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DOC: standardizing docstrings to use pd.DataFrame #18788

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Dec 16, 2017
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DOC: standardizing docstrings to use pd.DataFrame #18788

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c23482c
DOC: standardizing docstrings to use pd.DataFrame
accraze Dec 15, 2017
71fd9ee
fix docstring spacing
accraze Dec 16, 2017
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18 changes: 9 additions & 9 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2304,7 +2304,7 @@ def query(self, expr, inplace=False, **kwargs):
--------
>>> from numpy.random import randn
>>> from pandas import DataFrame
>>> df = DataFrame(randn(10, 2), columns=list('ab'))
>>> df = pd.DataFrame(randn(10, 2), columns=list('ab'))
>>> df.query('a > b')
>>> df[df.a > df.b] # same result as the previous expression
"""
Expand Down Expand Up @@ -2368,7 +2368,7 @@ def eval(self, expr, inplace=False, **kwargs):
--------
>>> from numpy.random import randn
>>> from pandas import DataFrame
>>> df = DataFrame(randn(10, 2), columns=list('ab'))
>>> df = pd.DataFrame(randn(10, 2), columns=list('ab'))
>>> df.eval('a + b')
>>> df.eval('c = a + b')
"""
Expand Down Expand Up @@ -2664,7 +2664,7 @@ def assign(self, **kwargs):

Examples
--------
>>> df = DataFrame({'A': range(1, 11), 'B': np.random.randn(10)})
>>> df = pd.DataFrame({'A': range(1, 11), 'B': np.random.randn(10)})

Where the value is a callable, evaluated on `df`:

Expand Down Expand Up @@ -3780,7 +3780,7 @@ def nlargest(self, n, columns, keep='first'):

Examples
--------
>>> df = DataFrame({'a': [1, 10, 8, 11, -1],
>>> df = pd.DataFrame({'a': [1, 10, 8, 11, -1],
... 'b': list('abdce'),
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@gfyoung gfyoung Dec 15, 2017 •
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Although this won't fail, but style-wise, notice how the "a", "b", and "c" rows are aligned and start at that same location on their respective lines. Let's keep it that way (i.e. adjust the "b" and "c" rows).

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Follow this comment for one of your other fixes down below (the "column=['a', 'b']").

... 'c': [1.0, 2.0, np.nan, 3.0, 4.0]})
>>> df.nlargest(3, 'a')
Expand Down Expand Up @@ -3815,7 +3815,7 @@ def nsmallest(self, n, columns, keep='first'):

Examples
--------
>>> df = DataFrame({'a': [1, 10, 8, 11, -1],
>>> df = pd.DataFrame({'a': [1, 10, 8, 11, -1],
... 'b': list('abdce'),
... 'c': [1.0, 2.0, np.nan, 3.0, 4.0]})
>>> df.nsmallest(3, 'a')
Expand Down Expand Up @@ -5818,7 +5818,7 @@ def quantile(self, q=0.5, axis=0, numeric_only=True,
Examples
--------

>>> df = DataFrame(np.array([[1, 1], [2, 10], [3, 100], [4, 100]]),
>>> df = pd.DataFrame(np.array([[1, 1], [2, 10], [3, 100], [4, 100]]),
columns=['a', 'b'])
>>> df.quantile(.1)
a 1.3
Expand Down Expand Up @@ -5941,7 +5941,7 @@ def isin(self, values):
--------
When ``values`` is a list:

>>> df = DataFrame({'A': [1, 2, 3], 'B': ['a', 'b', 'f']})
>>> df = pd.DataFrame({'A': [1, 2, 3], 'B': ['a', 'b', 'f']})
>>> df.isin([1, 3, 12, 'a'])
A B
0 True True
Expand All @@ -5950,7 +5950,7 @@ def isin(self, values):

When ``values`` is a dict:

>>> df = DataFrame({'A': [1, 2, 3], 'B': [1, 4, 7]})
>>> df = pd.DataFrame({'A': [1, 2, 3], 'B': [1, 4, 7]})
>>> df.isin({'A': [1, 3], 'B': [4, 7, 12]})
A B
0 True False # Note that B didn't match the 1 here.
Expand All @@ -5959,7 +5959,7 @@ def isin(self, values):

When ``values`` is a Series or DataFrame:

>>> df = DataFrame({'A': [1, 2, 3], 'B': ['a', 'b', 'f']})
>>> df = pd.DataFrame({'A': [1, 2, 3], 'B': ['a', 'b', 'f']})
>>> other = DataFrame({'A': [1, 3, 3, 2], 'B': ['e', 'f', 'f', 'e']})
>>> df.isin(other)
A B
Expand Down