Python Data Cleaning and Preparation Best Practices : A practical guide to organizing and handling data from various sources and formats using Python

Lingua: inglese

Editore: Packt Publishing, 2024

1837634742 / 9781837634743

Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

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EUR 97,18

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Descrizione dell’articolo da parte del venditore

nach der Bestellung gedruckt Neuware - Printed after ordering - Take your data preparation skills to the next level by converting any type of data asset into a structured, formatted, and readily usable datasetKey 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 Purchase of the print or Kindle book includes a free PDF Elektronisches BuchBook 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 dataWho 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.Table of Contents Data Ingestion Techniques Importance of Data Quality Data Profiling - Understanding Data Structure, Quality, and Distribution Cleaning Messy Data and Data Manipulation Data Transformation - Merging and Concatenating Data Grouping, Aggregation, Filtering, and Applying Functions Data Sinks Detecting and Handling Missing Values and Outliers Normalization and Standardization Handling Categorical Features Consuming Time Series Data Text Preprocessing in the Era of LLMs Image and Audio Preprocessing with LLMs.

Codice articolo 9781837634743

Titolo
Python Data Cleaning and Preparation Best Practices : A practical guide to organizing and handling data from various sources and formats using Python
Autore
Maria Zervou
Editore
Packt Publishing
Anno di pubblicazione
2024
Condizione
Neu
Rilegatura
Taschenbuch
Lingua
inglese
ISBN 10
1837634742
ISBN 13
9781837634743
Peso dell'articolo
845 grammi
Dimensioni
235x191x24 mm

AHA-BUCH GmbH

Einbeck, Germania

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

Tariffe di spedizione da Germania a U.S.A.

ArticoloDa 5 a 7 giorni lavorativiDa 7 a 10 giorni lavorativi
Primo articoloEUR 30,50EUR 30,50
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