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Python Data Cleaning Cookbook: Modern techniques and Python tools to detect and remove dirty data and extract key insights
86% of respondents would recommend this to a friend
€ 46
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This book is for anyone looking for ways to handle messy, duplicate, and poor data using different Python tools and techniques.
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What Stands Out
Produkta informācija
- Learn various data cleaning techniques using Python to reveal key insights
- Manipulate data of different complexities to shape them according to business needs
- Clean, monitor, and validate large data volumes before analysis
- Book provides essential tools and techniques for data cleaning and handling using Python
- Discusses reading and analyzing data from multiple sources, addressing messy data issues, and using visualizations for EDA
- Ideal for individuals seeking to handle messy, duplicate, and poor data using Python tools and techniques
| Publisher | Packt Publishing |
| Publication date | December 11, 2020 |
| Language | English |
| Print length | 436 pages |
| ISBN-10 | 1800565666 |
| ISBN-13 | 978-1800565661 |
| Item Weight | 1.64 pounds (740 grams) |
| Dimensions | 7.5 x 0.99 x 9.25 inches (19.1 x 2.5 x 23.5 cm) |
Who Should Buy?
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Data Analysts
Data analysts looking to enhance their skills in data cleaning using modern Python techniques will find this cookbook invaluable.
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Data Scientists
Data scientists needing effective methods to preprocess datasets for analysis and model training will benefit greatly from this resource.
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Python Beginners
Beginners in Python who seek practical applications of data cleaning will find clear examples and guidance in this cookbook.
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Advanced Users
Advanced data professionals might find the cookbook's content too basic and not suitable for their complex data needs.
PRODUKTA APRAKSTS
Python Data Cleaning Cookbook: Modern techniques and Python tools to detect and remove dirty data and extract key insights
Dietary Supplement Disclaimer
Statements regarding dietary supplements have not been evaluated by the Food and Drug Administration and are not intended to diagnose, treat, cure, or prevent any disease or health condition.
Klientu jautājumi un atbildes
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Data Mining Editorial Review
Python Data Cleaning Cookbook provides a comprehensive guide for software developers who need to process, clean and refine their datasets. The cookbook format, where each recipe provides a coding solution to specific problems, is effective in providing a range of techniques to help users extract meaningful insights. The book covers topics like detecting anomalies, visualizing data, and processing it at a macroscopic level. One of the standout features of the book is the author's ability to provide a 'WHY' behind data processing tasks, giving readers a deeper understanding of the concepts. The book is approachable for those new to Python and data processing and provides hands-on examples to help Consolidate information.
Customer Reviews & Ratings
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Pros
- Comprehensive guide for processing, cleaning and refining datasets
- Effective cookbook format with each recipe addressing specific problems
- Covers detecting anomalies, visualizing data and processing data at a macroscopic level
- 'WHY' behind data processing tasks provided
- Approachable for beginners
- Provides hands-on examples
Mīnusi
- Some beginners may find it challenging to follow along
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Svarīga informācija
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Funkcijas un priekšrocības
- Discover various data cleaning techniques to reveal key insights
- Manipulate data of different complexities to shape them into the right form for business needs
- Clean, monitor, and validate large data volumes to diagnose problems before analyzing
- Create visualizations to gain insights and identify data issues
- Build functions and classes for automating data cleaning
- Requires only working knowledge of Python programming
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