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repo_id stringlengths 12 110 | file_path stringlengths 24 164 | content stringlengths 3 89.3M | __index_level_0__ int64 0 0 |
|---|---|---|---|
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/dtypes/api.py | from pandas.core.dtypes.common import (
is_any_real_numeric_dtype,
is_array_like,
is_bool,
is_bool_dtype,
is_categorical_dtype,
is_complex,
is_complex_dtype,
is_datetime64_any_dtype,
is_datetime64_dtype,
is_datetime64_ns_dtype,
is_datetime64tz_dtype,
is_dict_like,
is_... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/dtypes/cast.py | """
Routines for casting.
"""
from __future__ import annotations
import datetime as dt
import functools
from typing import (
TYPE_CHECKING,
Any,
Literal,
TypeVar,
cast,
overload,
)
import warnings
import numpy as np
from pandas._config import using_pyarrow_string_dtype
from pandas._libs imp... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/dtypes/missing.py | """
missing types & inference
"""
from __future__ import annotations
from decimal import Decimal
from functools import partial
from typing import (
TYPE_CHECKING,
overload,
)
import warnings
import numpy as np
from pandas._config import get_option
from pandas._libs import lib
import pandas._libs.missing as ... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/dtypes/inference.py | """ basic inference routines """
from __future__ import annotations
from collections import abc
from numbers import Number
import re
from re import Pattern
from typing import TYPE_CHECKING
import numpy as np
from pandas._libs import lib
if TYPE_CHECKING:
from collections.abc import Hashable
from pandas._t... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/dtypes/concat.py | """
Utility functions related to concat.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
cast,
)
import warnings
import numpy as np
from pandas._libs import lib
from pandas.util._exceptions import find_stack_level
from pandas.core.dtypes.astype import astype_array
from pandas.core... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/dtypes/astype.py | """
Functions for implementing 'astype' methods according to pandas conventions,
particularly ones that differ from numpy.
"""
from __future__ import annotations
import inspect
from typing import (
TYPE_CHECKING,
overload,
)
import warnings
import numpy as np
from pandas._libs import lib
from pandas._libs.ts... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/dtypes/dtypes.py | """
Define extension dtypes.
"""
from __future__ import annotations
from datetime import (
date,
datetime,
time,
timedelta,
)
from decimal import Decimal
import re
from typing import (
TYPE_CHECKING,
Any,
cast,
)
import warnings
import numpy as np
import pytz
from pandas._libs import (
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/strings/accessor.py | from __future__ import annotations
import codecs
from functools import wraps
import re
from typing import (
TYPE_CHECKING,
Callable,
Literal,
cast,
)
import warnings
import numpy as np
from pandas._libs import lib
from pandas._typing import (
AlignJoin,
DtypeObj,
F,
Scalar,
npt,
)... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/strings/base.py | from __future__ import annotations
import abc
from typing import (
TYPE_CHECKING,
Callable,
Literal,
)
import numpy as np
if TYPE_CHECKING:
from collections.abc import Sequence
import re
from pandas._typing import Scalar
from pandas import Series
class BaseStringArrayMethods(abc.ABC):... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/strings/__init__.py | """
Implementation of pandas.Series.str and its interface.
* strings.accessor.StringMethods : Accessor for Series.str
* strings.base.BaseStringArrayMethods: Mixin ABC for EAs to implement str methods
Most methods on the StringMethods accessor follow the pattern:
1. extract the array from the series (or index)
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/strings/object_array.py | from __future__ import annotations
import functools
import re
import textwrap
from typing import (
TYPE_CHECKING,
Callable,
Literal,
cast,
)
import unicodedata
import numpy as np
from pandas._libs import lib
import pandas._libs.missing as libmissing
import pandas._libs.ops as libops
from pandas.core... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/internals/construction.py | """
Functions for preparing various inputs passed to the DataFrame or Series
constructors before passing them to a BlockManager.
"""
from __future__ import annotations
from collections import abc
from typing import (
TYPE_CHECKING,
Any,
)
import numpy as np
from numpy import ma
from pandas._config import usi... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/internals/blocks.py | from __future__ import annotations
from functools import wraps
import re
from typing import (
TYPE_CHECKING,
Any,
Callable,
Literal,
cast,
final,
)
import warnings
import weakref
import numpy as np
from pandas._config import (
get_option,
using_copy_on_write,
)
from pandas._libs impo... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/internals/ops.py | from __future__ import annotations
from typing import (
TYPE_CHECKING,
NamedTuple,
)
from pandas.core.dtypes.common import is_1d_only_ea_dtype
if TYPE_CHECKING:
from collections.abc import Iterator
from pandas._libs.internals import BlockPlacement
from pandas._typing import ArrayLike
from p... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/internals/managers.py | from __future__ import annotations
from collections.abc import (
Hashable,
Sequence,
)
import itertools
from typing import (
TYPE_CHECKING,
Callable,
Literal,
cast,
)
import warnings
import weakref
import numpy as np
from pandas._config import (
using_copy_on_write,
warn_copy_on_write... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/internals/base.py | """
Base class for the internal managers. Both BlockManager and ArrayManager
inherit from this class.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
Literal,
cast,
final,
)
import numpy as np
from pandas._config import using_copy_on_write
from pandas._libs import... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/internals/api.py | """
This is a pseudo-public API for downstream libraries. We ask that downstream
authors
1) Try to avoid using internals directly altogether, and failing that,
2) Use only functions exposed here (or in core.internals)
"""
from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from ... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/internals/array_manager.py | """
Experimental manager based on storing a collection of 1D arrays
"""
from __future__ import annotations
import itertools
from typing import (
TYPE_CHECKING,
Callable,
Literal,
)
import numpy as np
from pandas._libs import (
NaT,
lib,
)
from pandas.core.dtypes.astype import (
astype_array,... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/internals/concat.py | from __future__ import annotations
from typing import (
TYPE_CHECKING,
cast,
)
import warnings
import numpy as np
from pandas._libs import (
NaT,
algos as libalgos,
internals as libinternals,
lib,
)
from pandas._libs.missing import NA
from pandas.util._decorators import cache_readonly
from pa... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/internals/__init__.py | from pandas.core.internals.api import make_block
from pandas.core.internals.array_manager import (
ArrayManager,
SingleArrayManager,
)
from pandas.core.internals.base import (
DataManager,
SingleDataManager,
)
from pandas.core.internals.blocks import ( # io.pytables, io.packers
Block,
DatetimeT... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexes/multi.py | from __future__ import annotations
from collections.abc import (
Collection,
Generator,
Hashable,
Iterable,
Sequence,
)
from functools import wraps
from sys import getsizeof
from typing import (
TYPE_CHECKING,
Any,
Callable,
Literal,
cast,
)
import warnings
import numpy as np
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexes/accessors.py | """
datetimelike delegation
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
cast,
)
import warnings
import numpy as np
from pandas._libs import lib
from pandas.util._exceptions import find_stack_level
from pandas.core.dtypes.common import (
is_integer_dtype,
is_list_like,
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexes/timedeltas.py | """ implement the TimedeltaIndex """
from __future__ import annotations
from typing import TYPE_CHECKING
import warnings
from pandas._libs import (
index as libindex,
lib,
)
from pandas._libs.tslibs import (
Resolution,
Timedelta,
to_offset,
)
from pandas._libs.tslibs.timedeltas import disallow_am... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexes/period.py | from __future__ import annotations
from datetime import (
datetime,
timedelta,
)
from typing import TYPE_CHECKING
import warnings
import numpy as np
from pandas._libs import index as libindex
from pandas._libs.tslibs import (
BaseOffset,
NaT,
Period,
Resolution,
Tick,
)
from pandas._libs.... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexes/frozen.py | """
frozen (immutable) data structures to support MultiIndexing
These are used for:
- .names (FrozenList)
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
NoReturn,
)
from pandas.core.base import PandasObject
from pandas.io.formats.printing import pprint_thing
if TYPE_CHECKING:
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexes/datetimelike.py | """
Base and utility classes for tseries type pandas objects.
"""
from __future__ import annotations
from abc import (
ABC,
abstractmethod,
)
from typing import (
TYPE_CHECKING,
Any,
Callable,
cast,
final,
)
import warnings
import numpy as np
from pandas._config import using_copy_on_write... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexes/datetimes.py | from __future__ import annotations
import datetime as dt
import operator
from typing import TYPE_CHECKING
import warnings
import numpy as np
import pytz
from pandas._libs import (
NaT,
Period,
Timestamp,
index as libindex,
lib,
)
from pandas._libs.tslibs import (
Resolution,
periods_per_d... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexes/base.py | from __future__ import annotations
from collections import abc
from datetime import datetime
import functools
from itertools import zip_longest
import operator
from typing import (
TYPE_CHECKING,
Any,
Callable,
ClassVar,
Literal,
NoReturn,
cast,
final,
overload,
)
import warnings
i... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexes/interval.py | """ define the IntervalIndex """
from __future__ import annotations
from operator import (
le,
lt,
)
import textwrap
from typing import (
TYPE_CHECKING,
Any,
Literal,
)
import numpy as np
from pandas._libs import lib
from pandas._libs.interval import (
Interval,
IntervalMixin,
Interva... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexes/api.py | from __future__ import annotations
import textwrap
from typing import (
TYPE_CHECKING,
cast,
)
import numpy as np
from pandas._libs import (
NaT,
lib,
)
from pandas.errors import InvalidIndexError
from pandas.core.dtypes.cast import find_common_type
from pandas.core.algorithms import safe_sort
from... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexes/category.py | from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
Literal,
cast,
)
import numpy as np
from pandas._libs import index as libindex
from pandas.util._decorators import (
cache_readonly,
doc,
)
from pandas.core.dtypes.common import is_scalar
from pandas.core.dtypes.conc... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexes/range.py | from __future__ import annotations
from collections.abc import (
Hashable,
Iterator,
)
from datetime import timedelta
import operator
from sys import getsizeof
from typing import (
TYPE_CHECKING,
Any,
Callable,
cast,
)
import numpy as np
from pandas._libs import (
index as libindex,
l... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexes/extension.py | """
Shared methods for Index subclasses backed by ExtensionArray.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Callable,
TypeVar,
)
from pandas.util._decorators import cache_readonly
from pandas.core.dtypes.generic import ABCDataFrame
from pandas.core.indexes.base import In... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/util/hashing.py | """
data hash pandas / numpy objects
"""
from __future__ import annotations
import itertools
from typing import TYPE_CHECKING
import numpy as np
from pandas._libs.hashing import hash_object_array
from pandas.core.dtypes.common import is_list_like
from pandas.core.dtypes.dtypes import CategoricalDtype
from pandas.co... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/util/numba_.py | """Common utilities for Numba operations"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Callable,
)
from pandas.compat._optional import import_optional_dependency
from pandas.errors import NumbaUtilError
GLOBAL_USE_NUMBA: bool = False
def maybe_use_numba(engine: str | None) -> bo... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/_numba/executor.py | from __future__ import annotations
import functools
from typing import (
TYPE_CHECKING,
Any,
Callable,
)
if TYPE_CHECKING:
from pandas._typing import Scalar
import numpy as np
from pandas.compat._optional import import_optional_dependency
@functools.cache
def generate_apply_looper(func, nopython=T... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/_numba/extensions.py | # Disable type checking for this module since numba's internals
# are not typed, and we use numba's internals via its extension API
# mypy: ignore-errors
"""
Utility classes/functions to let numba recognize
pandas Index/Series/DataFrame
Mostly vendored from https://github.com/numba/numba/blob/main/numba/tests/pdlike_u... | 0 |
public_repos/pandas/pandas/core/_numba | public_repos/pandas/pandas/core/_numba/kernels/min_max_.py | """
Numba 1D min/max kernels that can be shared by
* Dataframe / Series
* groupby
* rolling / expanding
Mirrors pandas/_libs/window/aggregation.pyx
"""
from __future__ import annotations
from typing import TYPE_CHECKING
import numba
import numpy as np
if TYPE_CHECKING:
from pandas._typing import npt
@numba.ji... | 0 |
public_repos/pandas/pandas/core/_numba | public_repos/pandas/pandas/core/_numba/kernels/var_.py | """
Numba 1D var kernels that can be shared by
* Dataframe / Series
* groupby
* rolling / expanding
Mirrors pandas/_libs/window/aggregation.pyx
"""
from __future__ import annotations
from typing import TYPE_CHECKING
import numba
import numpy as np
if TYPE_CHECKING:
from pandas._typing import npt
from pandas.co... | 0 |
public_repos/pandas/pandas/core/_numba | public_repos/pandas/pandas/core/_numba/kernels/sum_.py | """
Numba 1D sum kernels that can be shared by
* Dataframe / Series
* groupby
* rolling / expanding
Mirrors pandas/_libs/window/aggregation.pyx
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
)
import numba
from numba.extending import register_jitable
import numpy as np
if TY... | 0 |
public_repos/pandas/pandas/core/_numba | public_repos/pandas/pandas/core/_numba/kernels/mean_.py | """
Numba 1D mean kernels that can be shared by
* Dataframe / Series
* groupby
* rolling / expanding
Mirrors pandas/_libs/window/aggregation.pyx
"""
from __future__ import annotations
from typing import TYPE_CHECKING
import numba
import numpy as np
from pandas.core._numba.kernels.shared import is_monotonic_increasi... | 0 |
public_repos/pandas/pandas/core/_numba | public_repos/pandas/pandas/core/_numba/kernels/shared.py | from __future__ import annotations
from typing import TYPE_CHECKING
import numba
if TYPE_CHECKING:
import numpy as np
@numba.jit(
# error: Any? not callable
numba.boolean(numba.int64[:]), # type: ignore[misc]
nopython=True,
nogil=True,
parallel=False,
)
def is_monotonic_increasing(bounds: ... | 0 |
public_repos/pandas/pandas/core/_numba | public_repos/pandas/pandas/core/_numba/kernels/__init__.py | from pandas.core._numba.kernels.mean_ import (
grouped_mean,
sliding_mean,
)
from pandas.core._numba.kernels.min_max_ import (
grouped_min_max,
sliding_min_max,
)
from pandas.core._numba.kernels.sum_ import (
grouped_sum,
sliding_sum,
)
from pandas.core._numba.kernels.var_ import (
grouped_v... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/array_algos/putmask.py | """
EA-compatible analogue to np.putmask
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
)
import numpy as np
from pandas._libs import lib
from pandas.core.dtypes.cast import infer_dtype_from
from pandas.core.dtypes.common import is_list_like
from pandas.core.arrays import E... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/array_algos/transforms.py | """
transforms.py is for shape-preserving functions.
"""
from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
if TYPE_CHECKING:
from pandas._typing import (
AxisInt,
Scalar,
)
def shift(
values: np.ndarray, periods: int, axis: AxisInt, fill_value: Scal... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/array_algos/quantile.py | from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from pandas.core.dtypes.missing import (
isna,
na_value_for_dtype,
)
if TYPE_CHECKING:
from pandas._typing import (
ArrayLike,
Scalar,
npt,
)
def quantile_compat(
values: ArrayLike, q... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/array_algos/masked_reductions.py | """
masked_reductions.py is for reduction algorithms using a mask-based approach
for missing values.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Callable,
)
import warnings
import numpy as np
from pandas._libs import missing as libmissing
from pandas.core.nanops import check_b... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/array_algos/datetimelike_accumulations.py | """
datetimelke_accumulations.py is for accumulations of datetimelike extension arrays
"""
from __future__ import annotations
from typing import Callable
import numpy as np
from pandas._libs import iNaT
from pandas.core.dtypes.missing import isna
def _cum_func(
func: Callable,
values: np.ndarray,
*,
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/array_algos/masked_accumulations.py | """
masked_accumulations.py is for accumulation algorithms using a mask-based approach
for missing values.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Callable,
)
import numpy as np
if TYPE_CHECKING:
from pandas._typing import npt
def _cum_func(
func: Callable,
v... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/array_algos/replace.py | """
Methods used by Block.replace and related methods.
"""
from __future__ import annotations
import operator
import re
from re import Pattern
from typing import (
TYPE_CHECKING,
Any,
)
import numpy as np
from pandas.core.dtypes.common import (
is_bool,
is_re,
is_re_compilable,
)
from pandas.core... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/array_algos/take.py | from __future__ import annotations
import functools
from typing import (
TYPE_CHECKING,
cast,
overload,
)
import numpy as np
from pandas._libs import (
algos as libalgos,
lib,
)
from pandas.core.dtypes.cast import maybe_promote
from pandas.core.dtypes.common import (
ensure_platform_int,
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/array_algos/__init__.py | """
core.array_algos is for algorithms that operate on ndarray and ExtensionArray.
These should:
- Assume that any Index, Series, or DataFrame objects have already been unwrapped.
- Assume that any list arguments have already been cast to ndarray/EA.
- Not depend on Index, Series, or DataFrame, nor import any of these... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/sparse/api.py | from pandas.core.dtypes.dtypes import SparseDtype
from pandas.core.arrays.sparse import SparseArray
__all__ = ["SparseArray", "SparseDtype"]
| 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/ops/mask_ops.py | """
Ops for masked arrays.
"""
from __future__ import annotations
import numpy as np
from pandas._libs import (
lib,
missing as libmissing,
)
def kleene_or(
left: bool | np.ndarray | libmissing.NAType,
right: bool | np.ndarray | libmissing.NAType,
left_mask: np.ndarray | None,
right_mask: np... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/ops/array_ops.py | """
Functions for arithmetic and comparison operations on NumPy arrays and
ExtensionArrays.
"""
from __future__ import annotations
import datetime
from functools import partial
import operator
from typing import (
TYPE_CHECKING,
Any,
)
import warnings
import numpy as np
from pandas._libs import (
NaT,
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/ops/common.py | """
Boilerplate functions used in defining binary operations.
"""
from __future__ import annotations
from functools import wraps
from typing import (
TYPE_CHECKING,
Callable,
)
from pandas._libs.lib import item_from_zerodim
from pandas._libs.missing import is_matching_na
from pandas.core.dtypes.generic impor... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/ops/invalid.py | """
Templates for invalid operations.
"""
from __future__ import annotations
import operator
from typing import TYPE_CHECKING
import numpy as np
if TYPE_CHECKING:
from pandas._typing import npt
def invalid_comparison(left, right, op) -> npt.NDArray[np.bool_]:
"""
If a comparison has mismatched types an... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/ops/docstrings.py | """
Templating for ops docstrings
"""
from __future__ import annotations
def make_flex_doc(op_name: str, typ: str) -> str:
"""
Make the appropriate substitutions for the given operation and class-typ
into either _flex_doc_SERIES or _flex_doc_FRAME to return the docstring
to attach to a generated metho... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/ops/dispatch.py | """
Functions for defining unary operations.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
)
from pandas.core.dtypes.generic import ABCExtensionArray
if TYPE_CHECKING:
from pandas._typing import ArrayLike
def should_extension_dispatch(left: ArrayLike, right: Any) -> bo... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/ops/missing.py | """
Missing data handling for arithmetic operations.
In particular, pandas conventions regarding division by zero differ
from numpy in the following ways:
1) np.array([-1, 0, 1], dtype=dtype1) // np.array([0, 0, 0], dtype=dtype2)
gives [nan, nan, nan] for most dtype combinations, and [0, 0, 0] for
th... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/ops/__init__.py | """
Arithmetic operations for PandasObjects
This is not a public API.
"""
from __future__ import annotations
from pandas.core.ops.array_ops import (
arithmetic_op,
comp_method_OBJECT_ARRAY,
comparison_op,
fill_binop,
get_array_op,
logical_op,
maybe_prepare_scalar_for_op,
)
from pandas.core... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/reshape/encoding.py | from __future__ import annotations
from collections import defaultdict
from collections.abc import (
Hashable,
Iterable,
)
import itertools
from typing import (
TYPE_CHECKING,
cast,
)
import numpy as np
from pandas._libs.sparse import IntIndex
from pandas.core.dtypes.common import (
is_integer_d... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/reshape/tile.py | """
Quantilization functions and related stuff
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
Callable,
Literal,
)
import numpy as np
from pandas._libs import (
Timedelta,
Timestamp,
lib,
)
from pandas.core.dtypes.common import (
ensure_platform_int,
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/reshape/merge.py | """
SQL-style merge routines
"""
from __future__ import annotations
from collections.abc import (
Hashable,
Sequence,
)
import datetime
from functools import partial
from typing import (
TYPE_CHECKING,
Literal,
cast,
final,
)
import uuid
import warnings
import numpy as np
from pandas._libs im... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/reshape/reshape.py | from __future__ import annotations
import itertools
from typing import (
TYPE_CHECKING,
cast,
)
import warnings
import numpy as np
import pandas._libs.reshape as libreshape
from pandas.errors import PerformanceWarning
from pandas.util._decorators import cache_readonly
from pandas.util._exceptions import find... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/reshape/melt.py | from __future__ import annotations
import re
from typing import TYPE_CHECKING
import numpy as np
from pandas.util._decorators import Appender
from pandas.core.dtypes.common import is_list_like
from pandas.core.dtypes.concat import concat_compat
from pandas.core.dtypes.missing import notna
import pandas.core.algori... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/reshape/api.py | from pandas.core.reshape.concat import concat
from pandas.core.reshape.encoding import (
from_dummies,
get_dummies,
)
from pandas.core.reshape.melt import (
lreshape,
melt,
wide_to_long,
)
from pandas.core.reshape.merge import (
merge,
merge_asof,
merge_ordered,
)
from pandas.core.reshap... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/reshape/util.py | from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from pandas.core.dtypes.common import is_list_like
if TYPE_CHECKING:
from pandas._typing import NumpyIndexT
def cartesian_product(X) -> list[np.ndarray]:
"""
Numpy version of itertools.product.
Sometimes faster ... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/reshape/pivot.py | from __future__ import annotations
from collections.abc import (
Hashable,
Sequence,
)
from typing import (
TYPE_CHECKING,
Callable,
Literal,
cast,
)
import numpy as np
from pandas._libs import lib
from pandas.util._decorators import (
Appender,
Substitution,
)
from pandas.core.dtype... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/reshape/concat.py | """
Concat routines.
"""
from __future__ import annotations
from collections import abc
from typing import (
TYPE_CHECKING,
Callable,
Literal,
cast,
overload,
)
import warnings
import numpy as np
from pandas._config import using_copy_on_write
from pandas.util._decorators import cache_readonly
fr... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/methods/selectn.py | """
Implementation of nlargest and nsmallest.
"""
from __future__ import annotations
from collections.abc import (
Hashable,
Sequence,
)
from typing import (
TYPE_CHECKING,
cast,
final,
)
import numpy as np
from pandas._libs import algos as libalgos
from pandas.core.dtypes.common import (
i... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/methods/describe.py | """
Module responsible for execution of NDFrame.describe() method.
Method NDFrame.describe() delegates actual execution to function describe_ndframe().
"""
from __future__ import annotations
from abc import (
ABC,
abstractmethod,
)
from typing import (
TYPE_CHECKING,
Callable,
cast,
)
import nump... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/methods/to_dict.py | from __future__ import annotations
from typing import (
TYPE_CHECKING,
Literal,
overload,
)
import warnings
import numpy as np
from pandas.util._exceptions import find_stack_level
from pandas.core.dtypes.cast import maybe_box_native
from pandas.core.dtypes.dtypes import ExtensionDtype
from pandas.core ... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/plotting/_misc.py | from __future__ import annotations
from contextlib import contextmanager
from typing import (
TYPE_CHECKING,
Any,
)
from pandas.plotting._core import _get_plot_backend
if TYPE_CHECKING:
from collections.abc import (
Generator,
Mapping,
)
from matplotlib.axes import Axes
from ... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/plotting/_core.py | from __future__ import annotations
import importlib
from typing import (
TYPE_CHECKING,
Callable,
Literal,
)
from pandas._config import get_option
from pandas.util._decorators import (
Appender,
Substitution,
)
from pandas.core.dtypes.common import (
is_integer,
is_list_like,
)
from pand... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/plotting/__init__.py | """
Plotting public API.
Authors of third-party plotting backends should implement a module with a
public ``plot(data, kind, **kwargs)``. The parameter `data` will contain
the data structure and can be a `Series` or a `DataFrame`. For example,
for ``df.plot()`` the parameter `data` will contain the DataFrame `df`.
In ... | 0 |
public_repos/pandas/pandas/plotting | public_repos/pandas/pandas/plotting/_matplotlib/misc.py | from __future__ import annotations
import random
from typing import TYPE_CHECKING
from matplotlib import patches
import matplotlib.lines as mlines
import numpy as np
from pandas.core.dtypes.missing import notna
from pandas.io.formats.printing import pprint_thing
from pandas.plotting._matplotlib.style import get_sta... | 0 |
public_repos/pandas/pandas/plotting | public_repos/pandas/pandas/plotting/_matplotlib/core.py | from __future__ import annotations
from abc import (
ABC,
abstractmethod,
)
from collections.abc import (
Hashable,
Iterable,
Iterator,
Sequence,
)
from typing import (
TYPE_CHECKING,
Any,
Literal,
cast,
final,
)
import warnings
import matplotlib as mpl
import numpy as np
... | 0 |
public_repos/pandas/pandas/plotting | public_repos/pandas/pandas/plotting/_matplotlib/groupby.py | from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from pandas.core.dtypes.missing import remove_na_arraylike
from pandas import (
DataFrame,
MultiIndex,
Series,
concat,
)
from pandas.plotting._matplotlib.misc import unpack_single_str_list
if TYPE_CHECKING:
... | 0 |
public_repos/pandas/pandas/plotting | public_repos/pandas/pandas/plotting/_matplotlib/style.py | from __future__ import annotations
from collections.abc import (
Collection,
Iterator,
)
import itertools
from typing import (
TYPE_CHECKING,
cast,
)
import warnings
import matplotlib as mpl
import matplotlib.colors
import numpy as np
from pandas._typing import MatplotlibColor as Color
from pandas.ut... | 0 |
public_repos/pandas/pandas/plotting | public_repos/pandas/pandas/plotting/_matplotlib/timeseries.py | # TODO: Use the fact that axis can have units to simplify the process
from __future__ import annotations
import functools
from typing import (
TYPE_CHECKING,
Any,
cast,
)
import warnings
import numpy as np
from pandas._libs.tslibs import (
BaseOffset,
Period,
to_offset,
)
from pandas._libs.t... | 0 |
public_repos/pandas/pandas/plotting | public_repos/pandas/pandas/plotting/_matplotlib/hist.py | from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
Literal,
final,
)
import numpy as np
from pandas.core.dtypes.common import (
is_integer,
is_list_like,
)
from pandas.core.dtypes.generic import (
ABCDataFrame,
ABCIndex,
)
from pandas.core.dtypes.missing impor... | 0 |
public_repos/pandas/pandas/plotting | public_repos/pandas/pandas/plotting/_matplotlib/converter.py | from __future__ import annotations
import contextlib
import datetime as pydt
from datetime import (
datetime,
timedelta,
tzinfo,
)
import functools
from typing import (
TYPE_CHECKING,
Any,
cast,
)
import warnings
import matplotlib.dates as mdates
from matplotlib.ticker import (
AutoLocator... | 0 |
public_repos/pandas/pandas/plotting | public_repos/pandas/pandas/plotting/_matplotlib/boxplot.py | from __future__ import annotations
from typing import (
TYPE_CHECKING,
Literal,
NamedTuple,
)
import warnings
from matplotlib.artist import setp
import numpy as np
from pandas._libs import lib
from pandas.util._decorators import cache_readonly
from pandas.util._exceptions import find_stack_level
from pa... | 0 |
public_repos/pandas/pandas/plotting | public_repos/pandas/pandas/plotting/_matplotlib/__init__.py | from __future__ import annotations
from typing import TYPE_CHECKING
from pandas.plotting._matplotlib.boxplot import (
BoxPlot,
boxplot,
boxplot_frame,
boxplot_frame_groupby,
)
from pandas.plotting._matplotlib.converter import (
deregister,
register,
)
from pandas.plotting._matplotlib.core impo... | 0 |
public_repos/pandas/pandas/plotting | public_repos/pandas/pandas/plotting/_matplotlib/tools.py | # being a bit too dynamic
from __future__ import annotations
from math import ceil
from typing import TYPE_CHECKING
import warnings
from matplotlib import ticker
import matplotlib.table
import numpy as np
from pandas.util._exceptions import find_stack_level
from pandas.core.dtypes.common import is_list_like
from pa... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tseries/frequencies.py | from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from pandas._libs import lib
from pandas._libs.algos import unique_deltas
from pandas._libs.tslibs import (
Timestamp,
get_unit_from_dtype,
periods_per_day,
tz_convert_from_utc,
)
from pandas._libs.tslibs.ccalendar... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tseries/api.py | """
Timeseries API
"""
from pandas._libs.tslibs.parsing import guess_datetime_format
from pandas.tseries import offsets
from pandas.tseries.frequencies import infer_freq
__all__ = ["infer_freq", "offsets", "guess_datetime_format"]
| 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tseries/holiday.py | from __future__ import annotations
from datetime import (
datetime,
timedelta,
)
import warnings
from dateutil.relativedelta import (
FR,
MO,
SA,
SU,
TH,
TU,
WE,
)
import numpy as np
from pandas.errors import PerformanceWarning
from pandas import (
DateOffset,
DatetimeInd... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tseries/offsets.py | from __future__ import annotations
from pandas._libs.tslibs.offsets import (
FY5253,
BaseOffset,
BDay,
BMonthBegin,
BMonthEnd,
BQuarterBegin,
BQuarterEnd,
BusinessDay,
BusinessHour,
BusinessMonthBegin,
BusinessMonthEnd,
BYearBegin,
BYearEnd,
CBMonthBegin,
CBM... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tseries/__init__.py | # ruff: noqa: TCH004
from typing import TYPE_CHECKING
if TYPE_CHECKING:
# import modules that have public classes/functions:
from pandas.tseries import (
frequencies,
offsets,
)
# and mark only those modules as public
__all__ = ["frequencies", "offsets"]
| 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_config/localization.py | """
Helpers for configuring locale settings.
Name `localization` is chosen to avoid overlap with builtin `locale` module.
"""
from __future__ import annotations
from contextlib import contextmanager
import locale
import platform
import re
import subprocess
from typing import TYPE_CHECKING
from pandas._config.config ... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_config/config.py | """
The config module holds package-wide configurables and provides
a uniform API for working with them.
Overview
========
This module supports the following requirements:
- options are referenced using keys in dot.notation, e.g. "x.y.option - z".
- keys are case-insensitive.
- functions should accept partial/regex k... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_config/display.py | """
Unopinionated display configuration.
"""
from __future__ import annotations
import locale
import sys
from pandas._config import config as cf
# -----------------------------------------------------------------------------
# Global formatting options
_initial_defencoding: str | None = None
def detect_console_en... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_config/dates.py | """
config for datetime formatting
"""
from __future__ import annotations
from pandas._config import config as cf
pc_date_dayfirst_doc = """
: boolean
When True, prints and parses dates with the day first, eg 20/01/2005
"""
pc_date_yearfirst_doc = """
: boolean
When True, prints and parses dates with the yea... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_config/__init__.py | """
pandas._config is considered explicitly upstream of everything else in pandas,
should have no intra-pandas dependencies.
importing `dates` and `display` ensures that keys needed by _libs
are initialized.
"""
__all__ = [
"config",
"detect_console_encoding",
"get_option",
"set_option",
"reset_opt... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_testing/asserters.py | from __future__ import annotations
import operator
from typing import (
TYPE_CHECKING,
Literal,
cast,
)
import numpy as np
from pandas._libs.missing import is_matching_na
from pandas._libs.sparse import SparseIndex
import pandas._libs.testing as _testing
from pandas._libs.tslibs.np_datetime import compar... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_testing/_hypothesis.py | """
Hypothesis data generator helpers.
"""
from datetime import datetime
from hypothesis import strategies as st
from hypothesis.extra.dateutil import timezones as dateutil_timezones
from hypothesis.extra.pytz import timezones as pytz_timezones
from pandas.compat import is_platform_windows
import pandas as pd
from ... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_testing/contexts.py | from __future__ import annotations
from contextlib import contextmanager
import os
from pathlib import Path
import tempfile
from typing import (
IO,
TYPE_CHECKING,
Any,
)
import uuid
from pandas.compat import PYPY
from pandas.errors import ChainedAssignmentError
from pandas import set_option
from pandas... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_testing/_io.py | from __future__ import annotations
import gzip
import io
import pathlib
import tarfile
from typing import (
TYPE_CHECKING,
Any,
Callable,
)
import uuid
import zipfile
from pandas.compat import (
get_bz2_file,
get_lzma_file,
)
from pandas.compat._optional import import_optional_dependency
import p... | 0 |
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