ENH + BUG: insert of new values for axis parameter on pandas.DataFrame.quantile

pandas/core/frame.py

@@ -4363,8 +4363,9 @@ def quantile(self, q=0.5, axis=0, numeric_only=True):
         ----------
         q : float or array-like, default 0.5 (50% quantile)
             0 <= q <= 1, the quantile(s) to compute
-        axis : {0, 1}
-            0 for row-wise, 1 for column-wise
+        axis : {0, 1, 'index', 'columns'} (default 0)
+            0 or 'index' for row-wise, 1 or 'columns' for column-wise 
+
 
         Returns
         -------
@@ -4410,6 +4411,9 @@ def f(arr, per):
                 return _quantile(values, per)
 
         data = self._get_numeric_data() if numeric_only else self
+
+        axis = self._get_axis_number(axis)
+
         if axis == 1:
             data = data.T
 

pandas/tests/test_frame.py

@@ -11786,6 +11786,30 @@ def test_quantile(self):
         expected = Series([3., 4.], index=[0, 1])
         assert_series_equal(result, expected)
 
+    def test_quantile_axis_parameter(self):
+        from numpy import percentile
+
+        df = DataFrame({"A": [1, 2, 3], "B": [2, 3, 4]}, index=[1, 2, 3])
+
+        result = df.quantile(.5, axis=0)
+
+        expected = Series([2., 3.], index=["A", "B"])
+        assert_series_equal(result, expected)
+
+        expected = df.quantile(.5, axis="index")
+        assert_series_equal(result, expected)
+
+        result = df.quantile(.5, axis=1)
+
+        expected = Series([1.5, 2.5, 3.5], index=[1, 2, 3])
+        assert_series_equal(result, expected)
+
+        result = df.quantile(.5, axis="columns")
+        assert_series_equal(result, expected)
+
+        assertRaises(ValueError, df.quantile, 0.1, axis=-1)
+        assertRaises(ValueError, df.quantile, 0.1, axis="column")
+
     def test_quantile_multi(self):
         df = DataFrame([[1, 1, 1], [2, 2, 2], [3, 3, 3]],
                        columns=['a', 'b', 'c'])