Search is not available for this dataset
repo_id stringlengths 12 110 | file_path stringlengths 24 164 | content stringlengths 3 89.3M | __index_level_0__ int64 0 0 |
|---|---|---|---|
public_repos/pandas | public_repos/pandas/pandas/meson.build | incdir_numpy = run_command(py,
[
'-c',
'''
import os
import numpy as np
try:
# Check if include directory is inside the pandas dir
# e.g. a venv created inside the pandas dir
# If so, convert it to a relative path
incdir = os.path.relpath(np.get_include())
except Exception:
incdir = np.get... | 0 |
public_repos/pandas | public_repos/pandas/pandas/conftest.py | """
This file is very long and growing, but it was decided to not split it yet, as
it's still manageable (2020-03-17, ~1.1k LoC). See gh-31989
Instead of splitting it was decided to define sections here:
- Configuration / Settings
- Autouse fixtures
- Common arguments
- Missing values & co.
- Classes
- Indices
- Serie... | 0 |
public_repos/pandas | public_repos/pandas/pandas/_version.py | # This file helps to compute a version number in source trees obtained from
# git-archive tarball (such as those provided by githubs download-from-tag
# feature). Distribution tarballs (built by setup.py sdist) and build
# directories (produced by setup.py build) will contain a much shorter file
# that just contains th... | 0 |
public_repos/pandas | public_repos/pandas/pandas/_typing.py | from __future__ import annotations
from collections.abc import (
Hashable,
Iterator,
Mapping,
MutableMapping,
Sequence,
)
from datetime import (
date,
datetime,
timedelta,
tzinfo,
)
from os import PathLike
import sys
from typing import (
TYPE_CHECKING,
Any,
Callable,
... | 0 |
public_repos/pandas | public_repos/pandas/pandas/testing.py | """
Public testing utility functions.
"""
from pandas._testing import (
assert_extension_array_equal,
assert_frame_equal,
assert_index_equal,
assert_series_equal,
)
__all__ = [
"assert_extension_array_equal",
"assert_frame_equal",
"assert_series_equal",
"assert_index_equal",
]
| 0 |
public_repos/pandas | public_repos/pandas/pandas/__init__.py | from __future__ import annotations
import os
import warnings
__docformat__ = "restructuredtext"
# Let users know if they're missing any of our hard dependencies
_hard_dependencies = ("numpy", "pytz", "dateutil")
_missing_dependencies = []
for _dependency in _hard_dependencies:
try:
__import__(_dependenc... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/construction.py | """
Constructor functions intended to be shared by pd.array, Series.__init__,
and Index.__new__.
These should not depend on core.internals.
"""
from __future__ import annotations
from collections.abc import Sequence
from typing import (
TYPE_CHECKING,
Optional,
Union,
cast,
overload,
)
import warn... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/sorting.py | """ miscellaneous sorting / groupby utilities """
from __future__ import annotations
from collections import defaultdict
from typing import (
TYPE_CHECKING,
Callable,
DefaultDict,
cast,
)
import numpy as np
from pandas._libs import (
algos,
hashtable,
lib,
)
from pandas._libs.hashtable im... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/flags.py | from __future__ import annotations
from typing import TYPE_CHECKING
import weakref
if TYPE_CHECKING:
from pandas.core.generic import NDFrame
class Flags:
"""
Flags that apply to pandas objects.
.. versionadded:: 1.2.0
Parameters
----------
obj : Series or DataFrame
The object t... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/config_init.py | """
This module is imported from the pandas package __init__.py file
in order to ensure that the core.config options registered here will
be available as soon as the user loads the package. if register_option
is invoked inside specific modules, they will not be registered until that
module is imported, which may or may... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/accessor.py | """
accessor.py contains base classes for implementing accessor properties
that can be mixed into or pinned onto other pandas classes.
"""
from __future__ import annotations
from typing import (
Callable,
final,
)
import warnings
from pandas.util._decorators import doc
from pandas.util._exceptions import fi... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/common.py | """
Misc tools for implementing data structures
Note: pandas.core.common is *not* part of the public API.
"""
from __future__ import annotations
import builtins
from collections import (
abc,
defaultdict,
)
from collections.abc import (
Collection,
Generator,
Hashable,
Iterable,
Sequence,
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/indexing.py | from __future__ import annotations
from contextlib import suppress
import sys
from typing import (
TYPE_CHECKING,
Any,
TypeVar,
cast,
final,
)
import warnings
import numpy as np
from pandas._config import using_copy_on_write
from pandas._libs.indexing import NDFrameIndexerBase
from pandas._libs.... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/base.py | """
Base and utility classes for pandas objects.
"""
from __future__ import annotations
import textwrap
from typing import (
TYPE_CHECKING,
Any,
Generic,
Literal,
cast,
final,
overload,
)
import warnings
import numpy as np
from pandas._config import using_copy_on_write
from pandas._libs... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/resample.py | from __future__ import annotations
import copy
from textwrap import dedent
from typing import (
TYPE_CHECKING,
Callable,
Literal,
cast,
final,
no_type_check,
)
import warnings
import numpy as np
from pandas._libs import lib
from pandas._libs.tslibs import (
BaseOffset,
IncompatibleFre... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/algorithms.py | """
Generic data algorithms. This module is experimental at the moment and not
intended for public consumption
"""
from __future__ import annotations
import operator
from textwrap import dedent
from typing import (
TYPE_CHECKING,
Literal,
cast,
)
import warnings
import numpy as np
from pandas._libs impor... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/apply.py | from __future__ import annotations
import abc
from collections import defaultdict
import functools
from functools import partial
import inspect
from typing import (
TYPE_CHECKING,
Any,
Callable,
DefaultDict,
Literal,
cast,
)
import warnings
import numpy as np
from pandas._config import option... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/frame.py | """
DataFrame
---------
An efficient 2D container for potentially mixed-type time series or other
labeled data series.
Similar to its R counterpart, data.frame, except providing automatic data
alignment and a host of useful data manipulation methods having to do with the
labeling information
"""
from __future__ import... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/nanops.py | from __future__ import annotations
import functools
import itertools
from typing import (
Any,
Callable,
cast,
)
import warnings
import numpy as np
from pandas._config import get_option
from pandas._libs import (
NaT,
NaTType,
iNaT,
lib,
)
from pandas._typing import (
ArrayLike,
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/generic.py | # pyright: reportPropertyTypeMismatch=false
from __future__ import annotations
import collections
from copy import deepcopy
import datetime as dt
from functools import partial
import gc
from json import loads
import operator
import pickle
import re
import sys
from typing import (
TYPE_CHECKING,
Any,
Callab... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/roperator.py | """
Reversed Operations not available in the stdlib operator module.
Defining these instead of using lambdas allows us to reference them by name.
"""
from __future__ import annotations
import operator
def radd(left, right):
return right + left
def rsub(left, right):
return right - left
def rmul(left, rig... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/api.py | from pandas._libs import (
NaT,
Period,
Timedelta,
Timestamp,
)
from pandas._libs.missing import NA
from pandas.core.dtypes.dtypes import (
ArrowDtype,
CategoricalDtype,
DatetimeTZDtype,
IntervalDtype,
PeriodDtype,
)
from pandas.core.dtypes.missing import (
isna,
isnull,
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/series.py | """
Data structure for 1-dimensional cross-sectional and time series data
"""
from __future__ import annotations
from collections.abc import (
Hashable,
Iterable,
Mapping,
Sequence,
)
import operator
import sys
from textwrap import dedent
from typing import (
IO,
TYPE_CHECKING,
Any,
Cal... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/shared_docs.py | from __future__ import annotations
_shared_docs: dict[str, str] = {}
_shared_docs[
"aggregate"
] = """
Aggregate using one or more operations over the specified axis.
Parameters
----------
func : function, str, list or dict
Function to use for aggregating the data. If a function, must either
work when pa... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/sample.py | """
Module containing utilities for NDFrame.sample() and .GroupBy.sample()
"""
from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from pandas._libs import lib
from pandas.core.dtypes.generic import (
ABCDataFrame,
ABCSeries,
)
if TYPE_CHECKING:
from pandas._typing im... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/missing.py | """
Routines for filling missing data.
"""
from __future__ import annotations
from functools import (
partial,
wraps,
)
from typing import (
TYPE_CHECKING,
Any,
Literal,
cast,
overload,
)
import numpy as np
from pandas._libs import (
NaT,
algos,
lib,
)
from pandas._typing impo... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/core/arraylike.py | """
Methods that can be shared by many array-like classes or subclasses:
Series
Index
ExtensionArray
"""
from __future__ import annotations
import operator
from typing import Any
import numpy as np
from pandas._libs import lib
from pandas._libs.ops_dispatch import maybe_dispatch_ufunc_to_dunder_op
from ... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/window/online.py | from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from pandas.compat._optional import import_optional_dependency
def generate_online_numba_ewma_func(
nopython: bool,
nogil: bool,
parallel: bool,
):
"""
Generate a numba jitted groupby ewma function specified ... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/window/ewm.py | from __future__ import annotations
import datetime
from functools import partial
from textwrap import dedent
from typing import TYPE_CHECKING
import numpy as np
from pandas._libs.tslibs import Timedelta
import pandas._libs.window.aggregations as window_aggregations
from pandas.util._decorators import doc
from panda... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/window/rolling.py | """
Provide a generic structure to support window functions,
similar to how we have a Groupby object.
"""
from __future__ import annotations
import copy
from datetime import timedelta
from functools import partial
import inspect
from textwrap import dedent
from typing import (
TYPE_CHECKING,
Any,
Callable,... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/window/expanding.py | from __future__ import annotations
from textwrap import dedent
from typing import (
TYPE_CHECKING,
Any,
Callable,
Literal,
)
from pandas.util._decorators import (
deprecate_kwarg,
doc,
)
from pandas.core.indexers.objects import (
BaseIndexer,
ExpandingIndexer,
GroupbyIndexer,
)
fr... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/window/common.py | """Common utility functions for rolling operations"""
from __future__ import annotations
from collections import defaultdict
from typing import cast
import numpy as np
from pandas.core.dtypes.generic import (
ABCDataFrame,
ABCSeries,
)
from pandas.core.indexes.api import MultiIndex
def flex_binary_moment(... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/window/doc.py | """Any shareable docstring components for rolling/expanding/ewm"""
from __future__ import annotations
from textwrap import dedent
from pandas.core.shared_docs import _shared_docs
_shared_docs = dict(**_shared_docs)
def create_section_header(header: str) -> str:
"""Create numpydoc section header"""
return f... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/window/numba_.py | from __future__ import annotations
import functools
from typing import (
TYPE_CHECKING,
Any,
Callable,
)
import numpy as np
from pandas.compat._optional import import_optional_dependency
from pandas.core.util.numba_ import jit_user_function
if TYPE_CHECKING:
from pandas._typing import Scalar
@fun... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/window/__init__.py | from pandas.core.window.ewm import (
ExponentialMovingWindow,
ExponentialMovingWindowGroupby,
)
from pandas.core.window.expanding import (
Expanding,
ExpandingGroupby,
)
from pandas.core.window.rolling import (
Rolling,
RollingGroupby,
Window,
)
__all__ = [
"Expanding",
"ExpandingGr... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/computation/check.py | from __future__ import annotations
from pandas.compat._optional import import_optional_dependency
ne = import_optional_dependency("numexpr", errors="warn")
NUMEXPR_INSTALLED = ne is not None
__all__ = ["NUMEXPR_INSTALLED"]
| 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/computation/expressions.py | """
Expressions
-----------
Offer fast expression evaluation through numexpr
"""
from __future__ import annotations
import operator
from typing import TYPE_CHECKING
import warnings
import numpy as np
from pandas._config import get_option
from pandas.util._exceptions import find_stack_level
from pandas.core impor... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/computation/parsing.py | """
:func:`~pandas.eval` source string parsing functions
"""
from __future__ import annotations
from io import StringIO
from keyword import iskeyword
import token
import tokenize
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from collections.abc import (
Hashable,
Iterator,
)
# A token v... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/computation/ops.py | """
Operator classes for eval.
"""
from __future__ import annotations
from datetime import datetime
from functools import partial
import operator
from typing import (
TYPE_CHECKING,
Callable,
Literal,
)
import numpy as np
from pandas._libs.tslibs import Timestamp
from pandas.core.dtypes.common import (... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/computation/scope.py | """
Module for scope operations
"""
from __future__ import annotations
from collections import ChainMap
import datetime
import inspect
from io import StringIO
import itertools
import pprint
import struct
import sys
from typing import TypeVar
import numpy as np
from pandas._libs.tslibs import Timestamp
from pandas.er... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/computation/common.py | from __future__ import annotations
from functools import reduce
import numpy as np
from pandas._config import get_option
def ensure_decoded(s) -> str:
"""
If we have bytes, decode them to unicode.
"""
if isinstance(s, (np.bytes_, bytes)):
s = s.decode(get_option("display.encoding"))
ret... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/computation/expr.py | """
:func:`~pandas.eval` parsers.
"""
from __future__ import annotations
import ast
from functools import (
partial,
reduce,
)
from keyword import iskeyword
import tokenize
from typing import (
Callable,
ClassVar,
TypeVar,
)
import numpy as np
from pandas.errors import UndefinedVariableError
imp... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/computation/eval.py | """
Top level ``eval`` module.
"""
from __future__ import annotations
import tokenize
from typing import TYPE_CHECKING
import warnings
from pandas.util._exceptions import find_stack_level
from pandas.util._validators import validate_bool_kwarg
from pandas.core.dtypes.common import is_extension_array_dtype
from pand... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/computation/align.py | """
Core eval alignment algorithms.
"""
from __future__ import annotations
from functools import (
partial,
wraps,
)
from typing import (
TYPE_CHECKING,
Callable,
)
import warnings
import numpy as np
from pandas.errors import PerformanceWarning
from pandas.util._exceptions import find_stack_level
fr... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/computation/pytables.py | """ manage PyTables query interface via Expressions """
from __future__ import annotations
import ast
from decimal import (
Decimal,
InvalidOperation,
)
from functools import partial
from typing import (
TYPE_CHECKING,
Any,
ClassVar,
)
import numpy as np
from pandas._libs.tslibs import (
Time... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/computation/api.py | __all__ = ["eval"]
from pandas.core.computation.eval import eval
| 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/computation/engines.py | """
Engine classes for :func:`~pandas.eval`
"""
from __future__ import annotations
import abc
from typing import TYPE_CHECKING
from pandas.errors import NumExprClobberingError
from pandas.core.computation.align import (
align_terms,
reconstruct_object,
)
from pandas.core.computation.ops import (
MATHOPS,... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexers/objects.py | """Indexer objects for computing start/end window bounds for rolling operations"""
from __future__ import annotations
from datetime import timedelta
import numpy as np
from pandas._libs.tslibs import BaseOffset
from pandas._libs.window.indexers import calculate_variable_window_bounds
from pandas.util._decorators imp... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexers/utils.py | """
Low-dependency indexing utilities.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
)
import numpy as np
from pandas._libs import lib
from pandas.core.dtypes.common import (
is_array_like,
is_bool_dtype,
is_integer,
is_integer_dtype,
is_list_like,
)
fro... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/indexers/__init__.py | from pandas.core.indexers.utils import (
check_array_indexer,
check_key_length,
check_setitem_lengths,
disallow_ndim_indexing,
is_empty_indexer,
is_list_like_indexer,
is_scalar_indexer,
is_valid_positional_slice,
length_of_indexer,
maybe_convert_indices,
unpack_1tuple,
un... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/tools/times.py | from __future__ import annotations
from datetime import (
datetime,
time,
)
from typing import TYPE_CHECKING
import warnings
import numpy as np
from pandas._libs.lib import is_list_like
from pandas.util._exceptions import find_stack_level
from pandas.core.dtypes.generic import (
ABCIndex,
ABCSeries,... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/tools/timedeltas.py | """
timedelta support tools
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
overload,
)
import warnings
import numpy as np
from pandas._libs import lib
from pandas._libs.tslibs import (
NaT,
NaTType,
)
from pandas._libs.tslibs.timedeltas import (
Timedelta,
disallow... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/tools/datetimes.py | from __future__ import annotations
from collections import abc
from datetime import date
from functools import partial
from itertools import islice
from typing import (
TYPE_CHECKING,
Callable,
TypedDict,
Union,
cast,
overload,
)
import warnings
import numpy as np
from pandas._libs import (
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/tools/numeric.py | from __future__ import annotations
from typing import (
TYPE_CHECKING,
Literal,
)
import warnings
import numpy as np
from pandas._libs import lib
from pandas.util._exceptions import find_stack_level
from pandas.util._validators import check_dtype_backend
from pandas.core.dtypes.cast import maybe_downcast_nu... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/interchange/dataframe.py | from __future__ import annotations
from collections import abc
from typing import TYPE_CHECKING
from pandas.core.interchange.column import PandasColumn
from pandas.core.interchange.dataframe_protocol import DataFrame as DataFrameXchg
if TYPE_CHECKING:
from collections.abc import (
Iterable,
Seque... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/interchange/column.py | from __future__ import annotations
from typing import Any
import numpy as np
from pandas._libs.lib import infer_dtype
from pandas._libs.tslibs import iNaT
from pandas.errors import NoBufferPresent
from pandas.util._decorators import cache_readonly
from pandas.core.dtypes.dtypes import (
ArrowDtype,
Datetime... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/interchange/utils.py | """
Utility functions and objects for implementing the interchange API.
"""
from __future__ import annotations
import typing
import numpy as np
from pandas._libs import lib
from pandas.core.dtypes.dtypes import (
ArrowDtype,
CategoricalDtype,
DatetimeTZDtype,
)
if typing.TYPE_CHECKING:
from pandas... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/interchange/from_dataframe.py | from __future__ import annotations
import ctypes
import re
from typing import Any
import numpy as np
from pandas.compat._optional import import_optional_dependency
from pandas.errors import SettingWithCopyError
import pandas as pd
from pandas.core.interchange.dataframe_protocol import (
Buffer,
Column,
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/interchange/buffer.py | from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
)
from pandas.core.interchange.dataframe_protocol import (
Buffer,
DlpackDeviceType,
)
if TYPE_CHECKING:
import numpy as np
class PandasBuffer(Buffer):
"""
Data in the buffer is guaranteed to be contiguous in me... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/interchange/dataframe_protocol.py | """
A verbatim copy (vendored) of the spec from https://github.com/data-apis/dataframe-api
"""
from __future__ import annotations
from abc import (
ABC,
abstractmethod,
)
import enum
from typing import (
TYPE_CHECKING,
Any,
TypedDict,
)
if TYPE_CHECKING:
from collections.abc import (
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/groupby/categorical.py | from __future__ import annotations
import numpy as np
from pandas.core.algorithms import unique1d
from pandas.core.arrays.categorical import (
Categorical,
CategoricalDtype,
recode_for_categories,
)
def recode_for_groupby(
c: Categorical, sort: bool, observed: bool
) -> tuple[Categorical, Categorica... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/groupby/ops.py | """
Provide classes to perform the groupby aggregate operations.
These are not exposed to the user and provide implementations of the grouping
operations, primarily in cython. These classes (BaseGrouper and BinGrouper)
are contained *in* the SeriesGroupBy and DataFrameGroupBy objects.
"""
from __future__ import annota... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/groupby/indexing.py | from __future__ import annotations
from collections.abc import Iterable
from typing import (
TYPE_CHECKING,
Literal,
cast,
)
import numpy as np
from pandas.util._decorators import (
cache_readonly,
doc,
)
from pandas.core.dtypes.common import (
is_integer,
is_list_like,
)
if TYPE_CHECKI... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/groupby/base.py | """
Provide basic components for groupby.
"""
from __future__ import annotations
import dataclasses
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from collections.abc import Hashable
@dataclasses.dataclass(order=True, frozen=True)
class OutputKey:
label: Hashable
position: int
# special case to p... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/groupby/groupby.py | """
Provide the groupby split-apply-combine paradigm. Define the GroupBy
class providing the base-class of operations.
The SeriesGroupBy and DataFrameGroupBy sub-class
(defined in pandas.core.groupby.generic)
expose these user-facing objects to provide specific functionality.
"""
from __future__ import annotations
fr... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/groupby/generic.py | """
Define the SeriesGroupBy and DataFrameGroupBy
classes that hold the groupby interfaces (and some implementations).
These are user facing as the result of the ``df.groupby(...)`` operations,
which here returns a DataFrameGroupBy object.
"""
from __future__ import annotations
from collections import abc
from functo... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/groupby/numba_.py | """Common utilities for Numba operations with groupby ops"""
from __future__ import annotations
import functools
import inspect
from typing import (
TYPE_CHECKING,
Any,
Callable,
)
import numpy as np
from pandas.compat._optional import import_optional_dependency
from pandas.core.util.numba_ import (
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/groupby/grouper.py | """
Provide user facing operators for doing the split part of the
split-apply-combine paradigm.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
final,
)
import warnings
import numpy as np
from pandas._config import (
using_copy_on_write,
warn_copy_on_write,
)
from pandas._... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/groupby/__init__.py | from pandas.core.groupby.generic import (
DataFrameGroupBy,
NamedAgg,
SeriesGroupBy,
)
from pandas.core.groupby.groupby import GroupBy
from pandas.core.groupby.grouper import Grouper
__all__ = [
"DataFrameGroupBy",
"NamedAgg",
"SeriesGroupBy",
"GroupBy",
"Grouper",
]
| 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/masked.py | from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
Callable,
Literal,
overload,
)
import warnings
import numpy as np
from pandas._libs import (
lib,
missing as libmissing,
)
from pandas._libs.tslibs import (
get_unit_from_dtype,
is_supported_unit,
)
from p... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/categorical.py | from __future__ import annotations
from csv import QUOTE_NONNUMERIC
from functools import partial
import operator
from shutil import get_terminal_size
from typing import (
TYPE_CHECKING,
Literal,
cast,
overload,
)
import warnings
import numpy as np
from pandas._config import get_option
from pandas._... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/timedeltas.py | from __future__ import annotations
from datetime import timedelta
import operator
from typing import (
TYPE_CHECKING,
cast,
)
import warnings
import numpy as np
from pandas._libs import (
lib,
tslibs,
)
from pandas._libs.tslibs import (
NaT,
NaTType,
Tick,
Timedelta,
astype_overfl... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/boolean.py | from __future__ import annotations
import numbers
from typing import (
TYPE_CHECKING,
ClassVar,
cast,
)
import numpy as np
from pandas._libs import (
lib,
missing as libmissing,
)
from pandas.core.dtypes.common import is_list_like
from pandas.core.dtypes.dtypes import register_extension_dtype
fr... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/period.py | from __future__ import annotations
from datetime import timedelta
import operator
from typing import (
TYPE_CHECKING,
Any,
Callable,
Literal,
TypeVar,
cast,
overload,
)
import warnings
import numpy as np
from pandas._libs import (
algos as libalgos,
lib,
)
from pandas._libs.arrays... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/datetimelike.py | from __future__ import annotations
from datetime import (
datetime,
timedelta,
)
from functools import wraps
import operator
from typing import (
TYPE_CHECKING,
Any,
Callable,
Literal,
Union,
cast,
final,
overload,
)
import warnings
import numpy as np
from pandas._libs import ... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/datetimes.py | from __future__ import annotations
from datetime import (
datetime,
timedelta,
tzinfo,
)
from typing import (
TYPE_CHECKING,
cast,
)
import warnings
import numpy as np
from pandas._libs import (
lib,
tslib,
)
from pandas._libs.tslibs import (
BaseOffset,
NaT,
NaTType,
Reso... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/base.py | """
An interface for extending pandas with custom arrays.
.. warning::
This is an experimental API and subject to breaking changes
without warning.
"""
from __future__ import annotations
import operator
from typing import (
TYPE_CHECKING,
Any,
Callable,
ClassVar,
Literal,
cast,
over... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/interval.py | from __future__ import annotations
import operator
from operator import (
le,
lt,
)
import textwrap
from typing import (
TYPE_CHECKING,
Literal,
Union,
overload,
)
import numpy as np
from pandas._libs import lib
from pandas._libs.interval import (
VALID_CLOSED,
Interval,
IntervalM... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/_arrow_string_mixins.py | from __future__ import annotations
from typing import Literal
import numpy as np
from pandas.compat import pa_version_under10p1
if not pa_version_under10p1:
import pyarrow as pa
import pyarrow.compute as pc
class ArrowStringArrayMixin:
_pa_array = None
def __init__(self, *args, **kwargs) -> None:... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/_ranges.py | """
Helper functions to generate range-like data for DatetimeArray
(and possibly TimedeltaArray/PeriodArray)
"""
from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from pandas._libs.lib import i8max
from pandas._libs.tslibs import (
BaseOffset,
OutOfBoundsDatetime,
Tim... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/integer.py | from __future__ import annotations
from typing import ClassVar
import numpy as np
from pandas.core.dtypes.base import register_extension_dtype
from pandas.core.dtypes.common import is_integer_dtype
from pandas.core.arrays.numeric import (
NumericArray,
NumericDtype,
)
class IntegerDtype(NumericDtype):
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/string_.py | from __future__ import annotations
from typing import (
TYPE_CHECKING,
ClassVar,
Literal,
)
import numpy as np
from pandas._config import get_option
from pandas._libs import (
lib,
missing as libmissing,
)
from pandas._libs.arrays import NDArrayBacked
from pandas._libs.lib import ensure_string_a... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/numpy_.py | from __future__ import annotations
from typing import (
TYPE_CHECKING,
Literal,
)
import numpy as np
from pandas._libs import lib
from pandas._libs.tslibs import (
get_unit_from_dtype,
is_supported_unit,
)
from pandas.compat.numpy import function as nv
from pandas.core.dtypes.astype import astype_ar... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/numeric.py | from __future__ import annotations
import numbers
from typing import (
TYPE_CHECKING,
Any,
Callable,
)
import numpy as np
from pandas._libs import (
lib,
missing as libmissing,
)
from pandas.errors import AbstractMethodError
from pandas.util._decorators import cache_readonly
from pandas.core.dty... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/string_arrow.py | from __future__ import annotations
from functools import partial
import re
from typing import (
TYPE_CHECKING,
Callable,
Union,
)
import warnings
import numpy as np
from pandas._libs import (
lib,
missing as libmissing,
)
from pandas.compat import (
pa_version_under10p1,
pa_version_under1... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/floating.py | from __future__ import annotations
from typing import ClassVar
import numpy as np
from pandas.core.dtypes.base import register_extension_dtype
from pandas.core.dtypes.common import is_float_dtype
from pandas.core.arrays.numeric import (
NumericArray,
NumericDtype,
)
class FloatingDtype(NumericDtype):
... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/_mixins.py | from __future__ import annotations
from functools import wraps
from typing import (
TYPE_CHECKING,
Any,
Literal,
cast,
overload,
)
import numpy as np
from pandas._libs import lib
from pandas._libs.arrays import NDArrayBacked
from pandas._libs.tslibs import (
get_unit_from_dtype,
is_suppor... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/arrays/__init__.py | from pandas.core.arrays.arrow import ArrowExtensionArray
from pandas.core.arrays.base import (
ExtensionArray,
ExtensionOpsMixin,
ExtensionScalarOpsMixin,
)
from pandas.core.arrays.boolean import BooleanArray
from pandas.core.arrays.categorical import Categorical
from pandas.core.arrays.datetimes import Dat... | 0 |
public_repos/pandas/pandas/core/arrays | public_repos/pandas/pandas/core/arrays/arrow/accessors.py | """Accessors for arrow-backed data."""
from __future__ import annotations
from abc import (
ABCMeta,
abstractmethod,
)
from typing import TYPE_CHECKING
from pandas.compat import (
pa_version_under10p1,
pa_version_under11p0,
)
if not pa_version_under10p1:
import pyarrow as pa
import pyarrow.c... | 0 |
public_repos/pandas/pandas/core/arrays | public_repos/pandas/pandas/core/arrays/arrow/array.py | from __future__ import annotations
import operator
import re
import textwrap
from typing import (
TYPE_CHECKING,
Any,
Callable,
Literal,
cast,
)
import unicodedata
import numpy as np
from pandas._libs import lib
from pandas._libs.tslibs import (
Timedelta,
Timestamp,
timezones,
)
from... | 0 |
public_repos/pandas/pandas/core/arrays | public_repos/pandas/pandas/core/arrays/arrow/_arrow_utils.py | from __future__ import annotations
import warnings
import numpy as np
import pyarrow
from pandas.errors import PerformanceWarning
from pandas.util._exceptions import find_stack_level
def fallback_performancewarning(version: str | None = None) -> None:
"""
Raise a PerformanceWarning for falling back to Exte... | 0 |
public_repos/pandas/pandas/core/arrays | public_repos/pandas/pandas/core/arrays/arrow/extension_types.py | from __future__ import annotations
import json
from typing import TYPE_CHECKING
import pyarrow
from pandas.compat import pa_version_under14p1
from pandas.core.dtypes.dtypes import (
IntervalDtype,
PeriodDtype,
)
from pandas.core.arrays.interval import VALID_CLOSED
if TYPE_CHECKING:
from pandas._typing... | 0 |
public_repos/pandas/pandas/core/arrays | public_repos/pandas/pandas/core/arrays/arrow/__init__.py | from pandas.core.arrays.arrow.accessors import (
ListAccessor,
StructAccessor,
)
from pandas.core.arrays.arrow.array import ArrowExtensionArray
__all__ = ["ArrowExtensionArray", "StructAccessor", "ListAccessor"]
| 0 |
public_repos/pandas/pandas/core/arrays | public_repos/pandas/pandas/core/arrays/sparse/array.py | """
SparseArray data structure
"""
from __future__ import annotations
from collections import abc
import numbers
import operator
from typing import (
TYPE_CHECKING,
Any,
Callable,
Literal,
cast,
overload,
)
import warnings
import numpy as np
from pandas._libs import lib
import pandas._libs.sp... | 0 |
public_repos/pandas/pandas/core/arrays | public_repos/pandas/pandas/core/arrays/sparse/accessor.py | """Sparse accessor"""
from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from pandas.compat._optional import import_optional_dependency
from pandas.core.dtypes.cast import find_common_type
from pandas.core.dtypes.dtypes import SparseDtype
from pandas.core.accessor import (
P... | 0 |
public_repos/pandas/pandas/core/arrays | public_repos/pandas/pandas/core/arrays/sparse/scipy_sparse.py | """
Interaction with scipy.sparse matrices.
Currently only includes to_coo helpers.
"""
from __future__ import annotations
from typing import TYPE_CHECKING
from pandas._libs import lib
from pandas.core.dtypes.missing import notna
from pandas.core.algorithms import factorize
from pandas.core.indexes.api import Mult... | 0 |
public_repos/pandas/pandas/core/arrays | public_repos/pandas/pandas/core/arrays/sparse/__init__.py | from pandas.core.arrays.sparse.accessor import (
SparseAccessor,
SparseFrameAccessor,
)
from pandas.core.arrays.sparse.array import (
BlockIndex,
IntIndex,
SparseArray,
make_sparse_index,
)
__all__ = [
"BlockIndex",
"IntIndex",
"make_sparse_index",
"SparseAccessor",
"SparseA... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/dtypes/common.py | """
Common type operations.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
Callable,
)
import warnings
import numpy as np
from pandas._libs import (
Interval,
Period,
algos,
lib,
)
from pandas._libs.tslibs import conversion
from pandas.util._exceptions imp... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/dtypes/base.py | """
Extend pandas with custom array types.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
TypeVar,
cast,
overload,
)
import numpy as np
from pandas._libs import missing as libmissing
from pandas._libs.hashtable import object_hash
from pandas._libs.properties impor... | 0 |
public_repos/pandas/pandas/core | public_repos/pandas/pandas/core/dtypes/generic.py | """ define generic base classes for pandas objects """
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Type,
cast,
)
if TYPE_CHECKING:
from pandas import (
Categorical,
CategoricalIndex,
DataFrame,
DatetimeIndex,
Index,
IntervalInd... | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.