FIX: resample redefinition

Co-authored-by: André Correia <[email protected]>

Author: tiago-firmino

pandas/core/resample.py

@@ -1005,10 +1005,14 @@ def asfreq(self, fill_value=None):
         return self._upsample("asfreq", fill_value=fill_value)
 
     @final
+    @doc(GroupBy.sum)
     def sum(
         self,
         numeric_only: bool = False,
         min_count: int = 0,
+        skipna: bool = True,
+        engine: Literal["cython", "numba"] | None = None,
+        engine_kwargs: dict[str, bool] | None = None,
     ):
         """
         Compute sum of group values.
@@ -1050,14 +1054,18 @@ def sum(
         2023-02-01    7
         Freq: MS, dtype: int64
         """
-        return self._downsample("sum", numeric_only=numeric_only, min_count=min_count)
+        return self._downsample(
+            "sum",
+            numeric_only=numeric_only,
+            min_count=min_count,
+            skipna=skipna,
+            engine=engine,
+            engine_kwargs=engine_kwargs,
+        )
 
     @final
-    def prod(
-        self,
-        numeric_only: bool = False,
-        min_count: int = 0,
-    ):
+    @doc(GroupBy.prod)
+    def prod(self, numeric_only: bool = False, min_count: int = 0, skipna: bool = True):
         """
         Compute prod of group values.
 
@@ -1098,13 +1106,19 @@ def prod(
         2023-02-01   12
         Freq: MS, dtype: int64
         """
-        return self._downsample("prod", numeric_only=numeric_only, min_count=min_count)
+        return self._downsample(
+            "prod", numeric_only=numeric_only, min_count=min_count, skipna=skipna
+        )
 
     @final
+    @doc(GroupBy.min)
     def min(
         self,
         numeric_only: bool = False,
-        min_count: int = 0,
+        min_count: int = -1,
+        skipna: bool = True,
+        engine: Literal["cython", "numba"] | None = None,
+        engine_kwargs: dict[str, bool] | None = None,
     ):
         """
         Compute min value of group.
@@ -1132,13 +1146,24 @@ def min(
         2023-02-01    3
         Freq: MS, dtype: int64
         """
-        return self._downsample("min", numeric_only=numeric_only, min_count=min_count)
+        return self._downsample(
+            "min",
+            numeric_only=numeric_only,
+            min_count=min_count,
+            skipna=skipna,
+            engine=engine,
+            engine_kwargs=engine_kwargs,
+        )
 
     @final
+    @doc(GroupBy.max)
     def max(
         self,
         numeric_only: bool = False,
-        min_count: int = 0,
+        min_count: int = -1,
+        skipna: bool = True,
+        engine: Literal["cython", "numba"] | None = None,
+        engine_kwargs: dict[str, bool] | None = None,
     ):
         """
         Compute max value of group.
@@ -1166,7 +1191,14 @@ def max(
         2023-02-01    4
         Freq: MS, dtype: int64
         """
-        return self._downsample("max", numeric_only=numeric_only, min_count=min_count)
+        return self._downsample(
+            "max",
+            numeric_only=numeric_only,
+            min_count=min_count,
+            skipna=skipna,
+            engine=engine,
+            engine_kwargs=engine_kwargs,
+        )
 
     @final
     @doc(GroupBy.first)
@@ -1201,87 +1233,6 @@ def median(
     ):
         return self._downsample("median", numeric_only=numeric_only, skipna=skipna)
 
-    @final
-    @doc(GroupBy.mean)
-    def mean(
-        self,
-        numeric_only: bool = False,
-        skipna: bool = True,
-        engine: Literal["cython", "numba"] | None = None,
-        engine_kwargs: dict[str, bool] | None = None,
-    ):
-        return self._downsample(
-            "mean",
-            numeric_only=numeric_only,
-            skipna=skipna,
-            engine=engine,
-            engine_kwargs=engine_kwargs,
-        )
-
-    @final
-    @doc(GroupBy.min)
-    def min(
-        self,
-        numeric_only: bool = False,
-        min_count: int = -1,
-        skipna: bool = True,
-        engine: Literal["cython", "numba"] | None = None,
-        engine_kwargs: dict[str, bool] | None = None,
-    ):
-        return self._downsample(
-            "min",
-            numeric_only=numeric_only,
-            min_count=min_count,
-            skipna=skipna,
-            engine=engine,
-            engine_kwargs=engine_kwargs,
-        )
-
-    @final
-    @doc(GroupBy.max)
-    def max(
-        self,
-        numeric_only: bool = False,
-        min_count: int = -1,
-        skipna: bool = True,
-        engine: Literal["cython", "numba"] | None = None,
-        engine_kwargs: dict[str, bool] | None = None,
-    ):
-        return self._downsample(
-            "max",
-            numeric_only=numeric_only,
-            min_count=min_count,
-            skipna=skipna,
-            engine=engine,
-            engine_kwargs=engine_kwargs,
-        )
-
-    @final
-    @doc(GroupBy.sum)
-    def sum(
-        self,
-        numeric_only: bool = False,
-        min_count: int = 0,
-        skipna: bool = True,
-        engine: Literal["cython", "numba"] | None = None,
-        engine_kwargs: dict[str, bool] | None = None,
-    ):
-        return self._downsample(
-            "sum",
-            numeric_only=numeric_only,
-            min_count=min_count,
-            skipna=skipna,
-            engine=engine,
-            engine_kwargs=engine_kwargs,
-        )
-
-    @final
-    @doc(GroupBy.prod)
-    def prod(self, numeric_only: bool = False, min_count: int = 0, skipna: bool = True):
-        return self._downsample(
-            "prod", numeric_only=numeric_only, min_count=min_count, skipna=skipna
-        )
-
     @final
     @doc(GroupBy.any)
     def any(self, skipna: bool = True):
@@ -1293,9 +1244,13 @@ def all(self, skipna: bool = True):
         return self._downsample("all", skipna=skipna)
 
     @final
+    @doc(GroupBy.mean)
     def mean(
         self,
         numeric_only: bool = False,
+        skipna: bool = True,
+        engine: Literal["cython", "numba"] | None = None,
+        engine_kwargs: dict[str, bool] | None = None,
     ):
         """
         Compute mean of groups, excluding missing values.
@@ -1334,13 +1289,23 @@ def mean(
         2023-02-01    3.5
         Freq: MS, dtype: float64
         """
-        return self._downsample("mean", numeric_only=numeric_only)
+        return self._downsample(
+            "mean",
+            numeric_only=numeric_only,
+            skipna=skipna,
+            engine=engine,
+            engine_kwargs=engine_kwargs,
+        )
 
     @final
+    @doc(GroupBy.std)
     def std(
         self,
         ddof: int = 1,
+        engine: Literal["cython", "numba"] | None = None,
+        engine_kwargs: dict[str, bool] | None = None,
         numeric_only: bool = False,
+        skipna: bool = True,
     ):
         """
         Compute standard deviation of groups, excluding missing values.
@@ -1384,13 +1349,24 @@ def std(
         2023-02-01    2.645751
         Freq: MS, dtype: float64
         """
-        return self._downsample("std", ddof=ddof, numeric_only=numeric_only)
+        return self._downsample(
+            "std",
+            ddof=ddof,
+            engine=engine,
+            engine_kwargs=engine_kwargs,
+            numeric_only=numeric_only,
+            skipna=skipna,
+        )
 
     @final
+    @doc(GroupBy.var)
     def var(
         self,
         ddof: int = 1,
+        engine: Literal["cython", "numba"] | None = None,
+        engine_kwargs: dict[str, bool] | None = None,
         numeric_only: bool = False,
+        skipna: bool = True,
     ):
         """
         Compute variance of groups, excluding missing values.
@@ -1440,37 +1416,6 @@ def var(
         2023-02-01    4.666667
         Freq: MS, dtype: float64
         """
-        return self._downsample("var", ddof=ddof, numeric_only=numeric_only)
-
-    @final
-    @doc(GroupBy.std)
-    def std(
-        self,
-        ddof: int = 1,
-        engine: Literal["cython", "numba"] | None = None,
-        engine_kwargs: dict[str, bool] | None = None,
-        numeric_only: bool = False,
-        skipna: bool = True,
-    ):
-        return self._downsample(
-            "std",
-            ddof=ddof,
-            engine=engine,
-            engine_kwargs=engine_kwargs,
-            numeric_only=numeric_only,
-            skipna=skipna,
-        )
-
-    @final
-    @doc(GroupBy.var)
-    def var(
-        self,
-        ddof: int = 1,
-        engine: Literal["cython", "numba"] | None = None,
-        engine_kwargs: dict[str, bool] | None = None,
-        numeric_only: bool = False,
-        skipna: bool = True,
-    ):
         return self._downsample(
             "var",
             ddof=ddof,