Module-5 on Ghafoor's Personal Blog

Module Summary

noreply@example.com (AG Sayyed) — Fri, 25 Jul 2025 06:58:18 +0000

This document summarizes essential concepts in Python APIs, data manipulation with Pandas, web scraping, HTTP methods, and file formats. It provides a structured overview of their roles and practical applications in Python data science development.

Module Summary

APIs and Data Access in Python

APIs (Application Programming Interfaces) in Python provide simple and efficient ways to interact with external services, libraries, and data sources. Using libraries such as requests, Python can send HTTP requests, retrieve data, and parse responses. APIs enable seamless integration with web services, databases, and cloud resources.

File Formats

noreply@example.com (AG Sayyed) — Fri, 25 Jul 2025 06:51:38 +0000

This document covers the essential file formats used in data science, such as CSV, JSON, and Excel. It explains their structure, how to read and write them in Python, and the advantages and limitations of each format for data storage and exchange.

Introduction

File formats are fundamental to data science, enabling the storage, exchange, and analysis of data. Understanding the structure and use cases of different file formats is crucial for efficient data handling.

Web Scraping

noreply@example.com (AG Sayyed) — Thu, 24 Jul 2025 20:36:23 +0000

This document provides a practical guide to web scraping with Python. It covers sending HTTP requests, parsing HTML, extracting structured data, and using libraries like requests, BeautifulSoup, and pandas. Readers will learn how to automate data collection and follow ethical scraping practices.

Introduction

Web scraping is the process of programmatically extracting information from websites. It is widely used for data collection, price monitoring, content aggregation, and research. Python offers powerful libraries for web scraping, enabling efficient and automated data extraction from web pages.

Rest Api

noreply@example.com (AG Sayyed) — Thu, 24 Jul 2025 14:07:03 +0000

This document covers the use of the Python Requests library for HTTP communication, including GET and POST requests, query strings, request and response objects, and practical examples for interacting with web APIs.

Introduction to the Requests Library

The Requests library in Python simplifies sending HTTP/1.1 requests. It supports GET and POST methods, allowing easy interaction with web servers and APIs.

Making GET Requests

Import the library and send a GET request:

HTTP Protocols and REST APIs

noreply@example.com (AG Sayyed) — Thu, 24 Jul 2025 14:01:59 +0000

This document covers the fundamentals of REST APIs, the HTTP protocol, URL structure, request and response cycles, status codes, and HTTP methods. Readers will learn how web communication works and how REST APIs facilitate data transfer between clients and servers.

Introduction to HTTP and REST APIs

The HTTP protocol is a standard for transferring information over the web, including REST APIs. REST APIs operate by sending requests and receiving responses using HTTP messages, often containing JSON data.

Api

noreply@example.com (AG Sayyed) — Thu, 24 Jul 2025 13:58:24 +0000

This document covers the fundamentals of APIs, API libraries, and REST APIs in Python, including request and response cycles, practical usage with PyCoinGecko, and time series analysis with pandas. Readers will learn how APIs enable communication between software components and how to process and visualize data from web services.

Introduction to APIs

An Application Programming Interface (API) allows different software components to communicate by exchanging inputs and outputs. APIs abstract the internal workings, enabling users to interact with software through defined methods and data structures.