diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 33539e8d294c1..673fb45d98f08 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -3232,9 +3232,12 @@ def first(
         self, numeric_only: bool = False, min_count: int = -1, skipna: bool = True
     ) -> NDFrameT:
         """
-        Compute the first entry of each column within each group.
+        Compute the first non-null entry of each column within each group.
 
-        Defaults to skipping NA elements.
+        This method operates column-wise, returning the first non-null value
+        in each column for every group. Unlike `nth(0)`, which returns the
+        first row (even if it contains nulls), `first()` skips over NA/null
+        values in each column independently.
 
         Parameters
         ----------
@@ -3251,15 +3254,15 @@ def first(
         Returns
         -------
         Series or DataFrame
-            First values within each group.
+            First non-null values within each group, selected independently per column.
 
         See Also
         --------
-        DataFrame.groupby : Apply a function groupby to each row or column of a
-            DataFrame.
-        core.groupby.DataFrameGroupBy.last : Compute the last non-null entry
-            of each column.
-        core.groupby.DataFrameGroupBy.nth : Take the nth row from each group.
+        DataFrame.groupby : Group DataFrame using a mapper or by a Series of columns.
+        Series.groupby : Group Series using a mapper or by a Series of values.
+        GroupBy.nth : Take the nth row from each group.
+        GroupBy.head : Return the first `n` rows from each group.
+        GroupBy.last : Compute the last non-null entry of each column.
 
         Examples
         --------
@@ -3272,23 +3275,38 @@ def first(
         ...     )
         ... )
         >>> df["D"] = pd.to_datetime(df["D"])
+
         >>> df.groupby("A").first()
-             B  C          D
+            B  C          D
         A
         1  5.0  1 2000-03-11
         3  6.0  3 2000-03-13
+
+        >>> df.groupby("A").nth(0)
+            B  C          D
+        A
+        1  NaN  1 2000-03-11
+        3  6.0  3 2000-03-13
+
+        >>> df.groupby("A").head(1)
+        A    B  C          D
+        0  1  NaN  1 2000-03-11
+        2  3  6.0  3 2000-03-13
+
         >>> df.groupby("A").first(min_count=2)
             B    C          D
         A
-        1 NaN  1.0 2000-03-11
-        3 NaN  NaN        NaT
+        1  NaN  1.0 2000-03-11
+        3  NaN  NaN        NaT
+
         >>> df.groupby("A").first(numeric_only=True)
-             B  C
+            B  C
         A
         1  5.0  1
         3  6.0  3
         """
 
+
         def first_compat(obj: NDFrameT):
             def first(x: Series):
                 """Helper function for first item that isn't NA."""