Python Data Cleaning and Preparation Best Practices. (Record no. 15266)
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| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250710181508.0 |
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| 024 80 - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 9781837632909 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | PACKT |
| Transcribing agency | PACKT |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | en |
| 044 ## - COUNTRY OF PUBLISHING/PRODUCING ENTITY CODE | |
| MARC country code | GB |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Maria Zervou |
| Relator term | author. |
| 245 00 - TITLE STATEMENT | |
| Title | Python Data Cleaning and Preparation Best Practices. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | GB: |
| Name of publisher, distributor, etc. | Packt, |
| Date of publication, distribution, etc. | 2024-09-27. |
| 263 ## - PROJECTED PUBLICATION DATE | |
| Projected publication date | 2024-09-27 |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | GB: |
| Name of producer, publisher, distributor, manufacturer | Packt, |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 456. |
| 377 ## - ASSOCIATED LANGUAGE | |
| Language code | en |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | <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.<br/>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.<br/>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 ## - SYSTEM DETAILS NOTE | |
| System details note | Data in extended ASCII character set. |
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| System details note | Mode of access: Internet. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | PACKT |
| 773 0# - HOST ITEM ENTRY | |
| Title | Python Data Cleaning and Preparation Best Practices |
| Place, publisher, and date of publication | GB,Packt,2024-09-27 |
| Physical description | 456 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://learning.packt.com/product/477493">https://learning.packt.com/product/477493</a> |
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