BUG: from_dummies always returning object data

doc/source/whatsnew/v2.1.0.rst

@@ -828,6 +828,8 @@ Other
 - Bug in :func:`api.interchange.from_dataframe` when converting an empty DataFrame object (:issue:`53155`)
 - Bug in :func:`assert_almost_equal` now throwing assertion error for two unequal sets (:issue:`51727`)
 - Bug in :func:`assert_frame_equal` checks category dtypes even when asked not to check index type (:issue:`52126`)
+- Bug in :func:`from_dummies` where the resulting :class:`Index` did not match the original :class:`Index` (:issue:`54300`)
+- Bug in :func:`from_dummies` where the resulting data would always be ``object`` dtype instead of the dtype of the columns (:issue:`54300`)
 - Bug in :meth:`DataFrame.pivot_table` with casting the mean of ints back to an int (:issue:`16676`)
 - Bug in :meth:`DataFrame.reindex` with a ``fill_value`` that should be inferred with a :class:`ExtensionDtype` incorrectly inferring ``object`` dtype (:issue:`52586`)
 - Bug in :meth:`DataFrame.shift` and :meth:`Series.shift` and :meth:`DataFrameGroupBy.shift` when passing both "freq" and "fill_value" silently ignoring "fill_value" instead of raising ``ValueError`` (:issue:`53832`)

pandas/core/reshape/encoding.py

@@ -534,8 +534,13 @@ def from_dummies(
             )
         else:
             data_slice = data_to_decode.loc[:, prefix_slice]
-        cats_array = np.array(cats, dtype="object")
+        cats_array = data._constructor_sliced(cats, dtype=data.columns.dtype)
         # get indices of True entries along axis=1
-        cat_data[prefix] = cats_array[data_slice.to_numpy().nonzero()[1]]
+        true_values = data_slice.idxmax(axis=1)
+        indexer = data_slice.columns.get_indexer_for(true_values)
+        cat_data[prefix] = cats_array.take(indexer).set_axis(data.index)
 
-    return DataFrame(cat_data)
+    result = DataFrame(cat_data)
+    if sep is not None:
+        result.columns = result.columns.astype(data.columns.dtype)
+    return result

pandas/tests/reshape/test_from_dummies.py

@@ -257,7 +257,7 @@ def test_no_prefix_int_cats_basic():
     dummies = DataFrame(
         {1: [1, 0, 0, 0], 25: [0, 1, 0, 0], 2: [0, 0, 1, 0], 5: [0, 0, 0, 1]}
     )
-    expected = DataFrame({"": [1, 25, 2, 5]}, dtype="object")
+    expected = DataFrame({"": [1, 25, 2, 5]})
     result = from_dummies(dummies)
     tm.assert_frame_equal(result, expected)
 
@@ -266,7 +266,7 @@ def test_no_prefix_float_cats_basic():
     dummies = DataFrame(
         {1.0: [1, 0, 0, 0], 25.0: [0, 1, 0, 0], 2.5: [0, 0, 1, 0], 5.84: [0, 0, 0, 1]}
     )
-    expected = DataFrame({"": [1.0, 25.0, 2.5, 5.84]}, dtype="object")
+    expected = DataFrame({"": [1.0, 25.0, 2.5, 5.84]})
     result = from_dummies(dummies)
     tm.assert_frame_equal(result, expected)
 
@@ -399,3 +399,45 @@ def test_with_prefix_default_category(
         dummies_with_unassigned, sep="_", default_category=default_category
     )
     tm.assert_frame_equal(result, expected)
+
+
+def test_ea_categories():
+    # GH 54300
+    df = DataFrame({"a": [1, 0, 0, 1], "b": [0, 1, 0, 0], "c": [0, 0, 1, 0]})
+    df.columns = df.columns.astype("string[python]")
+    result = from_dummies(df)
+    expected = DataFrame({"": Series(list("abca"), dtype="string[python]")})
+    tm.assert_frame_equal(result, expected)
+
+
+def test_ea_categories_with_sep():
+    # GH 54300
+    df = DataFrame(
+        {
+            "col1_a": [1, 0, 1],
+            "col1_b": [0, 1, 0],
+            "col2_a": [0, 1, 0],
+            "col2_b": [1, 0, 0],
+            "col2_c": [0, 0, 1],
+        }
+    )
+    df.columns = df.columns.astype("string[python]")
+    result = from_dummies(df, sep="_")
+    expected = DataFrame(
+        {
+            "col1": Series(list("aba"), dtype="string[python]"),
+            "col2": Series(list("bac"), dtype="string[python]"),
+        }
+    )
+    expected.columns = expected.columns.astype("string[python]")
+    tm.assert_frame_equal(result, expected)
+
+
+def test_maintain_original_index():
+    # GH 54300
+    df = DataFrame(
+        {"a": [1, 0, 0, 1], "b": [0, 1, 0, 0], "c": [0, 0, 1, 0]}, index=list("abcd")
+    )
+    result = from_dummies(df)
+    expected = DataFrame({"": list("abca")}, index=list("abcd"))
+    tm.assert_frame_equal(result, expected)