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||`index` ||[[Python/Pandas/Types|RangeIndex]] containing the member indices || ||`iloc` ||[[Python/Pandas/Types#A_ILocIndexer|indexable accessor of member values]] ||
||`index` ||[[Python/Pandas/Types|RangeIndex]] containing the member indices      ||
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||`size` ||[[Python/Builtins/Types#Int|int]] count of member values                                   || ||`loc` ||[[Python/Pandas/Types#A_LocIndexer|indexable accessor of member values]] ||
||`size` ||[[Python/Builtins/Types#Int|int]] count of member values ||
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||`get` ||return the value from an index or a default ||`s.get("foo", default=None)` ||
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||`sort_values`||return a sorted `Series` ||`s.sort_values(ascending=False)`|| ||`sort_index` ||return a `Series` sorted by indices ||`s.sort_index(ascending=True)` ||
||`sort_values`||return a `Series` sorted by values ||`s.sort_values(ascending=True)` ||
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Note that the `get` method can take a list of indices to look up. A new `Series` will be returned if all indices exist, and the singleton default will be returned otherwise.

Python Pandas Series

A Series is an ordered collection of somewhat-uniform data that can be indexed.

The type is fully specified as pandas.core.series.Series.

Contents

  1. Python Pandas Series
    1. Example
    2. Data Model
      1. Index
      2. DType
      3. Dunder Methods
    3. Attributes
    4. Methods

Example

import pandas as pd

pd.Series(["foo", "bar", "baz"])  # 0   foo
                                  # 1   bar
                                  # 2   baz
                                  # dtype: object

Data Model

A Series can be instantiated with any iterable.

Index

By default, a series is indexed by a sequential integer (beginning at 0).

Certain iterables are interpreted as pairs of indices and values. 

d = {"First": "foo", "Second": "bar", "Third": "baz"}
s = pd.Series(d)  # First    foo
                  # Second   bar
                  # Third    baz
                  # dtype: object

A second iterable can be specified as explicit indices. 

d = ["foo", "bar", "baz"]
i = ["First", "Second", "Third"]
s = pd.Series(d, i)
s = pd.Series(d, index=i)
s = pd.Series(data=d, index=i)

DType

A series without significant consistency of data types with initialize with a dtype of object. Alternatives include:

  • int64

  • float64

  • datetime64

  • bool

  • category

Dunder Methods

Series objects support all of the dunder methods implied by a sequence, e.g. len() and sorted().

Attributes

Method

Meaning

iloc

indexable accessor of member values

index

RangeIndex containing the member indices

is_unique

bool representing if all member values are unique

loc

indexable accessor of member values

size

int count of member values

values

numpy.ndarray containing the member values

Methods

These methods return numpy.float64 values unless otherwise specified.

Method

Meaning

Example

get

return the value from an index or a default

s.get("foo", default=None)

head

return a Series of the first N member values

s.head(5)

mean

return mean value

product

return product from multiplying all member values

sort_index

return a Series sorted by indices

s.sort_index(ascending=True)

sort_values

return a Series sorted by values

s.sort_values(ascending=True)

std

return standard deviation of values

sum

return sum from adding all member values

tail

return a Series of the last N member values

s.tail(5)

Note that the get method can take a list of indices to look up. A new Series will be returned if all indices exist, and the singleton default will be returned otherwise.

CategoryRicottone