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DOC: Fixing EX01 - Added examples #53561

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8 changes: 0 additions & 8 deletions ci/code_checks.sh
Original file line number Diff line number Diff line change
Expand Up @@ -265,35 +265,27 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.api.indexers.VariableOffsetWindowIndexer \
pandas.core.groupby.DataFrameGroupBy.diff \
pandas.core.groupby.DataFrameGroupBy.ffill \
pandas.core.groupby.DataFrameGroupBy.max \
pandas.core.groupby.DataFrameGroupBy.median \
pandas.core.groupby.DataFrameGroupBy.min \
pandas.core.groupby.DataFrameGroupBy.ohlc \
pandas.core.groupby.DataFrameGroupBy.pct_change \
pandas.core.groupby.DataFrameGroupBy.prod \
pandas.core.groupby.DataFrameGroupBy.sem \
pandas.core.groupby.DataFrameGroupBy.shift \
pandas.core.groupby.DataFrameGroupBy.size \
pandas.core.groupby.DataFrameGroupBy.skew \
pandas.core.groupby.DataFrameGroupBy.std \
pandas.core.groupby.DataFrameGroupBy.sum \
pandas.core.groupby.DataFrameGroupBy.var \
pandas.core.groupby.SeriesGroupBy.diff \
pandas.core.groupby.SeriesGroupBy.fillna \
pandas.core.groupby.SeriesGroupBy.ffill \
pandas.core.groupby.SeriesGroupBy.max \
pandas.core.groupby.SeriesGroupBy.median \
pandas.core.groupby.SeriesGroupBy.min \
pandas.core.groupby.SeriesGroupBy.nunique \
pandas.core.groupby.SeriesGroupBy.ohlc \
pandas.core.groupby.SeriesGroupBy.pct_change \
pandas.core.groupby.SeriesGroupBy.prod \
pandas.core.groupby.SeriesGroupBy.sem \
pandas.core.groupby.SeriesGroupBy.shift \
pandas.core.groupby.SeriesGroupBy.size \
pandas.core.groupby.SeriesGroupBy.skew \
pandas.core.groupby.SeriesGroupBy.std \
pandas.core.groupby.SeriesGroupBy.sum \
pandas.core.groupby.SeriesGroupBy.var \
pandas.core.groupby.SeriesGroupBy.hist \
pandas.core.groupby.DataFrameGroupBy.plot \
Expand Down
168 changes: 164 additions & 4 deletions pandas/core/groupby/groupby.py
Original file line number Diff line number Diff line change
Expand Up @@ -341,6 +341,10 @@ class providing the base-class of operations.
-------
Series or DataFrame
Computed {fname} of values within each group.

Examples
--------
{example}
"""

_pipe_template = """
Expand Down Expand Up @@ -2550,7 +2554,46 @@ def size(self) -> DataFrame | Series:
return result

@final
@doc(_groupby_agg_method_template, fname="sum", no=False, mc=0)
@doc(
_groupby_agg_method_template,
fname="sum",
no=False,
mc=0,
example=dedent(
"""\
For SeriesGroupBy:

>>> lst = ['a', 'a', 'b', 'b']
>>> ser = pd.Series([1, 2, 3, 4], index=lst)
>>> ser
a 1
a 2
b 3
b 4
dtype: int64
>>> ser.groupby(level=0).sum()
a 3
b 7
dtype: int64

For DataFrameGroupBy:

>>> data = [[1, 8, 2], [1, 2, 5], [2, 5, 8], [2, 6, 9]]
>>> df = pd.DataFrame(data, columns=["a", "b", "c"],
... index=["tiger", "leopard", "cheetah", "lion"])
>>> df
a b c
tiger 1 8 2
leopard 1 2 5
cheetah 2 5 8
lion 2 6 9
>>> df.groupby("a").sum()
b c
a
1 10 7
2 11 17"""
),
)
def sum(
self,
numeric_only: bool = False,
Expand Down Expand Up @@ -2580,14 +2623,92 @@ def sum(
return self._reindex_output(result, fill_value=0)

@final
@doc(_groupby_agg_method_template, fname="prod", no=False, mc=0)
@doc(
_groupby_agg_method_template,
fname="prod",
no=False,
mc=0,
example=dedent(
"""\
For SeriesGroupBy:

>>> lst = ['a', 'a', 'b', 'b']
>>> ser = pd.Series([1, 2, 3, 4], index=lst)
>>> ser
a 1
a 2
b 3
b 4
dtype: int64
>>> ser.groupby(level=0).prod()
a 2
b 12
dtype: int64

For DataFrameGroupBy:

>>> data = [[1, 8, 2], [1, 2, 5], [2, 5, 8], [2, 6, 9]]
>>> df = pd.DataFrame(data, columns=["a", "b", "c"],
... index=["tiger", "leopard", "cheetah", "lion"])
>>> df
a b c
tiger 1 8 2
leopard 1 2 5
cheetah 2 5 8
lion 2 6 9
>>> df.groupby("a").prod()
b c
a
1 16 10
2 30 72"""
),
)
def prod(self, numeric_only: bool = False, min_count: int = 0):
return self._agg_general(
numeric_only=numeric_only, min_count=min_count, alias="prod", npfunc=np.prod
)

@final
@doc(_groupby_agg_method_template, fname="min", no=False, mc=-1)
@doc(
_groupby_agg_method_template,
fname="min",
no=False,
mc=-1,
example=dedent(
"""\
For SeriesGroupBy:

>>> lst = ['a', 'a', 'b', 'b']
>>> ser = pd.Series([1, 2, 3, 4], index=lst)
>>> ser
a 1
a 2
b 3
b 4
dtype: int64
>>> ser.groupby(level=0).min()
a 1
b 3
dtype: int64

For DataFrameGroupBy:

>>> data = [[1, 8, 2], [1, 2, 5], [2, 5, 8], [2, 6, 9]]
>>> df = pd.DataFrame(data, columns=["a", "b", "c"],
... index=["tiger", "leopard", "cheetah", "lion"])
>>> df
a b c
tiger 1 8 2
leopard 1 2 5
cheetah 2 5 8
lion 2 6 9
>>> df.groupby("a").min()
b c
a
1 2 2
2 5 8"""
),
)
def min(
self,
numeric_only: bool = False,
Expand All @@ -2608,7 +2729,46 @@ def min(
)

@final
@doc(_groupby_agg_method_template, fname="max", no=False, mc=-1)
@doc(
_groupby_agg_method_template,
fname="max",
no=False,
mc=-1,
example=dedent(
"""\
For SeriesGroupBy:

>>> lst = ['a', 'a', 'b', 'b']
>>> ser = pd.Series([1, 2, 3, 4], index=lst)
>>> ser
a 1
a 2
b 3
b 4
dtype: int64
>>> ser.groupby(level=0).max()
a 2
b 4
dtype: int64

For DataFrameGroupBy:

>>> data = [[1, 8, 2], [1, 2, 5], [2, 5, 8], [2, 6, 9]]
>>> df = pd.DataFrame(data, columns=["a", "b", "c"],
... index=["tiger", "leopard", "cheetah", "lion"])
>>> df
a b c
tiger 1 8 2
leopard 1 2 5
cheetah 2 5 8
lion 2 6 9
>>> df.groupby("a").max()
b c
a
1 8 5
2 6 9"""
),
)
def max(
self,
numeric_only: bool = False,
Expand Down