.com> * Update pandas/core/indexes/interval.py Co-authored-by: Matthew Roeschke <10647082+mroeschke@users.noreply.github.com> --------- Co-authored-by: Matthew Roeschke <10647082+mroeschke@users.noreply.github.com>

Author: VISWESWARAN1998

doc/source/whatsnew/v3.0.0.rst

@@ -213,7 +213,7 @@ Strings
 
 Interval
 ^^^^^^^^
--
+- Bug in :func:`interval_range` where start and end numeric types were always cast to 64 bit (:issue:`57268`)
 -
 
 Indexing

pandas/core/indexes/interval.py

@@ -1101,9 +1101,23 @@ def interval_range(
  breaks: np.ndarray | TimedeltaIndex | DatetimeIndex
 
  if is_number(endpoint):
+ dtype: np.dtype = np.dtype("int64")
  if com.all_not_none(start, end, freq):
+ if (
+ isinstance(start, (float, np.float16))
+ or isinstance(end, (float, np.float16))
+ or isinstance(freq, (float, np.float16))
+ ):
+ dtype = np.dtype("float64")
+ elif (
+ isinstance(start, (np.integer, np.floating))
+ and isinstance(end, (np.integer, np.floating))
+ and start.dtype == end.dtype
+ ):
+ dtype = start.dtype
  # 0.1 ensures we capture end
  breaks = np.arange(start, end + (freq * 0.1), freq)
+ breaks = maybe_downcast_numeric(breaks, dtype)
  else:
  # compute the period/start/end if unspecified (at most one)
  if periods is None:
@@ -1122,7 +1136,7 @@ def interval_range(
  # expected "ndarray[Any, Any]" [
  breaks = maybe_downcast_numeric(
  breaks, # type: ignore[arg-type]
- np.dtype("int64"),
+ dtype,
  )
  else:
  # delegate to the appropriate range function
@@ -1131,4 +1145,9 @@ def interval_range(
  else:
  breaks = timedelta_range(start=start, end=end, periods=periods, freq=freq)
 
- return IntervalIndex.from_breaks(breaks, name=name, closed=closed)
+ return IntervalIndex.from_breaks(
+ breaks,
+ name=name,
+ closed=closed,
+ dtype=IntervalDtype(subtype=breaks.dtype, closed=closed),
+ )

pandas/tests/indexes/interval/test_interval_range.py

@@ -220,6 +220,20 @@ def test_float_subtype(self, start, end, freq):
  expected = "int64" if is_integer(start + end) else "float64"
  assert result == expected
 
+ @pytest.mark.parametrize(
+ "start, end, expected",
+ [
+ (np.int8(1), np.int8(10), np.dtype("int8")),
+ (np.int8(1), np.float16(10), np.dtype("float64")),
+ (np.float32(1), np.float32(10), np.dtype("float32")),
+ (1, 10, np.dtype("int64")),
+ (1, 10.0, np.dtype("float64")),
+ ],
+ )
+ def test_interval_dtype(self, start, end, expected):
+ result = interval_range(start=start, end=end).dtype.subtype
+ assert result == expected
+
  def test_interval_range_fractional_period(self):
  # float value for periods
  expected = interval_range(start=0, periods=10)