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ShaharNavehShaharNaveh
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DOC: Fixed documentation for few files (#40903)
Co-authored-by: ShaharNaveh <>
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‎ci/code_checks.sh‎

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Original file line numberDiff line numberDiff line change
@@ -110,10 +110,13 @@ if [[ -z "$CHECK" || "$CHECK" == "doctests" ]]; then
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pytest -q --doctest-modules \
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pandas/core/accessor.py \
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pandas/core/aggregation.py \
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pandas/core/algorithms.py \
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pandas/core/base.py \
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pandas/core/construction.py \
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pandas/core/frame.py \
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pandas/core/generic.py \
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pandas/core/indexers.py \
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pandas/core/nanops.py \
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pandas/core/series.py \
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pandas/io/sql.py
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RET=$(($RET + $?)) ; echo $MSG "DONE"

‎pandas/core/algorithms.py‎

Lines changed: 38 additions & 24 deletions
Original file line numberDiff line numberDiff line change
@@ -375,46 +375,60 @@ def unique(values):
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>>> pd.unique(pd.Series([2] + [1] * 5))
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array([2, 1])
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378-
>>> pd.unique(pd.Series([pd.Timestamp('20160101'),
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... pd.Timestamp('20160101')]))
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>>> pd.unique(pd.Series([pd.Timestamp("20160101"), pd.Timestamp("20160101")]))
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array(['2016-01-01T00:00:00.000000000'], dtype='datetime64[ns]')
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>>> pd.unique(pd.Series([pd.Timestamp('20160101', tz='US/Eastern'),
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... pd.Timestamp('20160101', tz='US/Eastern')]))
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array([Timestamp('2016-01-01 00:00:00-0500', tz='US/Eastern')],
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dtype=object)
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>>> pd.unique(pd.Index([pd.Timestamp('20160101', tz='US/Eastern'),
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... pd.Timestamp('20160101', tz='US/Eastern')]))
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>>> pd.unique(
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... pd.Series(
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... [
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... pd.Timestamp("20160101", tz="US/Eastern"),
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... pd.Timestamp("20160101", tz="US/Eastern"),
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... ]
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... )
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... )
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<DatetimeArray>
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['2016-01-01 00:00:00-05:00']
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Length: 1, dtype: datetime64[ns, US/Eastern]
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>>> pd.unique(
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... pd.Index(
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... [
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... pd.Timestamp("20160101", tz="US/Eastern"),
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... pd.Timestamp("20160101", tz="US/Eastern"),
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... ]
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... )
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... )
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DatetimeIndex(['2016-01-01 00:00:00-05:00'],
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... dtype='datetime64[ns, US/Eastern]', freq=None)
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dtype='datetime64[ns, US/Eastern]',
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freq=None)
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>>> pd.unique(list('baabc'))
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>>> pd.unique(list("baabc"))
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array(['b', 'a', 'c'], dtype=object)
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An unordered Categorical will return categories in the
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order of appearance.
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>>> pd.unique(pd.Series(pd.Categorical(list('baabc'))))
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[b, a, c]
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Categories (3, object): [b, a, c]
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>>> pd.unique(pd.Series(pd.Categorical(list("baabc"))))
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['b', 'a', 'c']
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Categories (3, object): ['a', 'b', 'c']
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402-
>>> pd.unique(pd.Series(pd.Categorical(list('baabc'),
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... categories=list('abc'))))
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[b, a, c]
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Categories (3, object): [b, a, c]
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>>> pd.unique(pd.Series(pd.Categorical(list("baabc"), categories=list("abc"))))
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['b', 'a', 'c']
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Categories (3, object): ['a', 'b', 'c']
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An ordered Categorical preserves the category ordering.
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409-
>>> pd.unique(pd.Series(pd.Categorical(list('baabc'),
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... categories=list('abc'),
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... ordered=True)))
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[b, a, c]
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Categories (3, object): [a < b < c]
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>>> pd.unique(
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... pd.Series(
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... pd.Categorical(list("baabc"), categories=list("abc"), ordered=True)
424+
... )
425+
... )
426+
['b', 'a', 'c']
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Categories (3, object): ['a' < 'b' < 'c']
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An array of tuples
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>>> pd.unique([('a', 'b'), ('b', 'a'), ('a', 'c'), ('b', 'a')])
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>>> pd.unique([("a", "b"), ("b", "a"), ("a", "c"), ("b", "a")])
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array([('a', 'b'), ('b', 'a'), ('a', 'c')], dtype=object)
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"""
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values = _ensure_arraylike(values)

‎pandas/core/indexers.py‎

Lines changed: 18 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -209,16 +209,24 @@ def validate_indices(indices: np.ndarray, n: int) -> None:
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Examples
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--------
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>>> validate_indices([1, 2], 3)
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# OK
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>>> validate_indices([1, -2], 3)
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ValueError
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>>> validate_indices([1, 2, 3], 3)
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IndexError
218-
>>> validate_indices([-1, -1], 0)
219-
# OK
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>>> validate_indices([0, 1], 0)
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IndexError
212+
>>> validate_indices(np.array([1, 2]), 3) # OK
213+
214+
>>> validate_indices(np.array([1, -2]), 3)
215+
Traceback (most recent call last):
216+
...
217+
ValueError: negative dimensions are not allowed
218+
219+
>>> validate_indices(np.array([1, 2, 3]), 3)
220+
Traceback (most recent call last):
221+
...
222+
IndexError: indices are out-of-bounds
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224+
>>> validate_indices(np.array([-1, -1]), 0) # OK
225+
226+
>>> validate_indices(np.array([0, 1]), 0)
227+
Traceback (most recent call last):
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...
229+
IndexError: indices are out-of-bounds
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"""
223231
if len(indices):
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min_idx = indices.min()

‎pandas/core/nanops.py‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1056,7 +1056,7 @@ def nanargmax(
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[ 6., 7., nan],
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[ 9., 10., nan]])
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>>> nanops.nanargmax(arr, axis=1)
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array([2, 2, 1, 1], dtype=int64)
1059+
array([2, 2, 1, 1])
10601060
"""
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values, mask, _, _, _ = _get_values(values, True, fill_value_typ="-inf", mask=mask)
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# error: Need type annotation for 'result'
@@ -1102,7 +1102,7 @@ def nanargmin(
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[nan, 7., 8.],
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[nan, 10., 11.]])
11041104
>>> nanops.nanargmin(arr, axis=1)
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array([0, 0, 1, 1], dtype=int64)
1105+
array([0, 0, 1, 1])
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"""
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values, mask, _, _, _ = _get_values(values, True, fill_value_typ="+inf", mask=mask)
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# error: Need type annotation for 'result'

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