BUG: Add dropna to Grouper repr (pandas-dev#46754)

doc/source/whatsnew/v1.5.0.rst

@@ -603,6 +603,7 @@ Groupby/resample/rolling
 - Bug in :meth:`GroupBy.max` with empty groups and ``uint64`` dtype incorrectly raising ``RuntimeError`` (:issue:`46408`)
 - Bug in :meth:`.GroupBy.apply` would fail when ``func`` was a string and args or kwargs were supplied (:issue:`46479`)
 - Bug in :meth:`.Rolling.var` would segfault calculating weighted variance when window size was larger than data size (:issue:`46760`)
+- Bug in :meth:`Grouper.__repr__` where ``dropna`` was not included. Now it is (:issue:`46754`)
 
 Reshaping
 ^^^^^^^^^

pandas/core/groupby/grouper.py

@@ -263,7 +263,7 @@ class Grouper:
     _gpr_index: Index | None
     _grouper: Index | None
 
-    _attributes: tuple[str, ...] = ("key", "level", "freq", "axis", "sort")
+    _attributes: tuple[str, ...] = ("key", "level", "freq", "axis", "sort", "dropna")
 
     def __new__(cls, *args, **kwargs):
         if kwargs.get("freq") is not None:
@@ -287,6 +287,7 @@ def __init__(
         self.freq = freq
         self.axis = axis
         self.sort = sort
+        self.dropna = dropna
 
         self.grouper = None
         self._gpr_index = None
@@ -295,7 +296,6 @@ def __init__(
         self.binner = None
         self._grouper = None
         self._indexer = None
-        self.dropna = dropna
 
     @final
     @property
@@ -339,7 +339,7 @@ def _get_grouper(
         return self.binner, self.grouper, self.obj  # type: ignore[return-value]
 
     @final
-    def _set_grouper(self, obj: NDFrame, sort: bool = False):
+    def _set_grouper(self, obj: NDFrame, sort: bool = False) -> None:
         """
         given an object and the specifications, setup the internal grouper
         for this particular specification
@@ -413,7 +413,6 @@ def _set_grouper(self, obj: NDFrame, sort: bool = False):
         # "NDFrameT", variable has type "None")
         self.obj = obj  # type: ignore[assignment]
         self._gpr_index = ax
-        return self._gpr_index
 
     @final
     @property

pandas/core/resample.py

@@ -1470,14 +1470,14 @@ def __init__(
         self,
         freq="Min",
         closed: Literal["left", "right"] | None = None,
-        label: str | None = None,
+        label: Literal["left", "right"] | None = None,
         how="mean",
         axis=0,
         fill_method=None,
         limit=None,
         loffset=None,
         kind: str | None = None,
-        convention: str | None = None,
+        convention: Literal["start", "end", "e", "s"] | None = None,
         base: int | None = None,
         origin: str | TimestampConvertibleTypes = "start_day",
         offset: TimedeltaConvertibleTypes | None = None,
@@ -1523,10 +1523,7 @@ def __init__(
         self.closed = closed
         self.label = label
         self.kind = kind
-
-        self.convention = convention or "E"
-        self.convention = self.convention.lower()
-
+        self.convention = convention if convention is not None else "e"
         self.how = how
         self.fill_method = fill_method
         self.limit = limit

pandas/tests/groupby/test_groupby.py

@@ -31,7 +31,7 @@
 def test_repr():
     # GH18203
     result = repr(Grouper(key="A", level="B"))
-    expected = "Grouper(key='A', level='B', axis=0, sort=False)"
+    expected = "Grouper(key='A', level='B', axis=0, sort=False, dropna=True)"
     assert result == expected
 
 

pandas/tests/resample/test_time_grouper.py

@@ -266,15 +266,15 @@ def test_repr():
     # GH18203
     result = repr(Grouper(key="A", freq="H"))
     expected = (
-        "TimeGrouper(key='A', freq=<Hour>, axis=0, sort=True, "
+        "TimeGrouper(key='A', freq=<Hour>, axis=0, sort=True, dropna=True, "
         "closed='left', label='left', how='mean', "
         "convention='e', origin='start_day')"
     )
     assert result == expected
 
     result = repr(Grouper(key="A", freq="H", origin="2000-01-01"))
     expected = (
-        "TimeGrouper(key='A', freq=<Hour>, axis=0, sort=True, "
+        "TimeGrouper(key='A', freq=<Hour>, axis=0, sort=True, dropna=True, "
         "closed='left', label='left', how='mean', "
         "convention='e', origin=Timestamp('2000-01-01 00:00:00'))"
     )