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

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

Maria Zervou

E-book
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 missing valuable insights 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, validation and profiling of the 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 for structuring 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.
  • 1. Data Ingestion Sources
  • 2. Importance of Data Quality
  • 3. Data Profiling and Validation
  • 4. Cleaning of Messy data and Data Manipulation
  • 5. Data Transformation, Aggregation and Grouping
  • 6. Data Destination/Sinks
  • 7. Detecting and Handle Missing Values and Outliers
  • 8. Feature Scaling and Normalization
  • 9. Handling Categorical Features
  • 10. Consume Times Series Data
  • 11. From Raw Text to Full Tokenization
  • 12. From clean Tokens to Text Structuring and Vector Models
  • 13. From Image Preprocessing to Video Handling
  • Titel: Python Data Cleaning and Preparation Best Practices. A practical guide to organizing and handling data from various sources and formats using Python
  • Autor: Maria Zervou
  • Originaler Titel: Python Data Cleaning and Preparation Best Practices. A practical guide to organizing and handling data from various sources and formats using Python
  • ISBN: 9781837632909, 9781837632909
  • Veröffentlichungsdatum: 2024-09-27
  • Format: E-book
  • Artikelkennung: e_40sz
  • Verleger: Packt Publishing