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Add a correction keyword to the std methods #183

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Merged
merged 4 commits into from
Jul 5, 2023
Merged

Add a correction keyword to the std methods #183

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802a45d
add correction to std
MarcoGorelli Jun 20, 2023
1e2d7b8
Merge branch 'main' into correction
MarcoGorelli Jun 21, 2023
a258400
Update spec/API_specification/dataframe_api/column_object.py
MarcoGorelli Jun 26, 2023
b77d702
Clarify the `correction` parameter and its allowed values in more detail
rgommers Jul 5, 2023
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20 changes: 18 additions & 2 deletions spec/API_specification/dataframe_api/column_object.py
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Original file line number Diff line number Diff line change
Expand Up @@ -469,20 +469,36 @@ def mean(self, *, skip_nulls: bool = True) -> Scalar:
dtypes.
"""

def std(self, *, skip_nulls: bool = True) -> Scalar:
def std(self, *, correction: int | float = 1, skip_nulls: bool = True) -> Scalar:
"""
Reduction returns a scalar. Must be supported for numerical and
datetime data types. Returns a float for numerical data types, and
datetime (with the appropriate timedelta format string) for datetime
dtypes.

Parameters
----------
correction
Correction to apply to the result. 0 for sample standard deviation
and 1 for population standard deviation.
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If we're only supporting 0 or 1 can this just be an int for now? We could change to allow floats later if desired?

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I think the description is misleading here. The 0 and 1 references are, tmk, to help users identify common correction values. See the Array API specification for a more extensive description.

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Should we "borrow" the docstring from the Array API specification then?

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Fine with me, but up to Marco. :)

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I've reworded to make clear that 0 and 1 are just examples

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That rewording was for only 1 of 4 docstrings. I now edited all of them, and for one adopted the more extensive description from the array API standard.

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@MarcoGorelli if you're happy with that change, I think this PR is good to go.

skip_nulls
Whether to skip null values.
"""

def var(self, *, skip_nulls: bool = True) -> Scalar:
def var(self, *, correction: int | float = 1, skip_nulls: bool = True) -> Scalar:
"""
Reduction returns a scalar. Must be supported for numerical and
datetime data types. Returns a float for numerical data types, and
datetime (with the appropriate timedelta format string) for datetime
dtypes.

Parameters
----------
correction
Correction to apply to the result. 0 for sample standard deviation
and 1 for population standard deviation.
skip_nulls
Whether to skip null values.
"""

def is_null(self) -> Column:
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20 changes: 18 additions & 2 deletions spec/API_specification/dataframe_api/dataframe_object.py
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Expand Up @@ -684,15 +684,31 @@ def mean(self, *, skip_nulls: bool = True) -> DataFrame:
"""
...

def std(self, *, skip_nulls: bool = True) -> DataFrame:
def std(self, *, correction: int | float = 1, skip_nulls: bool = True) -> DataFrame:
"""
Reduction returns a 1-row DataFrame.

Parameters
----------
correction
Correction to apply to the result. 0 for sample standard deviation
and 1 for population standard deviation.
skip_nulls
Whether to skip null values.
"""
...

def var(self, *, skip_nulls: bool = True) -> DataFrame:
def var(self, *, correction: int | float = 1, skip_nulls: bool = True) -> DataFrame:
"""
Reduction returns a 1-row DataFrame.

Parameters
----------
correction
Correction to apply to the result. 0 for sample standard deviation
and 1 for population standard deviation.
skip_nulls
Whether to skip null values.
"""
...

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4 changes: 2 additions & 2 deletions spec/API_specification/dataframe_api/groupby_object.py
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Expand Up @@ -41,10 +41,10 @@ def median(self, *, skip_nulls: bool = True) -> "DataFrame":
def mean(self, *, skip_nulls: bool = True) -> "DataFrame":
...

def std(self, *, skip_nulls: bool = True) -> "DataFrame":
def std(self, *, correction: int | float = 1, skip_nulls: bool = True) -> "DataFrame":
...

def var(self, *, skip_nulls: bool = True) -> "DataFrame":
def var(self, *, correction: int | float = 1, skip_nulls: bool = True) -> "DataFrame":
...

def size(self) -> "DataFrame":
Expand Down