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Dec 10, 2018
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DOC: Repair doc/source/merging.rst flake8 issues #24185

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5a09ad8
Repair merging.rst flake8 issues, remove exclusion from config
addisonlynch Dec 9, 2018
077276e
flake8 fixes
addisonlynch Dec 9, 2018
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51 changes: 25 additions & 26 deletions doc/source/merging.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -39,19 +39,19 @@ a simple example:
'B': ['B0', 'B1', 'B2', 'B3'],
'C': ['C0', 'C1', 'C2', 'C3'],
'D': ['D0', 'D1', 'D2', 'D3']},
index=[0, 1, 2, 3])
index=[0, 1, 2, 3])

df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],
'B': ['B4', 'B5', 'B6', 'B7'],
'C': ['C4', 'C5', 'C6', 'C7'],
'D': ['D4', 'D5', 'D6', 'D7']},
index=[4, 5, 6, 7])
index=[4, 5, 6, 7])

df3 = pd.DataFrame({'A': ['A8', 'A9', 'A10', 'A11'],
'B': ['B8', 'B9', 'B10', 'B11'],
'C': ['C8', 'C9', 'C10', 'C11'],
'D': ['D8', 'D9', 'D10', 'D11']},
index=[8, 9, 10, 11])
index=[8, 9, 10, 11])

frames = [df1, df2, df3]
result = pd.concat(frames)
Expand Down Expand Up @@ -380,7 +380,7 @@ Through the ``keys`` argument we can override the existing column names.

.. ipython:: python

pd.concat([s3, s4, s5], axis=1, keys=['red','blue','yellow'])
pd.concat([s3, s4, s5], axis=1, keys=['red', 'blue', 'yellow'])

Let's consider a variation of the very first example presented:

Expand Down Expand Up @@ -437,8 +437,8 @@ do so using the ``levels`` argument:
.. ipython:: python

result = pd.concat(pieces, keys=['x', 'y', 'z'],
levels=[['z', 'y', 'x', 'w']],
names=['group_key'])
levels=[['z', 'y', 'x', 'w']],
names=['group_key'])

.. ipython:: python
:suppress:
Expand Down Expand Up @@ -726,9 +726,9 @@ Here is another example with duplicate join keys in DataFrames:

.. ipython:: python

left = pd.DataFrame({'A' : [1,2], 'B' : [2, 2]})
left = pd.DataFrame({'A': [1, 2], 'B': [2, 2]})

right = pd.DataFrame({'A' : [4,5,6], 'B': [2,2,2]})
right = pd.DataFrame({'A': [4, 5, 6], 'B': [2, 2, 2]})

result = pd.merge(left, right, on='B', how='outer')

Expand Down Expand Up @@ -801,8 +801,8 @@ that takes on values:

.. ipython:: python

df1 = pd.DataFrame({'col1': [0, 1], 'col_left':['a', 'b']})
df2 = pd.DataFrame({'col1': [1, 2, 2],'col_right':[2, 2, 2]})
df1 = pd.DataFrame({'col1': [0, 1], 'col_left': ['a', 'b']})
df2 = pd.DataFrame({'col1': [1, 2, 2], 'col_right': [2, 2, 2]})
pd.merge(df1, df2, on='col1', how='outer', indicator=True)

The ``indicator`` argument will also accept string arguments, in which case the indicator function will use the value of the passed string as the name for the indicator column.
Expand Down Expand Up @@ -857,19 +857,18 @@ The left frame.
X = X.astype(CategoricalDtype(categories=['foo', 'bar']))

left = pd.DataFrame({'X': X,
'Y': np.random.choice(['one', 'two', 'three'], size=(10,))})
'Y': np.random.choice(['one', 'two', 'three'],
size=(10,))})
left
left.dtypes

The right frame.

.. ipython:: python

right = pd.DataFrame({
'X': pd.Series(['foo', 'bar'],
dtype=CategoricalDtype(['foo', 'bar'])),
'Z': [1, 2]
})
right = pd.DataFrame({'X': pd.Series(['foo', 'bar'],
dtype=CategoricalDtype(['foo', 'bar'])),
'Z': [1, 2]})
right
right.dtypes

Expand Down Expand Up @@ -903,11 +902,11 @@ potentially differently-indexed ``DataFrames`` into a single result

left = pd.DataFrame({'A': ['A0', 'A1', 'A2'],
'B': ['B0', 'B1', 'B2']},
index=['K0', 'K1', 'K2'])
index=['K0', 'K1', 'K2'])

right = pd.DataFrame({'C': ['C0', 'C2', 'C3'],
'D': ['D0', 'D2', 'D3']},
index=['K0', 'K2', 'K3'])
index=['K0', 'K2', 'K3'])

result = left.join(right)

Expand Down Expand Up @@ -999,7 +998,7 @@ join key), using ``join`` may be more convenient. Here is a simple example:

right = pd.DataFrame({'C': ['C0', 'C1'],
'D': ['D0', 'D1']},
index=['K0', 'K1'])
index=['K0', 'K1'])

result = left.join(right, on='key')

Expand Down Expand Up @@ -1038,8 +1037,8 @@ To join on multiple keys, the passed DataFrame must have a ``MultiIndex``:
index = pd.MultiIndex.from_tuples([('K0', 'K0'), ('K1', 'K0'),
('K2', 'K0'), ('K2', 'K1')])
right = pd.DataFrame({'C': ['C0', 'C1', 'C2', 'C3'],
'D': ['D0', 'D1', 'D2', 'D3']},
index=index)
'D': ['D0', 'D1', 'D2', 'D3']},
index=index)

Now this can be joined by passing the two key column names:

Expand Down Expand Up @@ -1134,12 +1133,12 @@ the left argument, as in this example:

leftindex = pd.MultiIndex.from_product([list('abc'), list('xy'), [1, 2]],
names=['abc', 'xy', 'num'])
left = pd.DataFrame({'v1' : range(12)}, index=leftindex)
left = pd.DataFrame({'v1': range(12)}, index=leftindex)
left

rightindex = pd.MultiIndex.from_product([list('abc'), list('xy')],
names=['abc', 'xy'])
right = pd.DataFrame({'v2': [100*i for i in range(1, 7)]}, index=rightindex)
right = pd.DataFrame({'v2': [100 * i for i in range(1, 7)]}, index=rightindex)
right

left.join(right, on=['abc', 'xy'], how='inner')
Expand All @@ -1154,17 +1153,17 @@ done using the following code.
names=['key', 'X'])
left = pd.DataFrame({'A': ['A0', 'A1', 'A2'],
'B': ['B0', 'B1', 'B2']},
index=leftindex)
index=leftindex)

rightindex = pd.MultiIndex.from_tuples([('K0', 'Y0'), ('K1', 'Y1'),
('K2', 'Y2'), ('K2', 'Y3')],
names=['key', 'Y'])
right = pd.DataFrame({'C': ['C0', 'C1', 'C2', 'C3'],
'D': ['D0', 'D1', 'D2', 'D3']},
index=rightindex)
index=rightindex)

result = pd.merge(left.reset_index(), right.reset_index(),
on=['key'], how='inner').set_index(['key','X','Y'])
on=['key'], how='inner').set_index(['key', 'X', 'Y'])

.. ipython:: python
:suppress:
Expand Down
1 change: 0 additions & 1 deletion setup.cfg
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Original file line number Diff line number Diff line change
Expand Up @@ -83,7 +83,6 @@ exclude =
doc/source/enhancingperf.rst
doc/source/groupby.rst
doc/source/indexing.rst
doc/source/merging.rst
doc/source/missing_data.rst
doc/source/options.rst
doc/source/release.rst
Expand Down