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Apr 16, 2023
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DOC add example of Series.index #51842

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48 changes: 48 additions & 0 deletions pandas/core/series.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5993,6 +5993,54 @@ def mask(

index = properties.AxisProperty(
axis=0, doc="The index (axis labels) of the Series."
"""
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Can you make this a single text, not concatenating in this way please?

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Sorry, but didn't understand. You mean like this ?
axis=0, doc="The index (axis labels) of the Series." """ A one-dimensional ndarray with hashable type axis labels. """

or this

axis=0, doc="The index (axis labels) of the Series."
""" A one-dimensional ndarray with hashable type axis labels. """

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@ggold7046

Could you please use triple backticks to format code blocks? Without it, your question is really hard to read.

What @datapythonista means is that you have two strings here that will be concatenated:

a = (
    "The index [...]"
    """

    A one-dimensional [...]
    """
)
print(a)
The index [...]

    A one-dimensional [...]

Since you already have a multiline string (triple quotes), you can just merge the two:

b = """\
The index [...]

A one-dimensional [...]
"""
print(b)
The index [...]

A one-dimensional [...]


A one-dimensional ndarray with hashable type axis labels.

Pandas Series.index attribute is used to get or set the index labels of the given Series object.
The object supports both integer- and label-based indexing and provides a host of methods for performing
operations involving the index.
The labels need not be unique but must be of the hashable type.

Returns
-------
index

Examples
--------

**Use the Series.index attribute to set the index label for the given Series object.**

>>> s = pd.Series(['Kolkata', 'Chicago', 'Toronto', 'Lisbon'])
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This example is not very realistic and confusing with the City 1, City 2 labels. Maybe something like using the city as index and then making the value a feature like population, average temperature... would make more sense.

Also, since here you're just showing the .index accessor, better create the index with Series(..., index=...) and simply show that your_series.index returns the index.

>>> print(s)
0 Kolkata
1 Chicago
2 Toronto
3 Lisbon
dtype: object

The ``Series.index`` attribute will now be used to set the index label for the given object.

>>> s.index = ['City 1', 'City 2', 'City 3', 'City 4']
>>> print(s)
City 1 Kolkata
City 2 Chicago
City 3 Toronto
City 4 Lisbon
dtype: object

As we can see in the output, the ``Series.index`` attribute has successfully set the index labels for the given Series object.

**We can also assign duplicate or nonunique indexes in Pandas.**

>>> s.index = ['City 1', 'City 1', 'City 3', 'City 3']
>>> print(s)
City 1 Kolkata
City 1 Chicago
City 3 Toronto
City 3 Lisbon
dtype: object
"""
)

# ----------------------------------------------------------------------
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