def add_index_level(
old_index: pandas.Index, value: Any, name: str = None, loc: int = 0
) -> pandas.MultiIndex:
"""
Expand a (multi)index by adding a level to it.
:param old_index: The index to expand
:param name: The name of the new index level
:param value: Scalar or list-like, the values of the new index level
:param loc: Where to insert the level in the index, 0 is at the front, negative values count back from the rear end
:return: A new multi-index with the new level added
"""
def _handle_insert_loc(loc: int, n: int) -> int:
"""
Computes the insert index from the right if loc is negative for a given size of n.
"""
return n + loc + 1 if loc < 0 else loc
loc = _handle_insert_loc(loc, len(old_index.names))
old_index_df = old_index.to_frame()
old_index_df.insert(loc, name, value)
new_index_names = list(
old_index.names
) # sometimes new index level names are invented when converting to a df,
new_index_names.insert(loc, name) # here the original names are reconstructed
new_index = pandas.MultiIndex.from_frame(old_index_df, names=new_index_names)
return new_index
def _get_indexer(self, index: pd.Index) -> Iterable[bool]:
if not callable(self.cond):
return self.cond
func = partial(self.cond, **self.kwargs)
if isinstance(index, pd.MultiIndex):
mi_df = index.to_frame()
selected = mi_df[Everywhere(func)]
mi_values = pd.MultiIndex.from_frame(selected).to_numpy()
return index.get_locs(mi_values)
return func(index)
