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TYP: Add annotation for df.pivot #32197

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Merged
merged 41 commits into from
May 18, 2020
Merged

TYP: Add annotation for df.pivot #32197

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7e461a1
remove \n from docstring
charlesdong1991 Dec 3, 2018
1314059
fix conflicts
charlesdong1991 Jan 19, 2019
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charlesdong1991 Jul 30, 2019
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charlesdong1991 Jan 14, 2020
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fix issue 17038
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Merge remote-tracking branch 'upstream/master' into add_signature_30928
charlesdong1991 Feb 23, 2020
1cc1225
Add signature for pivot
charlesdong1991 Feb 23, 2020
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sorting
charlesdong1991 Feb 23, 2020
2807b63
try fix annotation
charlesdong1991 Feb 23, 2020
2fdd875
fixup
charlesdong1991 Feb 24, 2020
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charlesdong1991 Feb 24, 2020
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Merge remote-tracking branch 'upstream/master' into add_signature_30928
charlesdong1991 Feb 25, 2020
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charlesdong1991 Apr 3, 2020
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improve annotation
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charlesdong1991 Apr 3, 2020
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charlesdong1991 Apr 3, 2020
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Merge remote-tracking branch 'upstream/master' into add_signature_30928
charlesdong1991 Apr 8, 2020
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add type ignore
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add comment
charlesdong1991 Apr 8, 2020
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Merge remote-tracking branch 'upstream/master' into add_signature_30928
charlesdong1991 May 17, 2020
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use cast
charlesdong1991 May 17, 2020
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use convert_list_like
charlesdong1991 May 18, 2020
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charlesdong1991 May 18, 2020
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charlesdong1991 May 18, 2020
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Merge remote-tracking branch 'upstream/master' into add_signature_30928
charlesdong1991 May 18, 2020
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22 changes: 14 additions & 8 deletions pandas/core/reshape/pivot.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,8 @@
from typing import TYPE_CHECKING, Callable, Dict, List, Tuple, Union
from typing import TYPE_CHECKING, Callable, Dict, List, Optional, Tuple, Union

import numpy as np

from pandas._typing import Label
from pandas.util._decorators import Appender, Substitution

from pandas.core.dtypes.cast import maybe_downcast_to_dtype
Expand Down Expand Up @@ -422,13 +423,18 @@ def _convert_by(by):

@Substitution("\ndata : DataFrame")
@Appender(_shared_docs["pivot"], indents=1)
def pivot(data: "DataFrame", index=None, columns=None, values=None) -> "DataFrame":
def pivot(
data: "DataFrame",
index: Optional[Union[Label, List[Optional[Label]]]] = None,
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Suggested change
index: Optional[Union[Label, List[Optional[Label]]]] = None,
index: Optional[Union[Label, Sequence[Optional[Label]]]] = None,

For API items we want to be as generic as possible, so Sequence instead of List and Mapping instead of Dict (unless the interface really isn't generic)

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Same comment on next two lines

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For API items we want to be as generic as possible, so Sequence instead of List and Mapping instead of Dict (unless the interface really isn't generic)

thanks for the very nice tip!!! 👍

columns: Optional[Union[Label, List[Optional[Label]]]] = None,
values: Optional[Union[Label, List[Optional[Label]]]] = None,
) -> "DataFrame":
if columns is None:
raise TypeError("pivot() missing 1 required argument: 'columns'")
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if this is a required kwarg, should the Optional be removed from the signature? cc @simonjayhawkins not sure how to handle this given that the default value is None

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There are a few considerations here.

Optional is normally included to represent a keyword argument that defaults to None. Since index is a keyword argument, columns must be a keyword argument (non-default argument follows default argument). but because Label already includes None (due to an issue with Hashable) the Optional isn't actually required in this case (This is the reason to exclude Optional from aliases in general).

If Optional was omitted, this could add to the confusion.

Since columns should allow None, if a column is named None.

so the default and check here should probably be _lib.no_default.

_lib.no_default currently resolves to Any (defined in cython with no stubs) so is compatible with anything.

If we typed _lib.no_default which is currently object() we wouldn't be able to type parameters precisely since object() wouldn't be compatible. In the future we may wish to define using Enums but this would add to the noise of the function signature from an end user perspective.

from https://www.python.org/dev/peps/pep-0484/#support-for-singleton-types-in-unions

To allow precise typing in such situations, the user should use the Union type in conjunction with the enum.Enum class provided by the standard library, so that type errors can be caught statically:

columns = columns if is_list_like(columns) else [columns]

if values is None:
cols: List[str] = []
cols: List[Label] = []
if index is None:
pass
elif is_list_like(index):
Expand All @@ -441,15 +447,15 @@ def pivot(data: "DataFrame", index=None, columns=None, values=None) -> "DataFram
indexed = data.set_index(cols, append=append)
else:
if index is None:
index = [Series(data.index, name=data.index.name)]
idx_list = [Series(data.index, name=data.index.name)]
elif is_list_like(index):
index = [data[idx] for idx in index]
idx_list = [data[idx] for idx in index]
else:
index = [data[index]]
idx_list = [data[index]]

data_columns = [data[col] for col in columns]
index.extend(data_columns)
index = MultiIndex.from_arrays(index)
idx_list.extend(data_columns)
index = MultiIndex.from_arrays(idx_list)

if is_list_like(values) and not isinstance(values, tuple):
# Exclude tuple because it is seen as a single column name
Expand Down