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use snake case (#178)
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+12
-12
lines changed

4 files changed

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-12
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spec/API_specification/dataframe_api/__init__.py

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@@ -17,7 +17,7 @@
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"column_from_sequence",
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"concat",
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"dataframe_from_dict",
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"isnull",
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"is_null",
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"null",
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]
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@@ -99,7 +99,7 @@ class null:
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From ``__eq__`` and from ``__bool__``.
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For ``__eq__``: a missing value must not be compared for equality
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directly. Instead, use `DataFrame.isnull` or `Column.isnull` to check
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directly. Instead, use `DataFrame.is_null` or `Column.is_null` to check
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for presence of missing values.
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For ``__bool__``: truthiness of a missing value is ambiguous.
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"""
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...
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def isnull(value: object, /) -> bool:
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def is_null(value: object, /) -> bool:
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"""
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Check if an object is a `null` scalar.
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spec/API_specification/dataframe_api/column_object.py

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@@ -426,7 +426,7 @@ def var(self, *, skip_nulls: bool = True) -> DType:
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dtypes.
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"""
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def isnull(self) -> Column:
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def is_null(self) -> Column:
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"""
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Check for 'missing' or 'null' entries.
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@@ -436,7 +436,7 @@ def isnull(self) -> Column:
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See also
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--------
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isnan
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is_nan
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Notes
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-----
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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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def is_nan(self) -> Column:
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"""
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Check for nan entries.
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@@ -455,7 +455,7 @@ def isnan(self) -> Column:
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See also
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--------
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isnull
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is_null
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Notes
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-----

spec/API_specification/dataframe_api/dataframe_object.py

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@@ -696,7 +696,7 @@ def var(self, *, skip_nulls: bool = True) -> DataFrame:
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"""
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...
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def isnull(self) -> DataFrame:
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def is_null(self) -> DataFrame:
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"""
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Check for 'missing' or 'null' entries.
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See also
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--------
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isnan
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is_nan
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Notes
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-----
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"""
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...
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def isnan(self) -> DataFrame:
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def is_nan(self) -> DataFrame:
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"""
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Check for nan entries.
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See also
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--------
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isnull
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is_null
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Notes
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-----

spec/API_specification/index.rst

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@@ -14,7 +14,7 @@ of objects and functions in the top-level namespace. The latter are:
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:nosignatures:
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__dataframe_api_version__
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isnull
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is_null
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null
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2020
The ``DataFrame``, ``Column`` and ``GroupBy`` objects have the following

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