filter_obs#
- Pseudobulk.filter_obs(*predicates, cell_types=None, excluded_cell_types=None, **constraints)[source]#
Equivalent to df.filter() from polars, but applied to both obs and X for each cell type.
- Parameters:
*predicates : str | Expr | Series | Iterable[str | Expr | Series] | bool | list[bool] | ndarray[dtype[bool]]
one or more column names, expressions that evaluate to Boolean Series, Boolean Series, lists of Booleans, and/or 1D Boolean NumPy arrays
cell_types : str | Iterable[str] | None
one or more cell types to operate on; if None, operate on all cell types. Mutually exclusive with excluded_cell_types.
excluded_cell_types : str | Iterable[str] | None
one or more cell types to exclude from the operation; mutually exclusive with cell_types
**constraints : Any
column filters: name=value filters to samples where the column named name has the value value
- Returns:
A new Pseudobulk dataset filtered to samples passing all the Boolean filters in predicates and constraints.
- Return type: