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Mar 15, 2018
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DOC: update the Series.reset_index DocString #20107

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DOC: update the Series.reset_index DocString
ludusrusso Mar 10, 2018
291b5c0
solved pep issues
ludusrusso Mar 10, 2018
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fix typos and unnecessary quotes
ludusrusso Mar 10, 2018
4e70101
add examples for drop=True
ludusrusso Mar 10, 2018
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up description
ludusrusso Mar 10, 2018
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add more examples and fix some typos in description
ludusrusso Mar 10, 2018
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add comments to examples, improved docs
ludusrusso Mar 10, 2018
28974ac
fix typo
ludusrusso Mar 10, 2018
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up descirption
ludusrusso Mar 10, 2018
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update docs according to reviews
ludusrusso Mar 11, 2018
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Updates [ci skip]
TomAugspurger Mar 15, 2018
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TomAugspurger Mar 15, 2018
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39 changes: 28 additions & 11 deletions pandas/core/series.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1002,24 +1002,34 @@ def _set_value(self, label, value, takeable=False):

def reset_index(self, level=None, drop=False, name=None, inplace=False):
"""
Analogous to the :meth:`pandas.DataFrame.reset_index` function, see
docstring there.
Reset the index of the Serie.
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General comment: Serie -> Series (the singular of Series is still Series :))

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Solved tnx!

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Did you already push? Because this one is not yet fixed

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Sorry, I missed it!


For a standard index, the index name will be used (if set),
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just say Index

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ok

otherwise a default index or `level_0` (if `index` is already taken)
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the default IS 'index', can you make this a bit more clear

will be used.
For a Series with multi-level index, return a new Series with labeling
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say MultiIndex

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done

information in the columns under the index names, defaulting to
`level_0`, `level_1`, etc. if any are None.

Parameters
----------
level : int, str, tuple, or list, default None
level : int, str, tuple, or list, default `None`
Only remove the given levels from the index. Removes all levels by
default
drop : boolean, default False
Do not try to insert index into dataframe columns
name : object, default None
The name of the column corresponding to the Series values
inplace : boolean, default False
Modify the Series in place (do not create a new object)
default.
drop : `boolean`, default `False`
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boolean -> bool

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tnx

Do not try to insert index into dataframe columns.
name : `object`, default `None`
The name of the column corresponding to the Series values.
inplace : `boolean`, default `False`
Modify the Series in place (do not create a new object).

Returns
----------
resetted : DataFrame, or Series if drop == True
resetted : `DataFrame`, or Series if `drop == True`
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Resetted should probably just "reset"

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ok!


See Also
--------
pandas.DataFrame.reset_index: Analogous function for DataFrame
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link to pandas.Series.set_index as well

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Series does not have a method set_index(), did you mean DataFrame.set_index()?

s.set_index()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/ludus/develop/pandas-meetup/pandas/pandas/core/generic.py", line 4046, in __getattr__
    return object.__getattribute__(self, name)
AttributeError: 'Series' object has no attribute 'set_index'


Examples
--------
Expand All @@ -1032,6 +1042,13 @@ def reset_index(self, level=None, drop=False, name=None, inplace=False):
2 c 3
3 d 4

>>> s.reset_index(drop=True)
0 1
1 2
2 3
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can you add an example with name

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Done, for name and for inplace

3 4
dtype: int64

>>> arrays = [np.array(['bar', 'bar', 'baz', 'baz', 'foo',
... 'foo', 'qux', 'qux']),
... np.array(['one', 'two', 'one', 'two', 'one', 'two',
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If I'm not wrong, just 4 rows should be enough to illustrate the example. That would make it more compact, and easier to understand for the user.

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You're right, that was an existing example!

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