BUG: Dtype was not changed when float was assignt to int column

doc/source/whatsnew/v1.2.0.rst

@@ -465,6 +465,7 @@ Indexing
 - Bug in indexing on a :class:`Series` or :class:`DataFrame` with a :class:`MultiIndex` with a level named "0" (:issue:`37194`)
 - Bug in :meth:`Series.__getitem__` when using an unsigned integer array as an indexer giving incorrect results or segfaulting instead of raising ``KeyError`` (:issue:`37218`)
 - Bug in :meth:`Index.where` incorrectly casting numeric values to strings (:issue:`37591`)
+- Bug in :meth:`DataFrame.at` and :meth:`Series.at` did not adjust dtype when float was assigned to integer column (:issue:`26395`)
 
 Missing
 ^^^^^^^

pandas/core/frame.py

@@ -91,7 +91,6 @@
     maybe_downcast_to_dtype,
     maybe_infer_to_datetimelike,
     maybe_upcast,
-    validate_numeric_casting,
 )
 from pandas.core.dtypes.common import (
     ensure_int64,
@@ -3202,13 +3201,8 @@ def _set_value(self, index, col, value, takeable: bool = False):
                 return
 
             series = self._get_item_cache(col)
-            engine = self.index._engine
-            loc = engine.get_loc(index)
-            validate_numeric_casting(series.dtype, value)
-
-            series._values[loc] = value
-            # Note: trying to use series._set_value breaks tests in
-            #  tests.frame.indexing.test_indexing and tests.indexing.test_partial
+            self.index._engine.get_loc(index)
+            series._set_value(index, value, takeable)
         except (KeyError, TypeError):
             # set using a non-recursive method & reset the cache
             if takeable:

pandas/core/series.py

@@ -42,6 +42,7 @@
 
 from pandas.core.dtypes.cast import (
     convert_dtypes,
+    infer_dtype_from_scalar,
     maybe_cast_to_extension_array,
     validate_numeric_casting,
 )
@@ -50,10 +51,12 @@
     is_bool,
     is_categorical_dtype,
     is_dict_like,
+    is_dtype_equal,
     is_extension_array_dtype,
     is_integer,
     is_iterator,
     is_list_like,
+    is_numeric_dtype,
     is_object_dtype,
     is_scalar,
     validate_all_hashable,
@@ -1110,6 +1113,10 @@ def _set_value(self, label, value, takeable: bool = False):
             else:
                 loc = self.index.get_loc(label)
                 validate_numeric_casting(self.dtype, value)
+                dtype, _ = infer_dtype_from_scalar(value, pandas_dtype=True)
+                if not is_dtype_equal(self.dtype, dtype) and is_numeric_dtype(dtype):
+                    self.loc[label] = value
+                    return
                 self._values[loc] = value
         except KeyError:
 

pandas/tests/indexing/test_at.py

@@ -3,7 +3,7 @@
 import numpy as np
 import pytest
 
-from pandas import DataFrame
+from pandas import DataFrame, Series
 import pandas._testing as tm
 
 
@@ -39,3 +39,19 @@ def test_at_with_duplicate_axes_requires_scalar_lookup(self):
             df.at[1, ["A"]] = 1
         with pytest.raises(ValueError, match=msg):
             df.at[:, "A"] = 1
+
+
+def test_at_assign_float_to_int_frame():
+    # GH: 26395
+    obj = DataFrame([0, 0, 0], index=["A", "B", "C"], columns=["D"])
+    obj.at["C", "D"] = 44.5
+    expected = DataFrame([0, 0, 44.5], index=["A", "B", "C"], columns=["D"])
+    tm.assert_frame_equal(obj, expected)
+
+
+def test_at_assign_float_to_int_series():
+    # GH: 26395
+    obj = Series([0, 0, 0], index=["A", "B", "C"])
+    obj.at["C"] = 44.5
+    expected = Series([0, 0, 44.5], index=["A", "B", "C"])
+    tm.assert_series_equal(obj, expected)