BUG: Fixes plotting with nullable integers (#32073) (#38014)

Author: rkc007

doc/source/whatsnew/v1.2.0.rst

@@ -746,6 +746,7 @@ Plotting
   indexed by a :class:`.TimedeltaIndex` with a fixed frequency and the x-axis lower limit was greater than the upper limit (:issue:`37454`)
 - Bug in :meth:`.DataFrameGroupBy.boxplot` when ``subplots=False`` would raise a ``KeyError`` (:issue:`16748`)
 - Bug in :meth:`DataFrame.plot` and :meth:`Series.plot` was overwriting matplotlib's shared y axes behaviour when no ``sharey`` parameter was passed (:issue:`37942`)
+- Bug in :meth:`DataFrame.plot` was raising a ``TypeError`` with ``ExtensionDtype`` columns (:issue:`32073`)
 
 
 Groupby/resample/rolling

pandas/plotting/_matplotlib/core.py

@@ -9,9 +9,12 @@
 from pandas.util._decorators import cache_readonly
 
 from pandas.core.dtypes.common import (
+    is_extension_array_dtype,
     is_float,
+    is_float_dtype,
     is_hashable,
     is_integer,
+    is_integer_dtype,
     is_iterator,
     is_list_like,
     is_number,
@@ -383,6 +386,20 @@ def result(self):
             else:
                 return self.axes[0]
 
+    def _convert_to_ndarray(self, data):
+        # GH32073: cast to float if values contain nulled integers
+        if (
+            is_integer_dtype(data.dtype) or is_float_dtype(data.dtype)
+        ) and is_extension_array_dtype(data.dtype):
+            return data.to_numpy(dtype="float", na_value=np.nan)
+
+        # GH25587: cast ExtensionArray of pandas (IntegerArray, etc.) to
+        # np.ndarray before plot.
+        if len(data) > 0:
+            return np.asarray(data)
+
+        return data
+
     def _compute_plot_data(self):
         data = self.data
 
@@ -423,13 +440,7 @@ def _compute_plot_data(self):
         if is_empty:
             raise TypeError("no numeric data to plot")
 
-        # GH25587: cast ExtensionArray of pandas (IntegerArray, etc.) to
-        # np.ndarray before plot.
-        numeric_data = numeric_data.copy()
-        for col in numeric_data:
-            numeric_data[col] = np.asarray(numeric_data[col])
-
-        self.data = numeric_data
+        self.data = numeric_data.apply(self._convert_to_ndarray)
 
     def _make_plot(self):
         raise AbstractMethodError(self)

pandas/tests/plotting/frame/test_frame.py

@@ -149,6 +149,28 @@ def test_plot(self):
         result = ax.axes
         assert result is axes[0]
 
+    def test_nullable_int_plot(self):
+        # GH 32073
+        dates = ["2008", "2009", None, "2011", "2012"]
+        df = DataFrame(
+            {
+                "A": [1, 2, 3, 4, 5],
+                "B": [1.0, 2.0, 3.0, 4.0, 5.0],
+                "C": [7, 5, np.nan, 3, 2],
+                "D": pd.to_datetime(dates, format="%Y"),
+                "E": pd.to_datetime(dates, format="%Y", utc=True),
+            },
+            dtype=np.int64,
+        )
+
+        _check_plot_works(df.plot, x="A", y="B")
+        _check_plot_works(df[["A", "B"]].plot, x="A", y="B")
+        _check_plot_works(df[["C", "A"]].plot, x="C", y="A")  # nullable value on x-axis
+        _check_plot_works(df[["A", "C"]].plot, x="A", y="C")
+        _check_plot_works(df[["B", "C"]].plot, x="B", y="C")
+        _check_plot_works(df[["A", "D"]].plot, x="A", y="D")
+        _check_plot_works(df[["A", "E"]].plot, x="A", y="E")
+
     def test_integer_array_plot(self):
         # GH 25587
         arr = integer_array([1, 2, 3, 4], dtype="UInt32")