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MarcoGorelliMarcoGorelli
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Add examples (#267)
* remove unused typevars, make dtype type alias * Rename `get_column_names` to `column_names` and make property (#254) * get_column_names -> column_names property * get_column_names -> column_names * add namespace protocol * fixup * add examples * add plotting example * fixup; * redirect examples * type check; * exclude examples from conf.py * post-merge fixup * add other example * fixup example; * noop
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10 files changed

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Diff for: ‎.github/workflows/mypy.yml

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@@ -29,4 +29,4 @@ jobs:
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- name: install-reqs
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run: python -m pip install --upgrade mypy==1.4.0
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- name: run mypy
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run: cd spec/API_specification && mypy dataframe_api
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run: cd spec/API_specification && mypy dataframe_api && mypy examples

Diff for: ‎spec/API_specification/dataframe_api/_types.py

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@@ -3,18 +3,22 @@
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import (
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TYPE_CHECKING,
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Any,
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List,
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Literal,
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Mapping,
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Optional,
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Protocol,
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Sequence,
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Tuple,
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Union,
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TYPE_CHECKING,
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)
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from enum import Enum
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if TYPE_CHECKING:
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from .dataframe_object import DataFrame as DataFrameType
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from .column_object import Column as ColumnType
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if TYPE_CHECKING:
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from .dtypes import (
@@ -41,6 +45,117 @@
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NullType = Any
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class Namespace(Protocol):
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__dataframe_api_version__: str
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@staticmethod
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def DataFrame() -> DataFrameType:
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...
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@staticmethod
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def Column() -> ColumnType:
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...
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@staticmethod
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def Int64() -> Int64:...
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@staticmethod
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def Int16() -> Int16:...
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@staticmethod
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def Int32() -> Int32:
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...
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@staticmethod
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def Int8() -> Int8:
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...
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@staticmethod
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def UInt64() -> UInt64:
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...
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@staticmethod
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def UInt32() -> UInt32:
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...
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@staticmethod
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def UInt16() -> UInt16:
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...
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@staticmethod
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def UInt8() -> UInt8:
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...
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@staticmethod
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def Float64() -> Float64:
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...
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@staticmethod
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def Float32() -> Float32:
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...
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@staticmethod
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def Bool() -> Bool:
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...
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@staticmethod
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def concat(dataframes: Sequence[DataFrameType]) -> DataFrameType:
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...
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@staticmethod
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def column_from_sequence(
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sequence: Sequence[Any],
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*,
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dtype: Any,
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name: str = "",
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api_version: str | None = None,
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) -> ColumnType:
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...
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@staticmethod
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def dataframe_from_dict(
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data: Mapping[str, ColumnType], *, api_version: str | None = None
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) -> DataFrameType:
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...
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@staticmethod
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def column_from_1d_array(
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array: Any, *, dtype: Any, name: str = "", api_version: str | None = None
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) -> ColumnType:
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...
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@staticmethod
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def dataframe_from_2d_array(
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array: Any,
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*,
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names: Sequence[str],
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dtypes: Mapping[str, Any],
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api_version: str | None = None,
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) -> DataFrameType:
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...
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@staticmethod
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def is_null(value: object, /) -> bool:
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...
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@staticmethod
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def is_dtype(dtype: Any, kind: str | tuple[str, ...]) -> bool:
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...
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class SupportsDataFrameAPI(Protocol):
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def __dataframe_consortium_standard__(
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self, *, api_version: str | None = None
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) -> DataFrameType:
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...
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class SupportsColumnAPI(Protocol):
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def __column_consortium_standard__(
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self, *, api_version: str | None = None
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) -> ColumnType:
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...
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__all__ = [
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"Any",
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"DataFrame",
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"device",
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"DType",
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"ellipsis",
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"Enum",
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]

Diff for: ‎spec/API_specification/dataframe_api/column_object.py

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@@ -3,7 +3,7 @@
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from typing import Any,NoReturn, TYPE_CHECKING, Literal, Generic
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if TYPE_CHECKING:
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from ._types import NullType, Scalar, DType
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from ._types import NullType, Scalar, DType, Namespace
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__all__ = ['Column']
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"""
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def __column_namespace__(self) -> Any:
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def __column_namespace__(self) -> Namespace:
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"""
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Returns an object that has all the Dataframe Standard API functions on it.
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Diff for: ‎spec/API_specification/dataframe_api/dataframe_object.py

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@@ -6,7 +6,7 @@
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if TYPE_CHECKING:
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from .column_object import Column
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from .groupby_object import GroupBy
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from ._types import NullType, Scalar, DType
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from ._types import NullType, Scalar, Namespace, DType
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__all__ = ["DataFrame"]
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**Methods and Attributes**
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"""
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def __dataframe_namespace__(self) -> Any:
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def __dataframe_namespace__(self) -> Namespace:
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"""
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Returns an object that has all the top-level dataframe API functions on it.
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Diff for: ‎spec/API_specification/examples/01_standardise_columns.py

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from typing import Any
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from dataframe_api._types import SupportsDataFrameAPI
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def my_dataframe_agnostic_function(df_non_standard: SupportsDataFrameAPI) -> Any:
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df = df_non_standard.__dataframe_consortium_standard__(api_version='2023.09-beta')
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for column_name in df.column_names:
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if column_name == 'species':
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continue
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new_column = df.get_column_by_name(column_name)
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new_column = (new_column - new_column.mean()) / new_column.std()
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df = df.assign(new_column.rename(f'{column_name}_scaled'))
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return df.dataframe

Diff for: ‎spec/API_specification/examples/02_plotting.py

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from typing import Callable, Any
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my_plotting_function: Callable[[Any, Any], Any]
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from dataframe_api._types import SupportsColumnAPI
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def group_by_and_plot(
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x_any: SupportsColumnAPI,
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y_any: SupportsColumnAPI,
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color_any: SupportsColumnAPI,
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) -> None:
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x = x_any.__column_consortium_standard__()
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y = y_any.__column_consortium_standard__()
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color = color_any.__column_consortium_standard__()
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namespace = x.__column_namespace__()
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df = namespace.dataframe_from_dict({"x": x, "y": y, "color": color})
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agg = df.group_by("color").mean()
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x = agg.get_column_by_name("x").to_array_object(namespace.Float64())
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y = agg.get_column_by_name("y").to_array_object(namespace.Float64())
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my_plotting_function(x, y)

Diff for: ‎spec/API_specification/examples/README.md

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# Examples
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Here are some examples of how to use the DataFrame API.
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These should work for any library which has an implemenation of the Standard.

Diff for: ‎spec/API_specification/examples/__init__.py

Whitespace-only changes.

Diff for: ‎spec/conf.py

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('py:class', 'Bool'),
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('py:class', 'optional'),
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('py:class', 'NullType'),
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('py:class', 'Namespace'),
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]
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# NOTE: this alias handling isn't used yet - added in anticipation of future
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# need based on dataframe API aliases.
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# List of patterns, relative to source directory, that match files and
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# directories to ignore when looking for source files.
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# This pattern also affects html_static_path and html_extra_path.
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exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
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exclude_patterns = [
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'_build',
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'Thumbs.db',
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'.DS_Store',
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'API_specification/examples/*',
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]
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# MyST options
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myst_heading_anchors = 3

Diff for: ‎spec/purpose_and_scope.md

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@@ -275,36 +275,7 @@ latest version of the dataframe API specification. If the given
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version is invalid or not implemented for the given module, an
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error should be raised. Default: ``None``.
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Example:
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```python
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import pandas as pd
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import polars as pl
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df_pandas = pd.read_parquet('iris.parquet')
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df_polars = pl.scan_parquet('iris.parquet')
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def my_dataframe_agnostic_function(df):
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df = df.__dataframe_consortium_standard__(api_version='2023.09-beta')
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mask = df.get_column_by_name('species') != 'setosa'
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df = df.filter(mask)
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for column_name in df.column_names:
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if column_name == 'species':
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continue
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new_column = df.get_column_by_name(column_name)
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new_column = (new_column - new_column.mean()) / new_column.std()
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df = df.assign(new_column.rename(f'{column_name}_scaled'))
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return df.dataframe
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# Then, either of the following will work as expected:
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my_dataframe_agnostic_function(df_pandas)
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my_dataframe_agnostic_function(df_polars)
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my_dataframe_agnostic_function(df_any_other_library_with_a_standard_compliant_namespace)
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```
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For some examples, please check https://github.com/data-apis/dataframe-api/tree/main/spec/examples.
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### Checking a dataframe object for Compliance
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