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Artikal br.:
34921421
Python Data Analysis: Perform data collection, data processing, wrangling, visualization, and model building using Python, 3rd Edition
Artikal br.:
34921421
BAM 106
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With this book, you'll get up and running using Python for data analysis by exploring the different phases and methodologies used in data analysis
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What Stands Out
Comprehensive Coverage
This edition offers extensive insights into data collection, processing, and visualization techniques tailored for Python, ensuring readers are well-equipped to tackle various data challenges.
Updated Tools
Includes the latest features and libraries in Python, enabling users to leverage cutting-edge tools for data analysis, maintaining relevance amid changing technology landscapes.
User-Friendly Approach
Written in an accessible style, it caters to both beginners and experienced analysts, making complex concepts easy to understand and apply in practical situations.
Detalji o proizvodu
- Perform data collection, processing, wrangling, visualization, and model building using Python
- Learn data analysis pipelines using machine learning algorithms and techniques
- Prepare and clean data for exploratory analysis, data manipulation, and data wrangling
- Discover supervised, unsupervised, probabilistic, and Bayesian machine learning methods
- Explore data science process models and data manipulation using NumPy and pandas
- Understand data visualization, time series analysis, signal processing, and parallel computing using Dask
| Publisher | Packt Publishing |
| Publication date | February 5, 2021 |
| Edition | 3rd ed. |
| Language | English |
| Print length | 478 pages |
| ISBN-10 | 1789955246 |
| ISBN-13 | 978-1789955248 |
| Item Weight | 1.79 pounds (810 grams) |
| Dimensions | 7.5 x 1.08 x 9.25 inches (19.1 x 2.7 x 23.5 cm) |
Who Should Buy?
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Data Analysts
Ideal for data analysts needing to effectively analyze and visualize data using Python's powerful libraries.
-
Students
Perfect for students in data science or statistics courses looking to enhance their practical skills in Python.
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Business Professionals
Beneficial for business professionals who want to leverage data analytics for better decision-making and insights.
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Beginners
Not suitable for complete beginners as it assumes prior knowledge of Python and data analysis concepts.
OPIS PROIZVODA
Python Data Analysis: Perform data collection, data processing, wrangling, visualization, and model building using Python, 3rd Edition
About This Item
Introducing the 3rd Edition Python Data Analysis Book Are you ready to unlock the full potential of data analysis using Python? Look no further than the Python Data Analysis book, now available in its highly anticipated 3rd Edition. Whether you are a beginner or an experienced data enthusiast, this book is designed to help you master the essential techniques for data collection, processing, wrangling, visualization, and model building using Python. With Python Data Analysis, you'll gain a comprehensive understanding of the data analysis process from start to finish. The book begins by laying a solid foundation, guiding you through the fundamentals of data collection and processing.
You'll learn how to gather data using various methods and effectively manipulate it for analysis purposes. But that's just the tip of the iceberg. Once you've mastered the basics, the book dives into advanced topics like data wrangling, visualization, and model building. You'll discover powerful Python libraries and tools that are indispensable for any data analyst, including NumPy, pandas, Matplotlib, and scikit-learn. Throughout the 3rd Edition, the author provides clear and concise explanations, accompanied by practical examples and step-by-step instructions.
This ensures that you not only understand the concepts but also know how to apply them in real-world scenarios. What sets this edition apart is its updated content and focus on the latest developments in the field of data analysis. Released on 5th February 2021, it incorporates the most recent advancements in Python and data analysis techniques. The Python Data Analysis book is the perfect resource for data scientists, analysts, researchers, and anyone looking to leverage the power of Python for extracting insights from data. Whether you are analyzing large datasets, building predictive models, or creating captivating visualizations, this book has got you covered. Don't miss out on the opportunity to enhance your data analysis skills.
Order your copy of the Python Data Analysis: Perform data collection, data processing, wrangling, visualization, and model building using Python, 3rd Edition Paperback today and join the ranks of proficient data analysts worldwide.
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Data Modeling & Design Editorial Review
The Python Data Analysis 3rd Edition book is meant for beginners as it is curated to be easy and simple to understand the most important concepts and tools. However, there are several negative reviews of the book that suggest it’s very basic and riddled with errors. One reviewer even says this book isn't worth a single Euro or Dollar in its current form, with blurry images and pixelated formulas making it difficult to follow some sections of the book. It appears that the book is not suitable for professional data analysts or scientists as it seems to lack the depth and quality necessary to handle complex data analysis projects.
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Pros
- Easy to read and understand for beginners
- Covers important concepts and tools
Cons
- Riddled with errors
Product Price History
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Karakteristike i prednosti
- Learn how to use modern libraries from the Python ecosystem to create efficient data pipelines
- Perform complex data analysis and modeling, data manipulation, data cleaning, and data visualization using easy-to-follow examples
- Work on real-world examples to analyze textual and image data using natural language processing (NLP) and image analytics techniques
- Equip the skills you need to prepare data for analysis and create meaningful data visualizations
- Use Python for data analysis in business and academic fields
- Includes interactive visualizations using Matplotlib, Seaborn, and Bokeh
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