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DOC: Fixing EX01 - Added examples #53352

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May 24, 2023
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7 changes: 0 additions & 7 deletions ci/code_checks.sh
Original file line number Diff line number Diff line change
Expand Up @@ -254,13 +254,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.util.hash_pandas_object \
pandas_object \
pandas.api.interchange.from_dataframe \
pandas.Index.drop \
pandas.Index.identical \
pandas.Index.insert \
pandas.Index.is_ \
pandas.Index.take \
pandas.Index.putmask \
pandas.Index.unique \
pandas.Index.fillna \
pandas.Index.dropna \
pandas.Index.astype \
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55 changes: 55 additions & 0 deletions pandas/core/indexes/base.py
Original file line number Diff line number Diff line change
Expand Up @@ -799,6 +799,18 @@ def is_(self, other) -> bool:
See Also
--------
Index.identical : Works like ``Index.is_`` but also checks metadata.

Examples
--------
>>> idx1 = pd.Index(['1', '2', '3'])
>>> idx2 = pd.Index(['1', '2', '3'])
>>> idx2.is_(idx1)
False

>>> idx1 = pd.Index(['1', '2', '3'])
>>> new_name = idx1
>>> new_name.is_(idx1)
True
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to make it clearer, maybe we could have an example like

>>> idx1.is_(idx1.view())
True
>>> idx1.is_(idx1.copy())
False

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Done

"""
if self is other:
return True
Expand Down Expand Up @@ -1089,6 +1101,12 @@ def astype(self, dtype, copy: bool = True):
--------
numpy.ndarray.take: Return an array formed from the
elements of a at the given indices.

Examples
--------
>>> idx = pd.Index(['a', 'b', 'c'])
>>> idx.take([2])
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I think take is often used with more than one element, and there can be repetitions - maybe something like

In [10]: idx = pd.Index(['a', 'b', 'c'])

In [11]: idx.take([2, 2, 1, 2])
Out[11]: Index(['c', 'c', 'b', 'c'], dtype='object')

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Done

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It's green @MarcoGorelli

Index(['c'], dtype='object')
"""

@Appender(_index_shared_docs["take"] % _index_doc_kwargs)
Expand Down Expand Up @@ -2966,6 +2984,12 @@ def unique(self, level: Hashable | None = None) -> Self:
--------
unique : Numpy array of unique values in that column.
Series.unique : Return unique values of Series object.

Examples
--------
>>> idx = pd.Index([1, 1, 2, 3, 3])
>>> idx.unique()
Index([1, 2, 3], dtype='int64')
"""
if level is not None:
self._validate_index_level(level)
Expand Down Expand Up @@ -5345,6 +5369,13 @@ def putmask(self, mask, value) -> Index:
--------
numpy.ndarray.putmask : Changes elements of an array
based on conditional and input values.

Examples
--------
>>> idx1 = pd.Index([1, 2, 3])
>>> idx2 = pd.Index([5, 6, 7])
>>> idx1.putmask([True, False, False], idx2)
Index([5, 2, 3], dtype='int64')
"""
mask, noop = validate_putmask(self._values, mask)
if noop:
Expand Down Expand Up @@ -5474,6 +5505,18 @@ def identical(self, other) -> bool:
bool
If two Index objects have equal elements and same type True,
otherwise False.

Examples
--------
>>> idx1 = pd.Index(['1', '2', '3'])
>>> idx2 = pd.Index(['1', '2', '3'])
>>> idx2.identical(idx1)
True

>>> idx1 = pd.Index(['1', '2', '3'], name="A")
>>> idx2 = pd.Index(['1', '2', '3'], name="B")
>>> idx2.identical(idx1)
False
"""
return (
self.equals(other)
Expand Down Expand Up @@ -6694,6 +6737,12 @@ def insert(self, loc: int, item) -> Index:
Returns
-------
Index

Examples
--------
>>> idx = pd.Index(['a', 'b', 'c'])
>>> idx.insert(1, 'x')
Index(['a', 'x', 'b', 'c'], dtype='object')
"""
item = lib.item_from_zerodim(item)
if is_valid_na_for_dtype(item, self.dtype) and self.dtype != object:
Expand Down Expand Up @@ -6755,6 +6804,12 @@ def drop(
------
KeyError
If not all of the labels are found in the selected axis

Examples
--------
>>> idx = pd.Index(['a', 'b', 'c'])
>>> idx.drop(['a'])
Index(['b', 'c'], dtype='object')
"""
if not isinstance(labels, Index):
# avoid materializing e.g. RangeIndex
Expand Down