DataFrameGroupby.boxplot fails when subplots=False

doc/source/whatsnew/v1.0.0.rst

@@ -169,6 +169,7 @@ Plotting
 - Bug in :meth:`DataFrame.plot` producing incorrect legend markers when plotting multiple series on the same axis (:issue:`18222`)
 - Bug in :meth:`DataFrame.plot` when ``kind='box'`` and data contains datetime or timedelta data. These types are now automatically dropped (:issue:`22799`)
 - Bug in :meth:`DataFrame.plot.line` and :meth:`DataFrame.plot.area` produce wrong xlim in x-axis (:issue:`27686`, :issue:`25160`, :issue:`24784`)
+- Bug in :meth:`DataFrameGroupby.boxplot` when ``subplots=False``, a KeyError would raise (:issue:`16748`)
 
 Groupby/resample/rolling
 ^^^^^^^^^^^^^^^^^^^^^^^^

pandas/plotting/_matplotlib/boxplot.py

@@ -9,6 +9,7 @@
 
 import pandas as pd
 
+from pandas import IndexSlice, Index, MultiIndex
 from pandas.io.formats.printing import pprint_thing
 from pandas.plotting._matplotlib import converter
 from pandas.plotting._matplotlib.core import LinePlot, MPLPlot
@@ -314,10 +315,21 @@ def plot_group(keys, values, ax):
             with plt.rc_context(rc):
                 ax = plt.gca()
         data = data._get_numeric_data()
+
+        # if columns is None, use all numeric columns of data; if data columns
+        # is multiIndex, which means a groupby has been applied before, select
+        # data using new grouped column names; if data columns is Index, select
+        # data simply using columns
         if columns is None:
             columns = data.columns
-        else:
-            data = data[columns]
+        elif isinstance(data.columns, MultiIndex):
+
+            # reselect columns with after-groupby multi-index columns
+            data = data.loc[:, IndexSlice[:, columns]]
+            columns = data.columns
+        elif isinstance(data.columns, Index):
+            data = data.loc[:, columns]
+            columns = data.columns
 
         result = plot_group(columns, data.values.T, ax)
         ax.grid(grid)

pandas/tests/plotting/test_boxplot_method.py

@@ -412,3 +412,46 @@ def test_fontsize(self):
         self._check_ticks_props(
             df.boxplot("a", by="b", fontsize=16), xlabelsize=16, ylabelsize=16
         )
+
+    @pytest.mark.parametrize(
+        "col, expected_xticklabel",
+        [
+            ("v", ["(a, v)", "(b, v)", "(c, v)", "(d, v)", "(e, v)"]),
+            (["v"], ["(a, v)", "(b, v)", "(c, v)", "(d, v)", "(e, v)"]),
+            ("v1", ["(a, v1)", "(b, v1)", "(c, v1)", "(d, v1)", "(e, v1)"]),
+            (
+                ["v", "v1"],
+                [
+                    "(a, v)",
+                    "(a, v1)",
+                    "(b, v)",
+                    "(b, v1)",
+                    "(c, v)",
+                    "(c, v1)",
+                    "(d, v)",
+                    "(d, v1)",
+                    "(e, v)",
+                    "(e, v1)",
+                ],
+            ),
+        ],
+    )
+    def test_groupby_boxplot_subplots_false(self, col, expected_xticklabel):
+        # GH 16748
+        df = DataFrame(
+            {
+                "cat": np.random.choice(list("abcde"), 100),
+                "v": np.random.rand(100),
+                "v1": np.random.rand(100),
+            }
+        )
+        grouped = df.groupby("cat")
+
+        # check is boxplot with subplots=False works
+        axes = _check_plot_works(
+            grouped.boxplot, subplots=False, column=col, return_type="axes"
+        )
+
+        # check if xticks labels are plotted correctly
+        result_xticklabel = [x.get_text() for x in axes.get_xticklabels()]
+        assert expected_xticklabel == result_xticklabel