BUG: resample.agg with read-only data

doc/source/whatsnew/v1.0.3.rst

@@ -15,6 +15,7 @@ including other versions of pandas.
 
 Fixed regressions
 ~~~~~~~~~~~~~~~~~
+- Fixed regression in ``resample.agg`` when the underlying data is non-writeable (:issue:`31710`)
 
 .. _whatsnew_103.bug_fixes:
 

pandas/_libs/groupby.pyx

@@ -848,11 +848,13 @@ cdef inline bint _treat_as_na(rank_t val, bint is_datetimelike) nogil:
         return val != val
 
 
+# GH#31710 use memorviews once cython 0.30 is released so we can
+#  use `const rank_t[:, :] values`
 @cython.wraparound(False)
 @cython.boundscheck(False)
 def group_last(rank_t[:, :] out,
                int64_t[:] counts,
-               rank_t[:, :] values,
+               ndarray[rank_t, ndim=2] values,
                const int64_t[:] labels,
                Py_ssize_t min_count=-1):
     """
@@ -937,11 +939,13 @@ def group_last(rank_t[:, :] out,
         raise RuntimeError("empty group with uint64_t")
 
 
+# GH#31710 use memorviews once cython 0.30 is released so we can
+#  use `const rank_t[:, :] values`
 @cython.wraparound(False)
 @cython.boundscheck(False)
 def group_nth(rank_t[:, :] out,
               int64_t[:] counts,
-              rank_t[:, :] values,
+              ndarray[rank_t, ndim=2] values,
               const int64_t[:] labels, int64_t rank=1,
               Py_ssize_t min_count=-1):
     """
@@ -1235,7 +1239,7 @@ ctypedef fused groupby_t:
 @cython.boundscheck(False)
 def group_max(groupby_t[:, :] out,
               int64_t[:] counts,
-              groupby_t[:, :] values,
+              ndarray[groupby_t, ndim=2] values,
               const int64_t[:] labels,
               Py_ssize_t min_count=-1):
     """
@@ -1308,7 +1312,7 @@ def group_max(groupby_t[:, :] out,
 @cython.boundscheck(False)
 def group_min(groupby_t[:, :] out,
               int64_t[:] counts,
-              groupby_t[:, :] values,
+              ndarray[groupby_t, ndim=2] values,
               const int64_t[:] labels,
               Py_ssize_t min_count=-1):
     """

pandas/core/series.py

@@ -840,11 +840,15 @@ def _slice(self, slobj: slice, axis: int = 0) -> "Series":
 
     def __getitem__(self, key):
         key = com.apply_if_callable(key, self)
+        key = lib.item_from_zerodim(key)
 
         if key is Ellipsis:
             return self
 
-        key_is_scalar = is_scalar(key)
+        # check for is_list_like/slice instead of is_scalar to allow non-standard
+        #  scalars through, e.g. cftime.datetime needed by xarray
+        #  https://github.com/pydata/xarray/issues/3751
+        key_is_scalar = not is_list_like(key) and not isinstance(key, slice)
         if isinstance(key, (list, tuple)):
             key = unpack_1tuple(key)
 

pandas/tests/resample/test_resample_api.py

@@ -580,3 +580,27 @@ def test_agg_with_datetime_index_list_agg_func(col_name):
         columns=pd.MultiIndex(levels=[[col_name], ["mean"]], codes=[[0], [0]]),
     )
     tm.assert_frame_equal(result, expected)
+
+
+def test_resample_agg_readonly():
+    # GH#31710 cython needs to allow readonly data
+    index = pd.date_range("2020-01-01", "2020-01-02", freq="1h")
+    arr = np.zeros_like(index)
+    arr.setflags(write=False)
+
+    ser = pd.Series(arr, index=index)
+    rs = ser.resample("1D")
+
+    expected = pd.Series([pd.Timestamp(0), pd.Timestamp(0)], index=index[::24])
+
+    result = rs.agg("last")
+    tm.assert_series_equal(result, expected)
+
+    result = rs.agg("first")
+    tm.assert_series_equal(result, expected)
+
+    result = rs.agg("max")
+    tm.assert_series_equal(result, expected)
+
+    result = rs.agg("min")
+    tm.assert_series_equal(result, expected)