feat(core): Add add_zeros_like function

src/pandas_indexing/accessors.py

@@ -19,6 +19,7 @@
 
 from . import arithmetics
 from .core import (
+    add_zeros_like,
     aggregatelevel,
     antijoin,
     assignlevel,
@@ -208,6 +209,16 @@ def aggregate(
             self._obj, agg_func=agg_func, axis=axis, dropna=dropna, mode=mode, **levels
         )
 
+    @doc(add_zeros_like, data="")
+    def add_zeros_like(
+        self,
+        reference: Union[MultiIndex, DataFrame, Series],
+        /,
+        derive: Optional[Dict[str, MultiIndex]] = None,
+        **levels: Sequence[str],
+    ):
+        return add_zeros_like(self._obj, reference=reference, derive=derive, **levels)
+
 
 def _create_forward_binop(op):
     def forward_binop(

src/pandas_indexing/core.py

@@ -1075,3 +1075,64 @@ def has_any_label(index: MultiIndex, level: str, labels: Sequence[Any]):
         raise ValueError(
             f'mode must be "replace", "append" or "return", but is "{mode}"'
         )
+
+
+@doc(
+    data="""
+    data : Data
+        Series or DataFrame to extend with zeros\
+    """
+)
+def add_zeros_like(
+    data: T,
+    reference: Union[MultiIndex, DataFrame, Series],
+    *,
+    derive: Optional[Dict[str, MultiIndex]] = None,
+    **levels: Sequence[str],
+) -> T:
+    """Add explicit `levels` to `data` as 0 values.
+
+    Remaining levels in `data` not found in `levels` or `derive` are taken from
+    `reference` (or its index).
+
+    Parameters
+    ----------\
+    {data}
+    reference : Index
+        expected level labels (like model, scenario combinations)
+    derive : dict
+        derive labels in a level from a multiindex with allowed combinations
+    **levels : [str]
+        which labels should be added to df
+
+    Returns
+    -------
+    DataFrame
+        unsorted data with additional zero data
+    """
+
+    if any(len(labels) == 0 for labels in levels.values()):
+        return data
+
+    if isinstance(reference, (Series, DataFrame)):
+        reference = reference.index
+
+    if derive is None:
+        derive = {}
+
+    target_levels = data.index.names
+    index = reference.pix.unique(
+        target_levels.difference(levels.keys()).difference(derive.keys())
+    )
+
+    zero_index = concat(
+        reduce(
+            lambda ind, d: ind.join(d, how="left"),
+            derive.values(),
+            index.pix.assign(**dict(zip(levels.keys(), labels))),
+        ).reorder_levels(target_levels)
+        for labels in product(*levels.values())
+    )
+    zero_index = antijoin(zero_index, data.index)
+
+    return concat([data, pd.DataFrame(0, index=zero_index, columns=data.columns)])

tests/test_accessors.py

@@ -9,6 +9,8 @@
 from pandas import DataFrame, Index, MultiIndex
 from pandas.testing import assert_frame_equal, assert_index_equal, assert_series_equal
 
+import pandas_indexing  # noqa: F401
+
 
 def test_assign_index(midx: MultiIndex):
     """
@@ -138,3 +140,14 @@ def test_aggregate(mdf):
             MultiIndex.from_tuples([("bar", 3), ("foo", "new")], names=["str", "num"]),
         ),
     )
+
+
+def test_add_zeros_like(mdf):
+    reference = MultiIndex.from_arrays(
+        [["foo", "foo", "bar", "baz"], [1, 2, 3, 4], ["a", "b", "c", "d"]],
+        names=["str", "num", "new"],
+    )
+    assert_frame_equal(
+        mdf.pix.add_zeros_like(reference),
+        mdf.reindex(reference.droplevel("new"), fill_value=0),
+    )

tests/test_core.py

@@ -13,6 +13,7 @@
 from pandas.testing import assert_frame_equal, assert_index_equal, assert_series_equal
 
 from pandas_indexing.core import (
+    add_zeros_like,
     aggregatelevel,
     antijoin,
     assignlevel,
@@ -612,3 +613,44 @@ def test_aggregatelevel(mdf):
 
     with pytest.raises(ValueError):
         aggregatelevel(mdf, num=dict(new=[1, 2]), mode="bla")
+
+
+def test_add_zeros_like(mdf):
+    reference = MultiIndex.from_arrays(
+        [["foo", "foo", "bar", "baz"], [1, 2, 3, 4], ["a", "b", "c", "d"]],
+        names=["str", "num", "new"],
+    )
+    assert_frame_equal(
+        add_zeros_like(mdf, reference),
+        mdf.reindex(reference.droplevel("new"), fill_value=0),
+    )
+
+    assert_frame_equal(
+        add_zeros_like(mdf, Series(0, reference)),
+        mdf.reindex(reference.droplevel("new"), fill_value=0),
+    )
+
+    assert_frame_equal(add_zeros_like(mdf, reference, blub=[]), mdf)
+
+    missing = MultiIndex.from_arrays(
+        [["bar", "baz", "foo", "baz"], [2, 2, 3, 3]], names=["str", "num"]
+    )
+    assert_frame_equal(
+        add_zeros_like(mdf, reference, num=[2, 3]),
+        mdf.reindex(mdf.index.append(missing), fill_value=0),
+    )
+
+    def add_first(df):
+        index = df if isinstance(df, Index) else df.index
+        return assignlevel(df, first=projectlevel(index, "str").str[:1])
+
+    mdf_w_first = add_first(mdf)
+    assert_frame_equal(
+        add_zeros_like(
+            mdf_w_first,
+            reference,
+            num=[2, 3],
+            derive=dict(first=add_first(Index(["foo", "bar", "baz"], name="str"))),
+        ),
+        mdf_w_first.reindex(mdf_w_first.index.append(add_first(missing)), fill_value=0),
+    )