Skip to content

Generated interface inventory (pandas parity)

This file is generated from source. It inventories the pandas-like skin surface and attempts to show parent-interface signatures when available in the local environment.

PandasLikeFrame vs pandas.DataFrame

Method Our signature Parent Parent signature Status Notes
assign def assign(self, **columns) pandas.DataFrame (self, **kwargs) -> 'DataFrame' typed-parity
astype def astype(self, dtype, errors) pandas.DataFrame (self, dtype, copy: 'bool_t | None' = None, errors: 'IgnoreRaise' = 'raise') -> 'Self' typed-parity
columns def columns(self) pandas.DataFrame typed-parity
drop def drop(self, *args, strict, columns, axis, errors) pandas.DataFrame (self, labels: 'IndexLabel | None' = None, *, axis: 'Axis' = 0, index: 'IndexLabel | None' = None, columns: 'IndexLabel | None' = None, level: 'Level | None' = None, inplace: 'bool' = False, errors: 'IgnoreRaise' = 'raise') -> 'DataFrame | None' divergence columns-only; no index semantics
drop_duplicates def drop_duplicates(self, *subset, keep, maintain_order, **kwargs) pandas.DataFrame (self, subset: 'Hashable | Sequence[Hashable] | None' = None, *, keep: 'DropKeep' = 'first', inplace: 'bool' = False, ignore_index: 'bool' = False) -> 'DataFrame | None' typed-parity
dropna def dropna(self, axis, how, thresh, subset) pandas.DataFrame (self, *, axis: 'Axis' = 0, how: 'AnyAll | lib.NoDefault' = <no_default>, thresh: 'int | lib.NoDefault' = <no_default>, subset: 'IndexLabel | None' = None, inplace: 'bool' = False, ignore_index: 'bool' = False) -> 'DataFrame | None' divergence lowered to core ops; eager/index semantics differ
eval def eval(self, **columns) pandas.DataFrame (self, expr: 'str', *, inplace: 'bool' = False, **kwargs) -> 'Any | None' typed-parity
fillna def fillna(self, value, subset) pandas.DataFrame (self, value: 'Hashable | Mapping | Series | DataFrame | None' = None, *, method: 'FillnaOptions | None' = None, axis: 'Axis | None' = None, inplace: 'bool_t' = False, limit: 'int | None' = None, downcast: 'dict | None | lib.NoDefault' = <no_default>) -> 'Self | None' divergence lowered to core ops; eager/index semantics differ
filter def filter(self, *predicates, items, like, regex) pandas.DataFrame (self, items=None, like: 'str | None' = None, regex: 'str | None' = None, axis: 'Axis | None' = None) -> 'Self' typed-parity
head def head(self, n) pandas.DataFrame (self, n: 'int' = 5) -> 'Self' typed-parity
merge def merge(self, right, how, on, left_on, right_on, suffixes, options) pandas.DataFrame (self, right: 'DataFrame | Series', how: 'MergeHow' = 'inner', on: 'IndexLabel | AnyArrayLike | None' = None, left_on: 'IndexLabel | AnyArrayLike | None' = None, right_on: 'IndexLabel | AnyArrayLike | None' = None, left_index: 'bool' = False, right_index: 'bool' = False, sort: 'bool' = False, suffixes: 'Suffixes' = ('_x', '_y'), copy: 'bool | None' = None, indicator: 'str | bool' = False, validate: 'MergeValidate | None' = None) -> 'DataFrame' divergence lowered to core ops; eager/index semantics differ
nlargest def nlargest(self, n, columns, keep) pandas.DataFrame (self, n: 'int', columns: 'IndexLabel', keep: 'NsmallestNlargestKeep' = 'first') -> 'DataFrame' typed-parity
nsmallest def nsmallest(self, n, columns, keep) pandas.DataFrame (self, n: 'int', columns: 'IndexLabel', keep: 'NsmallestNlargestKeep' = 'first') -> 'DataFrame' typed-parity
query def query(self, expr) pandas.DataFrame (self, expr: 'str', *, inplace: 'bool' = False, **kwargs) -> 'DataFrame | None' divergence typed predicate only; no string expression parser
rename def rename(self, mapping, strict, **named) pandas.DataFrame (self, mapper: 'Renamer | None' = None, *, index: 'Renamer | None' = None, columns: 'Renamer | None' = None, axis: 'Axis | None' = None, copy: 'bool | None' = None, inplace: 'bool' = False, level: 'Level | None' = None, errors: 'IgnoreRaise' = 'ignore') -> 'DataFrame | None' typed-parity
rename_pandas def rename_pandas(self, columns, errors) pandas.DataFrame typed-parity
sort_values def sort_values(self, by, ascending, na_position) pandas.DataFrame (self, by: 'IndexLabel', *, axis: 'Axis' = 0, ascending: 'bool | list[bool] | tuple[bool, ...]' = True, inplace: 'bool' = False, kind: 'SortKind' = 'quicksort', na_position: 'str' = 'last', ignore_index: 'bool' = False, key: 'ValueKeyFunc | None' = None) -> 'DataFrame | None' typed-parity
tail def tail(self, n) pandas.DataFrame (self, n: 'int' = 5) -> 'Self' typed-parity