Pandas Series

External

• https://pandas.pydata.org/docs/user_guide/dsintro.html#series
• https://pandas.pydata.org/docs/reference/api/pandas.Series.html#pandas.Series
• https://www.geeksforgeeks.org/python-pandas-series/

Internal

• Pandas Concepts
• DataFrame

Overview

A series is a one-dimensional array of values, where each value has a label. The labels are referred to as "axis labels" and they are managed by the series's index. By default, in absence of any explicit specification, a series gets a monotonic integer range index, starting with 0 and with the step 1, allowing retrieving data with 0-based integer indexes (see Accessing Elements of a Series below).

Data stored in series can be

Index

https://pandas.pydata.org/docs/reference/api/pandas.Series.index.html

RangeIndex

RangeIndex

Time Series Index

An index that contains datetime turns the A time series is a series whose index has datetime objects. To create a time series, ensure that the method that creates the series performs the conversion automatically, as show in the Create a Time Series from CSV section.

Create a Series

From a in-Memory List

A series can be created from an in-memory list:

import pandas as pd

a = ['a', 'b', 'c']
s = pd.Series(a)

A series can also be created from data stored externally.

Create a Series from CSV

https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html#pandas.read_csv

To create a series from a CSV file:

import pandas as pd

# TODO

Create a Series from JSON

Parse: https://pandas.pydata.org/docs/reference/api/pandas.read_json.html#pandas.read_json

Also see:

datetime

Accessing Elements of a Series

This is known as indexing or subset selection.

Operations on Series

Transformation

This class of operations are referred to as transformations or conversions.