Title
Data Wrangling with Python: Creating actionable data from raw sources,New
Delivery time: 8-12 business days (International)
Simplify your ETL processes with these handson 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 DescriptionFor 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 prebuilt 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 realworld 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 Perform web scraping with BeautifulSoup4 and html5lib Execute advanced string search and manipulation with RegEX Handle outliers and perform data imputation with Pandas Use descriptive statistics and plotting techniques Practice data wrangling and modeling using data generation techniques Who this book is forData Wrangling with Python is designed for developers, data analysts, and business analysts who are keen to pursue a career as a fullfledged data scientist or analytics expert. Although, this book is for beginners, prior working knowledge of Python is necessary to easily grasp the concepts covered here. It will also help to have rudimentary knowledge of relational database and SQL. Table of Contents Introduction to Data Wrangling with Python Advanced Data Structures and File Handling Introduction to Numpy, Pandas, and Matplotlib A Deep Dive into Data Wrangling with Python Getting Comfortable with Different Kinds of Data Sources Learning the Hidden Secrets of Data Wrangling Advanced Web Scraping and Data Gathering RDBMS and SQL Application of Data Wrangling in Real Life
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Shipping & Returns
Shipping
We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
Returns
To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.
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Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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Frequently Asked Questions
- Q: What is the main focus of 'Data Wrangling with Python'? A: The book primarily focuses on simplifying ETL processes through hands-on tips and best practices in data wrangling, enabling users to transform raw data into actionable insights.
- Q: Who is the target audience for this book? A: This book is intended for developers, data analysts, and business analysts who are beginners in Python but have some prior knowledge. It's suitable for those aspiring to become data scientists or analytics experts.
- Q: What prior knowledge is recommended before reading this book? A: Readers should have a basic working knowledge of Python and some rudimentary understanding of relational databases and SQL to fully grasp the concepts covered in the book.
- Q: How many pages does 'Data Wrangling with Python' contain? A: The book contains 452 pages, providing comprehensive coverage of data wrangling techniques.
- Q: What programming libraries does this book cover? A: The book covers essential Python libraries such as NumPy and Pandas, which are fundamental for data manipulation and analysis.
- Q: Are there practical examples included in the book? A: Yes, the book includes real-world examples and datasets to help readers grasp the concepts of data wrangling effectively.
- Q: What kind of techniques will I learn from this book? A: Readers will learn various data wrangling techniques, including handling missing data, performing web scraping, using regular expressions for string manipulation, and applying descriptive statistics.
- Q: Is there a focus on data cleaning methods specific to Python? A: Yes, the book emphasizes specialized pre-built routines in Python for data cleaning, which differ from traditional methods used in other programming languages.
- Q: When was 'Data Wrangling with Python' published? A: The book was published on February 28, 2019.
- Q: What type of binding does this book have? A: This book is available in a paperback binding.