""" Provide basic components for groupby. """ from __future__ import annotations import dataclasses from typing import Hashable @dataclasses.dataclass(order=True, frozen=True) class OutputKey: label: Hashable position: int # special case to prevent duplicate plots when catching exceptions when # forwarding methods from NDFrames plotting_methods = frozenset(["plot", "hist"]) # cythonized transformations or canned "agg+broadcast", which do not # require postprocessing of the result by transform. cythonized_kernels = frozenset(["cumprod", "cumsum", "shift", "cummin", "cummax"]) # List of aggregation/reduction functions. # These map each group to a single numeric value reduction_kernels = frozenset( [ "all", "any", "corrwith", "count", "first", "idxmax", "idxmin", "last", "max", "mean", "median", "min", "nunique", "prod", # as long as `quantile`'s signature accepts only # a single quantile value, it's a reduction. # GH#27526 might change that. "quantile", "sem", "size", "skew", "std", "sum", "var", ] ) # List of transformation functions. # a transformation is a function that, for each group, # produces a result that has the same shape as the group. transformation_kernels = frozenset( [ "bfill", "cumcount", "cummax", "cummin", "cumprod", "cumsum", "diff", "ffill", "fillna", "ngroup", "pct_change", "rank", "shift", ] ) # these are all the public methods on Grouper which don't belong # in either of the above lists groupby_other_methods = frozenset( [ "agg", "aggregate", "apply", "boxplot", # corr and cov return ngroups*ncolumns rows, so they # are neither a transformation nor a reduction "corr", "cov", "describe", "dtypes", "expanding", "ewm", "filter", "get_group", "groups", "head", "hist", "indices", "ndim", "ngroups", "nth", "ohlc", "pipe", "plot", "resample", "rolling", "tail", "take", "transform", "sample", "value_counts", ] ) # Valid values of `name` for `groupby.transform(name)` # NOTE: do NOT edit this directly. New additions should be inserted # into the appropriate list above. transform_kernel_allowlist = reduction_kernels | transformation_kernels