BUG: DateTimeIndex.is_year_start unexpected behavior when constructed…

… with freq 'MS' date_range (pandas-dev#57377) (pandas-dev#57494)

* Added some comments to where the bug is occurring

* Potential fix, passed all potentially relevant tests

* Very likely fix

* Reverted ro previous start/end scheme; added tests

* Added fixes to whatsnew doc

* Removed stray comment

* Fixed alphabetical problem in whatsnew

* add parametric test

* fixup

---------

Co-authored-by: Marco Gorelli <[email protected]>

doc/source/whatsnew/v3.0.0.rst

@@ -481,6 +481,7 @@ Categorical
 
 Datetimelike
 ^^^^^^^^^^^^
+- Bug in :attr:`is_year_start` where a DateTimeIndex constructed via a date_range with frequency 'MS' wouldn't have the correct year or quarter start attributes (:issue:`57377`)
 - Bug in :class:`Timestamp` constructor failing to raise when ``tz=None`` is explicitly specified in conjunction with timezone-aware ``tzinfo`` or data (:issue:`48688`)
 - Bug in :func:`date_range` where the last valid timestamp would sometimes not be produced (:issue:`56134`)
 - Bug in :func:`date_range` where using a negative frequency value would not include all points between the start and end values (:issue:`56382`)

pandas/_libs/tslibs/fields.pyx

@@ -253,9 +253,10 @@ def get_start_end_field(
         # month of year. Other offsets use month, startingMonth as ending
         # month of year.
 
-        if freq_name.lstrip("B")[0:2] in ["MS", "QS", "YS"]:
+        if freq_name.lstrip("B")[0:2] in ["QS", "YS"]:
             end_month = 12 if month_kw == 1 else month_kw - 1
             start_month = month_kw
+
         else:
             end_month = month_kw
             start_month = (end_month % 12) + 1

pandas/core/arrays/datetimes.py

@@ -143,7 +143,7 @@ def f(self):
                 month_kw = 12
                 if freq:
                     kwds = freq.kwds
-                    month_kw = kwds.get("startingMonth", kwds.get("month", 12))
+                    month_kw = kwds.get("startingMonth", kwds.get("month", month_kw))
 
                 if freq is not None:
                     freq_name = freq.name

pandas/tests/indexes/datetimes/test_scalar_compat.py

@@ -11,6 +11,8 @@
 import locale
 import unicodedata
 
+from hypothesis import given
+import hypothesis.strategies as st
 import numpy as np
 import pytest
 
@@ -329,6 +331,84 @@ def test_dti_is_month_start_custom(self):
         with pytest.raises(ValueError, match=msg):
             dti.is_month_start
 
+    @pytest.mark.parametrize(
+        "timestamp, freq, periods, expected_values",
+        [
+            ("2017-12-01", "MS", 3, np.array([False, True, False])),
+            ("2017-12-01", "QS", 3, np.array([True, False, False])),
+            ("2017-12-01", "YS", 3, np.array([True, True, True])),
+        ],
+    )
+    def test_dti_dr_is_year_start(self, timestamp, freq, periods, expected_values):
+        # GH57377
+        result = date_range(timestamp, freq=freq, periods=periods).is_year_start
+        tm.assert_numpy_array_equal(result, expected_values)
+
+    @pytest.mark.parametrize(
+        "timestamp, freq, periods, expected_values",
+        [
+            ("2017-12-01", "ME", 3, np.array([True, False, False])),
+            ("2017-12-01", "QE", 3, np.array([True, False, False])),
+            ("2017-12-01", "YE", 3, np.array([True, True, True])),
+        ],
+    )
+    def test_dti_dr_is_year_end(self, timestamp, freq, periods, expected_values):
+        # GH57377
+        result = date_range(timestamp, freq=freq, periods=periods).is_year_end
+        tm.assert_numpy_array_equal(result, expected_values)
+
+    @pytest.mark.parametrize(
+        "timestamp, freq, periods, expected_values",
+        [
+            ("2017-12-01", "MS", 3, np.array([False, True, False])),
+            ("2017-12-01", "QS", 3, np.array([True, True, True])),
+            ("2017-12-01", "YS", 3, np.array([True, True, True])),
+        ],
+    )
+    def test_dti_dr_is_quarter_start(self, timestamp, freq, periods, expected_values):
+        # GH57377
+        result = date_range(timestamp, freq=freq, periods=periods).is_quarter_start
+        tm.assert_numpy_array_equal(result, expected_values)
+
+    @pytest.mark.parametrize(
+        "timestamp, freq, periods, expected_values",
+        [
+            ("2017-12-01", "ME", 3, np.array([True, False, False])),
+            ("2017-12-01", "QE", 3, np.array([True, True, True])),
+            ("2017-12-01", "YE", 3, np.array([True, True, True])),
+        ],
+    )
+    def test_dti_dr_is_quarter_end(self, timestamp, freq, periods, expected_values):
+        # GH57377
+        result = date_range(timestamp, freq=freq, periods=periods).is_quarter_end
+        tm.assert_numpy_array_equal(result, expected_values)
+
+    @pytest.mark.parametrize(
+        "timestamp, freq, periods, expected_values",
+        [
+            ("2017-12-01", "MS", 3, np.array([True, True, True])),
+            ("2017-12-01", "QS", 3, np.array([True, True, True])),
+            ("2017-12-01", "YS", 3, np.array([True, True, True])),
+        ],
+    )
+    def test_dti_dr_is_month_start(self, timestamp, freq, periods, expected_values):
+        # GH57377
+        result = date_range(timestamp, freq=freq, periods=periods).is_month_start
+        tm.assert_numpy_array_equal(result, expected_values)
+
+    @pytest.mark.parametrize(
+        "timestamp, freq, periods, expected_values",
+        [
+            ("2017-12-01", "ME", 3, np.array([True, True, True])),
+            ("2017-12-01", "QE", 3, np.array([True, True, True])),
+            ("2017-12-01", "YE", 3, np.array([True, True, True])),
+        ],
+    )
+    def test_dti_dr_is_month_end(self, timestamp, freq, periods, expected_values):
+        # GH57377
+        result = date_range(timestamp, freq=freq, periods=periods).is_month_end
+        tm.assert_numpy_array_equal(result, expected_values)
+
     def test_dti_is_year_quarter_start_doubledigit_freq(self):
         # GH#58523
         dr = date_range("2017-01-01", periods=2, freq="10YS")
@@ -343,3 +423,18 @@ def test_dti_is_year_start_freq_custom_business_day_with_digit(self):
         msg = "Custom business days is not supported by is_year_start"
         with pytest.raises(ValueError, match=msg):
             dr.is_year_start
+
+
+@given(
+    dt=st.datetimes(min_value=datetime(1960, 1, 1), max_value=datetime(1980, 1, 1)),
+    n=st.integers(min_value=1, max_value=10),
+    freq=st.sampled_from(["MS", "QS", "YS"]),
+)
+@pytest.mark.slow
+def test_against_scalar_parametric(freq, dt, n):
+    # https://github.com/pandas-dev/pandas/issues/49606
+    freq = f"{n}{freq}"
+    d = date_range(dt, periods=3, freq=freq)
+    result = list(d.is_year_start)
+    expected = [x.is_year_start for x in d]
+    assert result == expected