Python 数据清理和准备最佳实践（True EPUB）

English | 2024 | ISBN: 1837634742 | 611 pages | True EPUB | 13.09 MB

Take your data preparation skills to the next level by converting any type of data asset into a structured, formatted, and readily usable dataset

Key Features Maximize the value of your data through effective data cleaning methods Enhance your data skills using strategies for handling structured and unstructured data Elevate the quality of your data products by testing and validating your data pipelines

Book Description 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 products, 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.

What you will learn Ingest data from different sources and write it to the required sinks Profile and validate data pipelines for better quality control Get up to speed with grouping, merging, and joining structured data Handle missing values and outliers in structured datasets Implement techniques to manipulate and transform time series data Apply structure to text, image, voice, and other unstructured data

Who this book is for 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.

提升你的数据准备技能，将任何类型的数据资产转换为结构化、格式化且易于使用的数据集。 关键特性 通过有效的数据清理方法最大化你数据的价值 使用处理结构化和非结构化数据的方法增强你的数据技能 通过测试和验证你的数据管道来提高数据产品的质量 本书简介 专业人士在当今以数据为中心的世界中有效利用数据面临着许多挑战。其中主要的挑战之一是数据产品低的质量，这通常由不准确、不完整或不一致的数据引起。另一个重大挑战是没有足够的技能对非结构化数据进行分析，导致有价值的见解被遗漏，这些见解难以或不可能仅通过结构化数据获取。 为了帮助你应对这些挑战，这本书将带你深入了解上游数据管道的过程，包括从各种来源提取数据，对高质量最终表数据进行验证和描述，并将其写入不同的目标。你会专注于处理结构化数据的任务，如清理和编码数据集、处理缺失值和异常值；在学习如何使用简单的技术操纵非结构化数据后，你将被介绍多种自然语言处理技术和结构化图像、视频和音频的技术。 本书结束时，你可以熟练地进行结构化和非结构化数据的数据清理与准备技术。 你将学会 从不同的来源获取并写入所需目标的原始数据 对数据管道进行描述和验证以实现更好的质量控制 熟悉分组、合并和连接结构化数据的方法 处理结构化数据中的缺失值和异常值 实施时间序列数据操纵和转换技术 为文本、图像、声音和其他非结构化数据添加结构 这本书适合你： 无论是数据分析师、数据工程师、数据科学家还是负责数据准备和清理的数据专业人士，这本书都适用。为了充分利用本书，请具备Python编程的知识。

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