ENH: support of pandas.DataFrame.hist for datetime data (pandas-dev#36287)

Author: onshek

doc/source/whatsnew/v1.2.0.rst

@@ -185,6 +185,7 @@ Other enhancements
 - :meth:`DataFrame.applymap` now supports ``na_action`` (:issue:`23803`)
 - :class:`Index` with object dtype supports division and multiplication (:issue:`34160`)
 - :meth:`DataFrame.explode` and :meth:`Series.explode` now support exploding of sets (:issue:`35614`)
+- :meth:`DataFrame.hist` now supports time series (datetime) data (:issue:`32590`)
 - ``Styler`` now allows direct CSS class name addition to individual data cells (:issue:`36159`)
 - :meth:`Rolling.mean()` and :meth:`Rolling.sum()` use Kahan summation to calculate the mean to avoid numerical problems (:issue:`10319`, :issue:`11645`, :issue:`13254`, :issue:`32761`, :issue:`36031`)
 - :meth:`DatetimeIndex.searchsorted`, :meth:`TimedeltaIndex.searchsorted`, :meth:`PeriodIndex.searchsorted`, and :meth:`Series.searchsorted` with datetimelike dtypes will now try to cast string arguments (listlike and scalar) to the matching datetimelike type (:issue:`36346`)

pandas/plotting/_matplotlib/hist.py

@@ -417,11 +417,16 @@ def hist_frame(
         if not isinstance(column, (list, np.ndarray, ABCIndexClass)):
             column = [column]
         data = data[column]
-    data = data._get_numeric_data()
+    # GH32590
+    data = data.select_dtypes(
+        include=(np.number, "datetime64", "datetimetz"), exclude="timedelta"
+    )
     naxes = len(data.columns)
 
     if naxes == 0:
-        raise ValueError("hist method requires numerical columns, nothing to plot.")
+        raise ValueError(
+            "hist method requires numerical or datetime columns, nothing to plot."
+        )
 
     fig, axes = create_subplots(
         naxes=naxes,

pandas/tests/plotting/common.py

@@ -10,7 +10,7 @@
 from pandas.core.dtypes.api import is_list_like
 
 import pandas as pd
-from pandas import DataFrame, Series
+from pandas import DataFrame, Series, to_datetime
 import pandas._testing as tm
 
 
@@ -28,6 +28,9 @@ def setup_method(self, method):
 
         mpl.rcdefaults()
 
+        self.start_date_to_int64 = 812419200000000000
+        self.end_date_to_int64 = 819331200000000000
+
         self.mpl_ge_2_2_3 = compat.mpl_ge_2_2_3()
         self.mpl_ge_3_0_0 = compat.mpl_ge_3_0_0()
         self.mpl_ge_3_1_0 = compat.mpl_ge_3_1_0()
@@ -50,6 +53,14 @@ def setup_method(self, method):
                     "height": random.normal(66, 4, size=n),
                     "weight": random.normal(161, 32, size=n),
                     "category": random.randint(4, size=n),
+                    "datetime": to_datetime(
+                        random.randint(
+                            self.start_date_to_int64,
+                            self.end_date_to_int64,
+                            size=n,
+                            dtype=np.int64,
+                        )
+                    ),
                 }
             )
 

pandas/tests/plotting/test_hist_method.py

@@ -6,7 +6,7 @@
 
 import pandas.util._test_decorators as td
 
-from pandas import DataFrame, Index, Series
+from pandas import DataFrame, Index, Series, to_datetime
 import pandas._testing as tm
 from pandas.tests.plotting.common import TestPlotBase, _check_plot_works
 
@@ -163,17 +163,34 @@ def test_hist_df_legacy(self):
             _check_plot_works(self.hist_df.hist)
 
         # make sure layout is handled
-        df = DataFrame(randn(100, 3))
+        df = DataFrame(randn(100, 2))
+        df[2] = to_datetime(
+            np.random.randint(
+                self.start_date_to_int64,
+                self.end_date_to_int64,
+                size=100,
+                dtype=np.int64,
+            )
+        )
         with tm.assert_produces_warning(UserWarning):
             axes = _check_plot_works(df.hist, grid=False)
         self._check_axes_shape(axes, axes_num=3, layout=(2, 2))
         assert not axes[1, 1].get_visible()
 
+        _check_plot_works(df[[2]].hist)
         df = DataFrame(randn(100, 1))
         _check_plot_works(df.hist)
 
         # make sure layout is handled
-        df = DataFrame(randn(100, 6))
+        df = DataFrame(randn(100, 5))
+        df[5] = to_datetime(
+            np.random.randint(
+                self.start_date_to_int64,
+                self.end_date_to_int64,
+                size=100,
+                dtype=np.int64,
+            )
+        )
         with tm.assert_produces_warning(UserWarning):
             axes = _check_plot_works(df.hist, layout=(4, 2))
         self._check_axes_shape(axes, axes_num=6, layout=(4, 2))
@@ -225,18 +242,42 @@ def test_hist_df_legacy(self):
             ser.hist(foo="bar")
 
     @pytest.mark.slow
-    def test_hist_non_numerical_raises(self):
-        # gh-10444
-        df = DataFrame(np.random.rand(10, 2))
+    def test_hist_non_numerical_or_datetime_raises(self):
+        # gh-10444, GH32590
+        df = DataFrame(
+            {
+                "a": np.random.rand(10),
+                "b": np.random.randint(0, 10, 10),
+                "c": to_datetime(
+                    np.random.randint(
+                        1582800000000000000, 1583500000000000000, 10, dtype=np.int64
+                    )
+                ),
+                "d": to_datetime(
+                    np.random.randint(
+                        1582800000000000000, 1583500000000000000, 10, dtype=np.int64
+                    ),
+                    utc=True,
+                ),
+            }
+        )
         df_o = df.astype(object)
 
-        msg = "hist method requires numerical columns, nothing to plot."
+        msg = "hist method requires numerical or datetime columns, nothing to plot."
         with pytest.raises(ValueError, match=msg):
             df_o.hist()
 
     @pytest.mark.slow
     def test_hist_layout(self):
-        df = DataFrame(randn(100, 3))
+        df = DataFrame(randn(100, 2))
+        df[2] = to_datetime(
+            np.random.randint(
+                self.start_date_to_int64,
+                self.end_date_to_int64,
+                size=100,
+                dtype=np.int64,
+            )
+        )
 
         layout_to_expected_size = (
             {"layout": None, "expected_size": (2, 2)},  # default is 2x2
@@ -268,7 +309,15 @@ def test_hist_layout(self):
     @pytest.mark.slow
     # GH 9351
     def test_tight_layout(self):
-        df = DataFrame(randn(100, 3))
+        df = DataFrame(np.random.randn(100, 2))
+        df[2] = to_datetime(
+            np.random.randint(
+                self.start_date_to_int64,
+                self.end_date_to_int64,
+                size=100,
+                dtype=np.int64,
+            )
+        )
         _check_plot_works(df.hist)
         self.plt.tight_layout()
 
@@ -355,7 +404,15 @@ def test_grouped_hist_legacy(self):
 
         from pandas.plotting._matplotlib.hist import _grouped_hist
 
-        df = DataFrame(randn(500, 2), columns=["A", "B"])
+        df = DataFrame(randn(500, 1), columns=["A"])
+        df["B"] = to_datetime(
+            np.random.randint(
+                self.start_date_to_int64,
+                self.end_date_to_int64,
+                size=500,
+                dtype=np.int64,
+            )
+        )
         df["C"] = np.random.randint(0, 4, 500)
         df["D"] = ["X"] * 500