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authoredFeb 16, 2023
51236 ex02 errors docstrings vi (#51432)
DOC: fix EX02 errors in docstrings VI
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‎ci/code_checks.sh

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@@ -591,14 +591,11 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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pandas.api.types.is_timedelta64_ns_dtype \
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pandas.api.types.is_unsigned_integer_dtype \
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pandas.core.groupby.DataFrameGroupBy.take \
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pandas.core.groupby.SeriesGroupBy.take \
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pandas.io.formats.style.Styler.concat \
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pandas.io.formats.style.Styler.export \
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pandas.io.formats.style.Styler.set_td_classes \
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pandas.io.formats.style.Styler.use \
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pandas.io.json.build_table_schema \
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pandas.merge_ordered \
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pandas.option_context \
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pandas.plotting.andrews_curves \
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pandas.plotting.autocorrelation_plot \
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pandas.plotting.lag_plot \

‎pandas/_config/config.py

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@@ -424,6 +424,7 @@ class option_context(ContextDecorator):
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Examples
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--------
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>>> from pandas import option_context
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>>> with option_context('display.max_rows', 10, 'display.max_columns', 5):
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... pass
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"""

‎pandas/core/groupby/generic.py

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@@ -933,7 +933,7 @@ def take(
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Examples
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--------
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>>> df = DataFrame([('falcon', 'bird', 389.0),
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>>> df = pd.DataFrame([('falcon', 'bird', 389.0),
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... ('parrot', 'bird', 24.0),
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... ('lion', 'mammal', 80.5),
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... ('monkey', 'mammal', np.nan),
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Examples
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--------
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>>> df = DataFrame([('falcon', 'bird', 389.0),
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>>> df = pd.DataFrame([('falcon', 'bird', 389.0),
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... ('parrot', 'bird', 24.0),
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... ('lion', 'mammal', 80.5),
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... ('monkey', 'mammal', np.nan),
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2 2 lion mammal 80.5
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1 monkey mammal NaN
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The order of the specified indices influnces the order in the result.
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The order of the specified indices influences the order in the result.
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Here, the order is swapped from the previous example.
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>>> gb.take([0, 1])
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>>> gb.take([1, 0])
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name class max_speed
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1 4 falcon bird 389.0
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3 parrot bird 24.0
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2 2 lion mammal 80.5
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1 monkey mammal NaN
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1 3 parrot bird 24.0
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4 falcon bird 389.0
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2 1 monkey mammal NaN
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2 lion mammal 80.5
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Take elements at indices 1 and 2 along the axis 1 (column selection).
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‎pandas/core/reshape/merge.py

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@@ -277,6 +277,7 @@ def merge_ordered(
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Examples
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--------
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>>> from pandas import merge_ordered
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>>> df1 = pd.DataFrame(
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... {
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... "key": ["a", "c", "e", "a", "c", "e"],

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