ENH: option to return -inf/inf as lower/upper bound for qcut quantiles, see pandas-dev#17282

Author: dberenbaum

doc/source/whatsnew/v0.24.0.txt

@@ -17,6 +17,8 @@ New features
 
 - ``ExcelWriter`` now accepts ``mode`` as a keyword argument, enabling append to existing workbooks when using the ``openpyxl`` engine (:issue:`3441`)
 
+- :func: qcut now accepts ``bounded`` as a keyword argument, allowing for unbounded quantiles such that the lower/upper bounds are -inf/inf (:issue:`17282`)
+
 .. _whatsnew_0240.enhancements.extension_array_operators:
 
 ``ExtensionArray`` operator support

pandas/core/reshape/tile.py

@@ -238,7 +238,8 @@ def cut(x, bins, right=True, labels=None, retbins=False, precision=3,
                                 series_index, name, dtype)
 
 
-def qcut(x, q, labels=None, retbins=False, precision=3, duplicates='raise'):
+def qcut(x, q, labels=None, retbins=False, precision=3, duplicates='raise',
+         bounded=True):
     """
     Quantile-based discretization function. Discretize variable into
     equal-sized buckets based on rank or based on sample quantiles. For example
@@ -262,6 +263,9 @@ def qcut(x, q, labels=None, retbins=False, precision=3, duplicates='raise'):
         The precision at which to store and display the bins labels
     duplicates : {default 'raise', 'drop'}, optional
         If bin edges are not unique, raise ValueError or drop non-uniques.
+    bounded : bool, optional
+        Use the min/max of the distribution as the lower/upper bounds if True,
+        otherwise use -inf/inf. Ignored if dtype is datetime/timedelta.
 
         .. versionadded:: 0.20.0
 
@@ -302,6 +306,9 @@ def qcut(x, q, labels=None, retbins=False, precision=3, duplicates='raise'):
     else:
         quantiles = q
     bins = algos.quantile(x, quantiles)
+    if not bounded and not dtype:
+        bins[0] = -np.inf
+        bins[1] = np.inf
     fac, bins = _bins_to_cuts(x, bins, labels=labels,
                               precision=precision, include_lowest=True,
                               dtype=dtype, duplicates=duplicates)

pandas/tests/reshape/test_tile.py

@@ -479,6 +479,12 @@ def test_cut_read_only(self, array_1_writeable, array_2_writeable):
         tm.assert_categorical_equal(cut(hundred_elements, array_1),
                                     cut(hundred_elements, array_2))
 
+    def test_qcut_unbounded(self):
+        result = qcut(range(5), 4, bounded=False)
+        expected = [(-np.inf, 1.0], (-0.001, 1.0], (1.0, 2.0], (2.0, 3.0], 
+                    (3.0, np.inf]]
+        assert result == expected
+
 
 class TestDatelike(object):