DOC: standardizing docstrings to use pd.DataFrame (#18788) · pandas-dev/pandas@b5f1e71 (original) (raw)
`@@ -2304,7 +2304,7 @@ def query(self, expr, inplace=False, **kwargs):
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` --------
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` >>> from numpy.random import randn
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` >>> from pandas import DataFrame
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``
`-
df = DataFrame(randn(10, 2), columns=list('ab'))
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``
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`+
df = pd.DataFrame(randn(10, 2), columns=list('ab'))
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` >>> df.query('a > b')
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` >>> df[df.a > df.b] # same result as the previous expression
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` """
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`@@ -2368,7 +2368,7 @@ def eval(self, expr, inplace=False, **kwargs):
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` --------
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` >>> from numpy.random import randn
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` >>> from pandas import DataFrame
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``
`-
df = DataFrame(randn(10, 2), columns=list('ab'))
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``
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`+
df = pd.DataFrame(randn(10, 2), columns=list('ab'))
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` >>> df.eval('a + b')
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` >>> df.eval('c = a + b')
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` """
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`@@ -2664,7 +2664,7 @@ def assign(self, **kwargs):
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``
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` Examples
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` --------
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``
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df = DataFrame({'A': range(1, 11), 'B': np.random.randn(10)})
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``
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`+
df = pd.DataFrame({'A': range(1, 11), 'B': np.random.randn(10)})
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``
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`` Where the value is a callable, evaluated on df:
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``
`@@ -3780,9 +3780,9 @@ def nlargest(self, n, columns, keep='first'):
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``
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` Examples
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` --------
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``
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df = DataFrame({'a': [1, 10, 8, 11, -1],
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``
`-
... 'b': list('abdce'),
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``
`-
... 'c': [1.0, 2.0, np.nan, 3.0, 4.0]})
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df = pd.DataFrame({'a': [1, 10, 8, 11, -1],
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... 'b': list('abdce'),
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... 'c': [1.0, 2.0, np.nan, 3.0, 4.0]})
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` >>> df.nlargest(3, 'a')
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` a b c
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` 3 11 c 3
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`@@ -3815,9 +3815,9 @@ def nsmallest(self, n, columns, keep='first'):
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``
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` Examples
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` --------
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``
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df = DataFrame({'a': [1, 10, 8, 11, -1],
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``
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... 'b': list('abdce'),
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``
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... 'c': [1.0, 2.0, np.nan, 3.0, 4.0]})
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df = pd.DataFrame({'a': [1, 10, 8, 11, -1],
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... 'b': list('abdce'),
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... 'c': [1.0, 2.0, np.nan, 3.0, 4.0]})
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` >>> df.nsmallest(3, 'a')
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` a b c
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` 4 -1 e 4
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`@@ -5818,7 +5818,7 @@ def quantile(self, q=0.5, axis=0, numeric_only=True,
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` Examples
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` --------
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``
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``
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df = DataFrame(np.array([[1, 1], [2, 10], [3, 100], [4, 100]]),
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df = pd.DataFrame(np.array([[1, 1], [2, 10], [3, 100], [4, 100]]),
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` columns=['a', 'b'])
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` >>> df.quantile(.1)
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` a 1.3
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`@@ -5941,7 +5941,7 @@ def isin(self, values):
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` --------
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``` When values is a list:
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``
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``
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>>> df = DataFrame({'A': [1, 2, 3], 'B': ['a', 'b', 'f']})
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``
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`+
>>> df = pd.DataFrame({'A': [1, 2, 3], 'B': ['a', 'b', 'f']})
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` >>> df.isin([1, 3, 12, 'a'])
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` A B
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` 0 True True
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`@@ -5950,7 +5950,7 @@ def isin(self, values):
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``
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``` When ``values`` is a dict:
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``
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``
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df = DataFrame({'A': [1, 2, 3], 'B': [1, 4, 7]})
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`+
df = pd.DataFrame({'A': [1, 2, 3], 'B': [1, 4, 7]})
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` >>> df.isin({'A': [1, 3], 'B': [4, 7, 12]})
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` A B
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` 0 True False # Note that B didn't match the 1 here.
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`@@ -5959,7 +5959,7 @@ def isin(self, values):
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``
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``` When values is a Series or DataFrame:
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``
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``
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df = DataFrame({'A': [1, 2, 3], 'B': ['a', 'b', 'f']})
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df = pd.DataFrame({'A': [1, 2, 3], 'B': ['a', 'b', 'f']})
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` >>> other = DataFrame({'A': [1, 3, 3, 2], 'B': ['e', 'f', 'f', 'e']})
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` >>> df.isin(other)
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` A B
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