BUG: asymmetric error bars for series (GH9536)

doc/source/user_guide/visualization.rst

@@ -1425,7 +1425,7 @@ Horizontal and vertical error bars can be supplied to the ``xerr`` and ``yerr``
 * As a ``str`` indicating which of the columns of plotting :class:`DataFrame` contain the error values.
 * As raw values (``list``, ``tuple``, or ``np.ndarray``). Must be the same length as the plotting :class:`DataFrame`/:class:`Series`.
 
-Asymmetrical error bars are also supported, however raw error values must be provided in this case. For a ``M`` length :class:`Series`, a ``Mx2`` array should be provided indicating lower and upper (or left and right) errors. For a ``MxN`` :class:`DataFrame`, asymmetrical errors should be in a ``Mx2xN`` array.
+Asymmetrical error bars are also supported, however raw error values must be provided in this case. For a ``N`` length :class:`Series`, a ``2xN`` array should be provided indicating lower and upper (or left and right) errors. For a ``MxN`` :class:`DataFrame`, asymmetrical errors should be in a ``Mx2xN`` array.
 
 Here is an example of one way to easily plot group means with standard deviations from the raw data.
 

doc/source/whatsnew/v1.1.0.rst

@@ -340,6 +340,7 @@ Other enhancements
 - :class:`pandas.core.window.ExponentialMovingWindow` now supports a ``times`` argument that allows ``mean`` to be calculated with observations spaced by the timestamps in ``times`` (:issue:`34839`)
 - :meth:`DataFrame.agg` and :meth:`Series.agg` now accept named aggregation for renaming the output columns/indexes. (:issue:`26513`)
 - ``compute.use_numba`` now exists as a configuration option that utilizes the numba engine when available (:issue:`33966`)
+- :meth:`Series.plot` now supports asymmetric error bars. Previously, if :meth:`Series.plot` received a "2xN" array with error values for `yerr` and/or `xerr`, the left/lower values (first row) were mirrored, while the right/upper values (second row) were ignored. Now, the first row represents the left/lower error values and the second row the right/upper error values. (:issue:`9536`)
 
 .. ---------------------------------------------------------------------------
 

pandas/plotting/_matplotlib/core.py

@@ -770,6 +770,12 @@ def _parse_errorbars(self, label, err):
             DataFrame/dict: error values are paired with keys matching the
                     key in the plotted DataFrame
             str: the name of the column within the plotted DataFrame
+
+        Asymmetrical error bars are also supported, however raw error values
+        must be provided in this case. For a ``N`` length :class:`Series`, a
+        ``2xN`` array should be provided indicating lower and upper (or left
+        and right) errors. For a ``MxN`` :class:`DataFrame`, asymmetrical errors
+        should be in a ``Mx2xN`` array.
         """
         if err is None:
             return None
@@ -810,7 +816,15 @@ def match_labels(data, e):
             err_shape = err.shape
 
             # asymmetrical error bars
-            if err.ndim == 3:
+            if isinstance(self.data, ABCSeries) and err_shape[0] == 2:
+                err = np.expand_dims(err, 0)
+                err_shape = err.shape
+                if err_shape[2] != len(self.data):
+                    raise ValueError(
+                        "Asymmetrical error bars should be provided "
+                        f"with the shape (2, {len(self.data)})"
+                    )
+            elif isinstance(self.data, ABCDataFrame) and err.ndim == 3:
                 if (
                     (err_shape[0] != self.nseries)
                     or (err_shape[1] != 2)

pandas/tests/plotting/test_series.py

@@ -729,6 +729,26 @@ def test_dup_datetime_index_plot(self):
         s = Series(values, index=index)
         _check_plot_works(s.plot)
 
+    def test_errorbar_asymmetrical(self):
+        # GH9536
+        s = Series(np.arange(10), name="x")
+        err = np.random.rand(2, 10)
+
+        ax = s.plot(yerr=err, xerr=err)
+
+        result = np.vstack([i.vertices[:, 1] for i in ax.collections[1].get_paths()])
+        expected = (err.T * np.array([-1, 1])) + s.to_numpy().reshape(-1, 1)
+        tm.assert_numpy_array_equal(result, expected)
+
+        msg = (
+            "Asymmetrical error bars should be provided "
+            f"with the shape \\(2, {len(s)}\\)"
+        )
+        with pytest.raises(ValueError, match=msg):
+            s.plot(yerr=np.random.rand(2, 11))
+
+        tm.close()
+
     @pytest.mark.slow
     def test_errorbar_plot(self):