Pandas Series

A Series is a one-dimensional labeled data structure that can contain data of any type (integer, float, etc.). The labels are known as index. A Series contain homogeneous data.

A Series can be visualized as a one-dimensional NumPy array, for example:

Red

Blue

Green

Black

Yellow

White

Brown

The size of a Series is immutable but data values are mutable.

Creating a Series

The syntax for creating a Pandas Series is:

pandas.DataFrame( data, index, dtype, copy)

data, index, columns, dtype, copy are its parameters –

• data can take constant values or lists, ndarray, etc.
• index contains the unique indexing values
• dtype is the for the data type of the series
• copy is for copying of data

Pandas Series can be created from constant values, lists, maps, dictionary, ndarray, etc. Let us look at some basic examples of creating a Series.

Creating an empty Series

import pandas as pd # creating an empty Series series = pd.Series() print(series)

The output obtained is:

Series([], dtype: float64)

Creating a Series using list

import pandas as pd # creating a Series using list student = [‘John’,15,87.5] series = pd.Series(student) print(series)

This gives the following output:

0 John 1 15 2 87.5 dtype: object

Creating a Series using list with labels

import pandas as pd # creating a Series using list with labels student = [‘John’,15,87.5] labels = [‘Name’,’Age’,’Marks’] series = pd.Series(student,labels) print(series)

Output is:

Name John Age 15 Marks 87.5 dtype: object

Creating a Series using Dictionary

import pandas as pd # a dictionary student = {‘Name’: ‘John’, ‘Age’: 20, ‘Marks’: 87.5} # creating a Series using dictionary series = pd.Series(student,index=[‘Name’,’Age’,’Country’,’Marks’]) print(series)

The output obtained is as follows:

Name John Age 20 Country NaN Marks 87.5 dtype: object

The missing values are filled with NaN.

Summary

In this article, we have looked at the main data structures of Pandas – Series. In the upcoming articles, we will focus on more operations on DataFrame and Series.