### Unit 2 - Introduction to data structures in Pandas

CBSE Revision Notes

Class-11 Informatics Practices (New Syllabus)
Unit 2: Data Handling (DH-1)

Introduction to data structures in Pandas

Pandas is an open-source, BSD-licensed Python library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Python with Pandas is used in a wide range of fields including academic and commercial domains including finance, economics, Statistics, analytics, etc.

Pandas deals with the following three data structures −

• Series
• DataFrame
• Panel

These data structures are built on top of Numpy array, which means they are fast.

Dimension & Description

The best way to think of these data structures is that the higher dimensional data structure is a container of its lower dimensional data structure. For example, DataFrame is a container of Series, Panel is a container of DataFrame.

Data StructureDimensionsDescription
Series11D labeled homogeneous array, sizeimmutable.
Data Frames2General 2D labeled, size-mutable tabular structure with potentially heterogeneously typed columns.
Panel3General 3D labeled, size-mutable array.

Building and handling two or more dimensional arrays is a tedious task, burden is placed on the user to consider the orientation of the data set when writing functions. But using Pandas data structures, the mental effort of the user is reduced.

For example, with tabular data (DataFrame) it is more semantically helpful to think of the index (the rows) and the columns rather than axis 0 and axis 1.

Mutability

All Pandas data structures are value mutable (can be changed) and except Series all are size mutable. Series is size immutable.

Note − DataFrame is widely used and one of the most important data structures. Panel is used much less.

Series

Series is a one-dimensional array like structure with homogeneous data. For example, the following series is a collection of integers 10, 23, 56, …

 10 23 56 17 52 61 73 90 26 72

Key Points

• Homogeneous data
• Size Immutable
• Values of Data Mutable

DataFrame

DataFrame is a two-dimensional array with heterogeneous data. For example,

NameAgeGenderRating
Steve32Male3.45
Lia28Female4.6
Vin45Male3.9
Katie38Female2.78

The table represents the data of a sales team of an organization with their overall performance rating. The data is represented in rows and columns. Each column represents an attribute and each row represents a person.

Data Type of Columns

The data types of the four columns are as follows −

ColumnType
NameString
AgeInteger
GenderString
RatingFloat

Key Points

• Heterogeneous data
• Size Mutable
• Data Mutable

Panel

Panel is a three-dimensional data structure with heterogeneous data. It is hard to represent the panel in graphical representation. But a panel can be illustrated as a container of DataFrame.

Key Points

• Heterogeneous data
• Size Mutable
• Data Mutable