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