Pandas on Ghafoor's Personal Blog

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.

Data With Pandas

noreply@example.com (AG Sayyed) — Thu, 24 Jul 2025 13:11:46 +0000

This document covers techniques for analyzing and filtering data in Pandas, including finding unique values in columns, filtering rows based on conditions, and saving results to CSV and other formats. Readers will learn practical steps for working with large datasets efficiently.

Working With DataFrames in Pandas

Pandas enables efficient data analysis and manipulation using DataFrames. Once a DataFrame is created, various methods can be applied to explore and process the data.

Pandas

noreply@example.com (AG Sayyed) — Thu, 24 Jul 2025 12:50:06 +0000

Pandas is a powerful Python library for data analysis and manipulation. This document explains how to import Pandas, read CSV and Excel files, create and work with DataFrames, and efficiently access and slice data using various indexing methods. Readers will learn practical techniques for handling tabular data in Python.

Introduction to Pandas

Pandas is a widely used Python library that provides tools for data analysis and manipulation. It offers pre-built classes and functions to simplify working with structured data, such as tables and spreadsheets. Importing Pandas is done using the import command, and it is common to use the abbreviation pd for convenience.