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.


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:


Attributes

Method

Meaning

index

RangeIndex containing the member indices

is_unique

bool representing if all member values are unique

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

mean

return mean value

product

return product from multiplying all member values

std

return standard deviation of values

sum

return sum from adding all member values


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