Pandas Data Structure (Python Pandas -I ) | Data Handling Using Pandas | Class 11 | Class 12 | CBSE | Informatics Practices | Notes | Study Material

Pandas Data Structure

Data Structure:

    A data structure is a particular way of storing and organizing data in a computer to suit a specific purpose so that it can be accessed and worked with in appropriate ways.

    Two Basic data Structures:

        1. Series

        2. DataFrame

        3. Panel

Series Vs DataFrame:

Property	Series	DataFrame
Dimensions	1 - Dimensional	2-Dimentional
Type of data	1.Homogeneous 2.All the elements must be of same type in a series object	1.Heterogenoues 2.DataFrame object can have elements of different data types
Mutability	Values Mutable: Their elements value can change Size-immutable, i.e., size of a Series object, once created, cannot change. If you want to add/drop an element, internally a new Series object will be created.	Values Mutable: Their elements value can change Size-mutable, i.e., size of a DataFrame object, once created, can change in place. That is, you can add/drop elements in an existing DataFrame object.

import both pandas and numpy modules/libraries by giving following import statements

import pandas as pd
import numpy as np

Module

• A module is a single file (or script) that contains Python code. This file could include functions, classes, variables, and runnable code. Essentially, a module is a file that you can import and use in your own Python programs.

• Example:

• math is a module that provides mathematical functions like sqrt() and sin().

• pandas itself is a module.

Library

• A library is a collection of modules that are grouped together to provide specific functionality. A library can contain one or more modules, and it’s essentially a broader package of tools that you can use in your programs.

• Example:

• Pandas is a library, and within it, there are multiple modules (like pandas.core, pandas.io, etc.).

Key Difference:

• Module: A single file of code (e.g., pandas.py).

• Library: A collection of modules (e.g., the entire pandas library includes many modules).

In Python, the terms module and library are often used interchangeably, but they have slightly different meanings. Here's a simple explanation:

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