BUG: added missing fill_na parameter to DataFrame.unstack() with list of levels (#30838)

* added missing fill_na parameter

Author: tanmay1618

doc/source/whatsnew/v1.0.0.rst

@@ -1040,6 +1040,7 @@ Reshaping
 - Dtypes are now preserved when transposing a ``DataFrame`` where each column is the same extension dtype (:issue:`30091`)
 - Bug in :func:`merge_asof` merging on a tz-aware ``left_index`` and ``right_on`` a tz-aware column (:issue:`29864`)
 - Improved error message and docstring in :func:`cut` and :func:`qcut` when `labels=True` (:issue:`13318`)
+- Bug in missing `fill_na` parameter to :meth:`DataFrame.unstack` with list of levels (:issue:`30740`)
 
 Sparse
 ^^^^^^

pandas/core/reshape/reshape.py

@@ -358,7 +358,7 @@ def _unstack_multiple(data, clocs, fill_value=None):
             result = data
             for i in range(len(clocs)):
                 val = clocs[i]
-                result = result.unstack(val)
+                result = result.unstack(val, fill_value=fill_value)
                 clocs = [v if i > v else v - 1 for v in clocs]
 
             return result

pandas/tests/frame/test_reshape.py

@@ -1128,3 +1128,34 @@ def test_stack_timezone_aware_values():
         ),
     )
     tm.assert_series_equal(result, expected)
+
+
+def test_unstacking_multi_index_df():
+    # see gh-30740
+    df = DataFrame(
+        {
+            "name": ["Alice", "Bob"],
+            "score": [9.5, 8],
+            "employed": [False, True],
+            "kids": [0, 0],
+            "gender": ["female", "male"],
+        }
+    )
+    df = df.set_index(["name", "employed", "kids", "gender"])
+    df = df.unstack(["gender"], fill_value=0)
+    expected = df.unstack("employed", fill_value=0).unstack("kids", fill_value=0)
+    result = df.unstack(["employed", "kids"], fill_value=0)
+    expected = DataFrame(
+        [[9.5, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 8.0]],
+        index=Index(["Alice", "Bob"], name="name"),
+        columns=MultiIndex.from_tuples(
+            [
+                ("score", "female", False, 0),
+                ("score", "female", True, 0),
+                ("score", "male", False, 0),
+                ("score", "male", True, 0),
+            ],
+            names=[None, "gender", "employed", "kids"],
+        ),
+    )
+    tm.assert_frame_equal(result, expected)