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MarcoGorellirgommers
MarcoGorelli
and
rgommers
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Fill in column a bit (#141)
* add some missing Column methods * update isnan to only be about nan * fixup return types of reductions * skipna -> skip_nulls * make fillnan changes only to the coolumn page * Specify more precisely what dtypes are supported * Fix Myst rendering issue * Bug: `median` behaves like `mean`, not like `min` * Remove rendering of `__hash__` --------- Co-authored-by: MarcoGorelli <> Co-authored-by: Ralf Gommers <[email protected]>
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‎spec/API_specification/dataframe_api/column_object.py

Lines changed: 350 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -2,7 +2,7 @@
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from typing import Sequence
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5-
from ._types import dtype
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from ._types import Scalar, dtype
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__all__ = ['Column']
@@ -35,3 +35,352 @@ def from_sequence(cls, sequence: Sequence[object], dtype: dtype) -> Column:
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-------
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Column
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"""
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def __eq__(self, other: Column | Scalar) -> Column:
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"""
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Compare for equality.
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __ne__(self, other: Column | Scalar) -> Column:
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"""
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Compare for non-equality.
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __ge__(self, other: Column | Scalar) -> Column:
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"""
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Compare for "greater than or equal to" `other`.
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __gt__(self, other: Column | Scalar) -> Column:
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"""
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Compare for "greater than" `other`.
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __le__(self, other: Column | Scalar) -> Column:
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"""
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Compare for "less than or equal to" `other`.
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __lt__(self, other: Column | Scalar) -> Column:
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"""
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Compare for "less than" `other`.
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __and__(self, other: Column | Scalar) -> Column:
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"""
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Add `other` dataframe or scalar to this column.
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __sub__(self, other: Column | Scalar) -> Column:
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"""
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Subtract `other` dataframe or scalar from this column.
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __mul__(self, other: Column | Scalar) -> Column:
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"""
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Multiply `other` dataframe or scalar with this column.
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __truediv__(self, other: Column | Scalar) -> Column:
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"""
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Divide this column by `other` column or scalar. True division, returns floats.
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __floordiv__(self, other: Column | Scalar) -> Column:
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"""
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Floor-divide `other` dataframe or scalar to this column.
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __pow__(self, other: Column | Scalar) -> Column:
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"""
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Raise this column to the power of `other`.
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __mod__(self, other: Column | Scalar) -> Column:
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"""
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Returns modulus of this column by `other` (`%` operator).
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __divmod__(self, other: Column | Scalar) -> tuple[Column, Column]:
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"""
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Return quotient and remainder of integer division. See `divmod` builtin function.
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Parameters
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----------
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other : Column or Scalar
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If Column, must have same length.
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"Scalar" here is defined implicitly by what scalar types are allowed
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for the operation by the underling dtypes.
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Returns
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-------
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Column
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"""
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def __invert__(self) -> Column:
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"""
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Invert truthiness of (boolean) elements.
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Raises
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------
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ValueError
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If any of the Column's columns is not boolean.
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"""
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def any(self, skip_nulls: bool = True) -> bool:
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"""
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Reduction returns a bool.
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Raises
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------
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ValueError
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If column is not boolean.
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"""
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def all(self, skip_nulls: bool = True) -> bool:
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"""
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Reduction returns a bool.
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Raises
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------
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ValueError
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If column is not boolean.
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"""
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def min(self, skip_nulls: bool = True) -> dtype:
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"""
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Reduction returns a scalar. Any data type that supports comparisons
296+
must be supported. The returned value has the same dtype as the column.
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"""
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def max(self, skip_nulls: bool = True) -> dtype:
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"""
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Reduction returns a scalar. Any data type that supports comparisons
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must be supported. The returned value has the same dtype as the column.
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"""
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def sum(self, skip_nulls: bool = True) -> dtype:
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"""
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Reduction returns a scalar. Must be supported for numerical and
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datetime data types. The returned value has the same dtype as the
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column.
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"""
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def prod(self, skip_nulls: bool = True) -> dtype:
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"""
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Reduction returns a scalar. Must be supported for numerical data types.
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The returned value has the same dtype as the column.
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"""
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def median(self, skip_nulls: bool = True) -> dtype:
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"""
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Reduction returns a scalar. Must be supported for numerical and
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datetime data types. Returns a float for numerical data types, and
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datetime (with the appropriate timedelta format string) for datetime
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dtypes.
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"""
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def mean(self, skip_nulls: bool = True) -> dtype:
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"""
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Reduction returns a scalar. Must be supported for numerical and
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datetime data types. Returns a float for numerical data types, and
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datetime (with the appropriate timedelta format string) for datetime
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dtypes.
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"""
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def std(self, skip_nulls: bool = True) -> dtype:
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"""
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Reduction returns a scalar. Must be supported for numerical and
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datetime data types. Returns a float for numerical data types, and
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datetime (with the appropriate timedelta format string) for datetime
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dtypes.
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"""
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def var(self, skip_nulls: bool = True) -> dtype:
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"""
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Reduction returns a scalar. Must be supported for numerical and
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datetime data types. Returns a float for numerical data types, and
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datetime (with the appropriate timedelta format string) for datetime
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dtypes.
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"""
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def isnull(self) -> Column:
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"""
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Check for 'missing' or 'null' entries.
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Returns
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-------
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Column
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See also
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--------
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isnan
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Notes
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-----
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Does *not* include NaN-like entries.
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May optionally include 'NaT' values (if present in an implementation),
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but note that the Standard makes no guarantees about them.
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"""
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def isnan(self) -> Column:
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"""
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Check for nan entries.
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Returns
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-------
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Column
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See also
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--------
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isnull
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Notes
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-----
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This only checks for 'NaN'.
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Does *not* include 'missing' or 'null' entries.
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In particular, does not check for `np.timedelta64('NaT')`.
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"""

‎spec/API_specification/dataframe_api/dataframe_object.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -265,7 +265,7 @@ def sorted_indices(
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If a sequence, it must be the same length as `keys`,
266266
and determines the direction with which to use each
267267
key to sort by.
268-
nulls_position : {'first', 'last'}
268+
nulls_position : ``{'first', 'last'}``
269269
Whether null values should be placed at the beginning
270270
or at the end of the result.
271271
Note that the position of NaNs is unspecified and may
@@ -565,7 +565,7 @@ def all(self, skip_nulls: bool = True) -> DataFrame:
565565
"""
566566
...
567567

568-
def any_rowwise(self, skipna: bool = True) -> Column:
568+
def any_rowwise(self, skip_nulls: bool = True) -> Column:
569569
"""
570570
Reduction returns a Column.
571571
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579579
"""
580580
...
581581

582-
def all_rowwise(self, skipna: bool = True) -> Column:
582+
def all_rowwise(self, skip_nulls: bool = True) -> Column:
583583
"""
584584
Reduction returns a Column.
585585

‎spec/conf.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -51,7 +51,7 @@
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'members': True,
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'special-members': True,
5353
'undoc-members': True,
54-
'exclude-members': '__annotations__, __dict__,__weakref__,__module__',
54+
'exclude-members': '__annotations__, __dict__,__weakref__,__module__,__hash__',
5555
}
5656
add_module_names = False
5757
napoleon_numpy_docstring = True

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