diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py
index 6aecfe5267e0c..0f1cd397f2dd1 100644
--- a/pandas/core/indexing.py
+++ b/pandas/core/indexing.py
@@ -1753,6 +1753,13 @@ def _setitem_with_indexer(self, indexer, value, name: str = "iloc"):
                             if not isinstance(value, ABCSeries):
                                 # if not Series (in which case we need to align),
                                 #  we can short-circuit
+                                if (
+                                    isinstance(arr, np.ndarray)
+                                    and arr.ndim == 1
+                                    and len(arr) == 1
+                                ):
+                                    # NumPy 1.25 deprecation: https://github.com/numpy/numpy/pull/10615
+                                    arr = arr[0, ...]
                                 empty_value[indexer[0]] = arr
                                 self.obj[key] = empty_value
                                 return
diff --git a/pandas/core/internals/base.py b/pandas/core/internals/base.py
index 523dee97a3c5c..8f771221c8890 100644
--- a/pandas/core/internals/base.py
+++ b/pandas/core/internals/base.py
@@ -187,6 +187,10 @@ def setitem_inplace(self, indexer, value) -> None:
             #  dt64/td64, which do their own validation.
             value = np_can_hold_element(arr.dtype, value)
 
+        if isinstance(value, np.ndarray) and value.ndim == 1 and len(value) == 1:
+            # NumPy 1.25 deprecation: https://github.com/numpy/numpy/pull/10615
+            value = value[0, ...]
+
         arr[indexer] = value
 
     def grouped_reduce(self, func):
diff --git a/pandas/core/internals/blocks.py b/pandas/core/internals/blocks.py
index ff022cb047f3d..94670fe47036b 100644
--- a/pandas/core/internals/blocks.py
+++ b/pandas/core/internals/blocks.py
@@ -1063,7 +1063,9 @@ def setitem(self, indexer, value, using_cow: bool = False) -> Block:
                 self = self.make_block_same_class(
                     values.T if values.ndim == 2 else values
                 )
-
+            if isinstance(casted, np.ndarray) and casted.ndim == 1 and len(casted) == 1:
+                # NumPy 1.25 deprecation: https://github.com/numpy/numpy/pull/10615
+                casted = casted[0, ...]
             values[indexer] = casted
         return self
 
diff --git a/pandas/io/parsers/base_parser.py b/pandas/io/parsers/base_parser.py
index 99fbfe46d22fc..0bac882756a91 100644
--- a/pandas/io/parsers/base_parser.py
+++ b/pandas/io/parsers/base_parser.py
@@ -1114,6 +1114,12 @@ def _make_date_converter(
     if date_parser is not lib.no_default and date_format is not None:
         raise TypeError("Cannot use both 'date_parser' and 'date_format'")
 
+    def unpack_if_single_element(arg):
+        # NumPy 1.25 deprecation: https://github.com/numpy/numpy/pull/10615
+        if isinstance(arg, np.ndarray) and arg.ndim == 1 and len(arg) == 1:
+            return arg[0]
+        return arg
+
     def converter(*date_cols, col: Hashable):
         if date_parser is lib.no_default:
             strs = parsing.concat_date_cols(date_cols)
@@ -1137,7 +1143,9 @@ def converter(*date_cols, col: Hashable):
         else:
             try:
                 result = tools.to_datetime(
-                    date_parser(*date_cols), errors="ignore", cache=cache_dates
+                    date_parser(*(unpack_if_single_element(arg) for arg in date_cols)),
+                    errors="ignore",
+                    cache=cache_dates,
                 )
                 if isinstance(result, datetime.datetime):
                     raise Exception("scalar parser")
diff --git a/pandas/tests/groupby/test_groupby_dropna.py b/pandas/tests/groupby/test_groupby_dropna.py
index 48cc1518937b3..551642ff64fd5 100644
--- a/pandas/tests/groupby/test_groupby_dropna.py
+++ b/pandas/tests/groupby/test_groupby_dropna.py
@@ -627,7 +627,7 @@ def test_categorical_transformers(
     result = getattr(gb_keepna, transformation_func)(*args)
     expected = getattr(gb_dropna, transformation_func)(*args)
     for iloc, value in zip(
-        df[df["x"].isnull()].index.tolist(), null_group_result.values
+        df[df["x"].isnull()].index.tolist(), null_group_result.values.ravel()
     ):
         if expected.ndim == 1:
             expected.iloc[iloc] = value