000			03337nam a2200265uu 4500
005			20250710181508.0
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024	8	0	_a9781837632909
040			_aPACKT _cPACKT
041			_aen
044			_aGB
100	0		_aMaria Zervou _eauthor.
710	2		_aPACKT
773	0		_tPython Data Cleaning and Preparation Best Practices _dGB,Packt,2024-09-27 _h456
245	0	0	_aPython Data Cleaning and Preparation Best Practices.
300			_a456.
377			_aen
260			_aGB: _bPackt, _c2024-09-27.
263			_a2024-09-27
264		1	_aGB: _bPackt,
520			_a<p><b>Take your data preparation skills to the next level by converting any type of data asset into a structured, formatted, and readily usable dataset </b></p><h4>Key Features</h4><ul><li>Maximize the value of your data through effective data cleaning methods</li><li>Enhance your data skills using strategies for handling structured and unstructured data</li><li>Elevate the quality of your data product_backups by testing and validating your data pipelines</li><li>Purchase of the print or Kindle book includes a free PDF eBook</li></ul><h4>Book Description</h4>Professionals face several challenges in effectively leveraging data in today's data-driven world. One of the main challenges is the low quality of data product_backups, often caused by inaccurate, incomplete, or inconsistent data. Another significant challenge is the lack of skills among data professionals to analyze unstructured data, leading to valuable insights being missed that are difficult or impossible to obtain from structured data alone. To help you tackle these challenges, this book will take you on a journey through the upstream data pipeline, which includes the ingestion of data from various sources, the validation and profiling of data for high-quality end tables, and writing data to different sinks. You’ll focus on structured data by performing essential tasks, such as cleaning and encoding datasets and handling missing values and outliers, before learning how to manipulate unstructured data with simple techniques. You’ll also be introduced to a variety of natural language processing techniques, from tokenization to vector models, as well as techniques to structure images, videos, and audio. By the end of this book, you’ll be proficient in data cleaning and preparation techniques for both structured and unstructured data.<h4>What you will learn</h4><ul><li>Ingest data from different sources and write it to the required sinks</li><li>Profile and validate data pipelines for better quality control</li><li>Get up to speed with grouping, merging, and joining structured data</li><li>Handle missing values and outliers in structured datasets</li><li>Implement techniques to manipulate and transform time series data</li><li>Apply structure to text, image, voice, and other unstructured data</li></ul><h4>Who this book is for</h4>Whether you're a data analyst, data engineer, data scientist, or a data professional responsible for data preparation and cleaning, this book is for you. Working knowledge of Python programming is needed to get the most out of this book. .
538			_aData in extended ASCII character set.
538			_aMode of access: Internet.
856	4	0	_uhttps://learning.packt.com/product/477493
999			_c15266 _d15266