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Data Wrangling with Python: Streamlining Raw Data to Actionable Insights

Data Wrangling with Python is the ultimate guide for transforming raw data into valuable, actionable insights. This comprehensive book is designed for developers, data analysts, and business analysts looking to enhance their data science skills. With a focus on hands-on learning, this resource provides an in-depth exploration of the essential tools and techniques for data wrangling using Python. Key features include a focus on data structures, efficient data extraction methods, and practical tips for data hygiene.

• Master essential data structures
• Utilize NumPy and Pandas for data manipulation
• Discover advanced string search and manipulation techniques

Unlock the Full Potential of Data with Python

Delve into the world of data wrangling with Python, where you'll learn to harness the power of this versatile programming language. The book starts with the basics of Python and quickly progresses to the most popular data wrangling libraries, NumPy and Pandas. You'll gain insights into the best practices for data cleaning and discover how to effectively extract, transform, and format data from a variety of sources. Advanced topics covered include web scraping, data integrity checks, and descriptive statistics.

• Enhance your learning curve with bonus topics
• Understand the importance of data integrity
• Implement web scraping with BeautifulSoup4 and html5lib

Empower Your Data Science Career with Real-World Skills

Whether you're a beginner or an experienced data professional, Data Wrangling with Python will help you achieve your data science goals. This book is tailored for those eager to pursue a career as a full-fledged data scientist or analytics expert, providing you with the skills to extract, clean, and transform data efficiently. By the end of this book, you'll be well-equipped to handle real-world data challenges and apply your newfound knowledge to various industries. Target audience includes developers, data analysts, and business analysts with a basic understanding of Python and relational databases.

• Developers looking to enhance their data science skills
• Data analysts seeking to streamline their data processing workflows
• Business analysts aiming to make data-driven decisions