BUG: Fix to_json when converting Period column

.gitignore

@@ -118,3 +118,4 @@ doc/build/html/index.html
 doc/tmp.sv
 env/
 doc/source/savefig/
+venv/

doc/source/whatsnew/v1.1.0.rst

@@ -985,6 +985,7 @@ I/O
 - Bug in :meth:`read_excel` did not correctly handle multiple embedded spaces in OpenDocument text cells. (:issue:`32207`)
 - Bug in :meth:`read_json` was raising ``TypeError`` when reading a list of booleans into a Series. (:issue:`31464`)
 - Bug in :func:`pandas.io.json.json_normalize` where location specified by `record_path` doesn't point to an array. (:issue:`26284`)
+- Bug in :meth:`to_json` was raising ``AttributeError`` with column or Series of `PeriodDtype` (:issue:`31917`)
 - :func:`pandas.read_hdf` has a more explicit error message when loading an
   unsupported HDF file (:issue:`9539`)
 - Bug in :meth:`~DataFrame.read_feather` was raising an `ArrowIOError` when reading an s3 or http file path (:issue:`29055`)

pandas/conftest.py

@@ -477,6 +477,15 @@ def _create_series(index):
 }
 
 
+@pytest.fixture
+def period_series():
+    """Fixture for Series with Period-type index.
+    """
+    s = tm.makePeriodSeries()
+    s.name = "ps"
+    return s
+
+
 @pytest.fixture
 def series_with_simple_index(indices):
     """
@@ -588,6 +597,35 @@ def datetime_frame():
     return DataFrame(tm.getTimeSeriesData())
 
 
+@pytest.fixture
+def period_frame():
+    """
+    Fixture for DataFrame of floats with PeriodIndex
+
+    Columns are ['A', 'B', 'C', 'D']
+
+                       A         B         C         D
+    2000-01-03 -1.122153  0.468535  0.122226  1.693711
+    2000-01-04  0.189378  0.486100  0.007864 -1.216052
+    2000-01-05  0.041401 -0.835752 -0.035279 -0.414357
+    2000-01-06  0.430050  0.894352  0.090719  0.036939
+    2000-01-07 -0.620982 -0.668211 -0.706153  1.466335
+    2000-01-10 -0.752633  0.328434 -0.815325  0.699674
+    2000-01-11 -2.236969  0.615737 -0.829076 -1.196106
+    ...              ...       ...       ...       ...
+    2000-02-03  1.642618 -0.579288  0.046005  1.385249
+    2000-02-04 -0.544873 -1.160962 -0.284071 -1.418351
+    2000-02-07 -2.656149 -0.601387  1.410148  0.444150
+    2000-02-08 -1.201881 -1.289040  0.772992 -1.445300
+    2000-02-09  1.377373  0.398619  1.008453 -0.928207
+    2000-02-10  0.473194 -0.636677  0.984058  0.511519
+    2000-02-11 -0.965556  0.408313 -1.312844 -0.381948
+
+    [30 rows x 4 columns]
+    """
+    return DataFrame(tm.getPeriodData())
+
+
 @pytest.fixture
 def float_frame():
     """

pandas/tests/io/json/test_pandas.py

@@ -42,23 +42,6 @@ def setup(self):
 
         yield
 
-    @pytest.fixture
-    def datetime_series(self):
-        # Same as usual datetime_series, but with index freq set to None,
-        #  since that doesnt round-trip, see GH#33711
-        ser = tm.makeTimeSeries()
-        ser.name = "ts"
-        ser.index = ser.index._with_freq(None)
-        return ser
-
-    @pytest.fixture
-    def datetime_frame(self):
-        # Same as usual datetime_frame, but with index freq set to None,
-        #  since that doesnt round-trip, see GH#33711
-        df = DataFrame(tm.getTimeSeriesData())
-        df.index = df.index._with_freq(None)
-        return df
-
     def test_frame_double_encoded_labels(self, orient):
         df = DataFrame(
             [["a", "b"], ["c", "d"]],
@@ -382,6 +365,42 @@ def test_frame_to_json_except(self):
         with pytest.raises(ValueError, match=msg):
             df.to_json(orient="garbage")
 
+    def test_frame_roundtrip_period_index(self, orient, period_frame):
+        # GH32665: Fix to_json when converting Period column/series
+        if orient == "split":
+            pytest.skip("skipping orient=split due to different conversion schema")
+
+        data = period_frame.to_json(orient=orient)
+        result = pd.read_json(data, typ="frame", orient=orient)
+
+        expected = period_frame.copy()
+        if orient in ("values", "records"):
+            expected = expected.reset_index(drop=True)
+            if orient == "values":
+                # drop column names as well
+                expected = expected.T.reset_index(drop=True).T
+        if orient in ("index", "columns"):
+            result.index = result.index.to_period(freq=expected.index.freq)
+        expected.name = None
+
+        tm.assert_frame_equal(result, expected)
+
+    @pytest.mark.skip(reason="Conversion of Period-like column in dict-like format")
+    def test_frame_roundtrip_period_columns(self, orient, period_frame):
+        # GH32665: Fix to_json when converting Period column/series
+
+        test_frame = period_frame.reset_index()
+        data = test_frame.to_json(orient=orient)
+        result = pd.read_json(data, typ="frame", orient=orient)
+
+        expected = test_frame
+        if orient == "values":
+            expected.colummns = range(len(expected.columns))
+        if orient != "split":
+            expected.name = None
+
+        tm.assert_frame_equal(result, expected)
+
     def test_frame_empty(self):
         df = DataFrame(columns=["jim", "joe"])
         assert not df._is_mixed_type
@@ -433,9 +452,6 @@ def test_frame_mixedtype_orient(self):  # GH10289
         tm.assert_frame_equal(left, right)
 
     def test_v12_compat(self, datapath):
-        dti = pd.date_range("2000-01-03", "2000-01-07")
-        # freq doesnt roundtrip
-        dti = pd.DatetimeIndex(np.asarray(dti), freq=None)
         df = DataFrame(
             [
                 [1.56808523, 0.65727391, 1.81021139, -0.17251653],
@@ -445,7 +461,7 @@ def test_v12_compat(self, datapath):
                 [0.05951614, -2.69652057, 1.28163262, 0.34703478],
             ],
             columns=["A", "B", "C", "D"],
-            index=dti,
+            index=pd.date_range("2000-01-03", "2000-01-07"),
         )
         df["date"] = pd.Timestamp("19920106 18:21:32.12")
         df.iloc[3, df.columns.get_loc("date")] = pd.Timestamp("20130101")
@@ -464,9 +480,6 @@ def test_v12_compat(self, datapath):
 
     def test_blocks_compat_GH9037(self):
         index = pd.date_range("20000101", periods=10, freq="H")
-        # freq doesnt round-trip
-        index = pd.DatetimeIndex(list(index), freq=None)
-
         df_mixed = DataFrame(
             OrderedDict(
                 float_1=[
@@ -673,6 +686,23 @@ def test_series_roundtrip_timeseries(self, orient, numpy, datetime_series):
 
         tm.assert_series_equal(result, expected)
 
+    def test_series_roundtrip_periodseries(self, orient, period_series):
+        # GH32665: Fix to_json when converting Period column/series
+        if orient == "split":
+            pytest.skip("skipping orient=split due to different conversion schema")
+
+        data = period_series.to_json(orient=orient)
+        result = pd.read_json(data, typ="series", orient=orient)
+
+        expected = period_series
+        if orient in ("values", "records"):
+            expected = expected.reset_index(drop=True)
+        if orient in ("index", "columns"):
+            result.index = result.index.to_period(freq=expected.index.freq)
+        expected.name = None
+
+        tm.assert_series_equal(result, expected)
+
     @pytest.mark.parametrize("dtype", [np.float64, int])
     @pytest.mark.parametrize("numpy", [True, False])
     def test_series_roundtrip_numeric(self, orient, numpy, dtype):