通达科技 - 宜兴电脑维护及IT服务外包服务商

Simplify your ETL processes with these hands-on data hygiene tips, tricks, and best practices.
　　Key Features
　　·Focus on the basics of data wrangling
　　·Study various ways to extract the most out of your data in less time
　　·Boost your learning curve with bonus topics like random data generation and data integrity checks
　　Book Description
　　For data to be useful and meaningful, it must be curated and refined. Data Wrangling with Python teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain.
　　The book starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You’ll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you’ll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The book will further help you grasp concepts through real-world examples and datasets.
　　By the end of this book, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently.
　　What you will learn
　　·Use and manipulate complex and simple data structures
　　·Harness the full potential of DataFrames and numpy.array at run time
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