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38255715
Advancing Into Analytics: From Excel to Python and R, (Paperback)
98% of respondents would recommend this to a friend
Item #:
38255715
GTQ 417
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By the time you complete this book, you'll be able to conduct exploratory data analysis and hypothesis testing using a programming language.
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What Stands Out
Comprehensive Transition Guide
Guides users from basic Excel analytics to advanced Python and R techniques, empowering them to elevate their data analysis skills efficiently.
Hands-On Learning
Incorporates practical exercises and examples, ensuring readers gain real-world experience and confidence in using Python and R for analytics.
Expert Insights
Authored by industry professionals, this book provides insider tips and strategies that enhance understanding and application of analytics tools.
Product Details
- Intermediate Excel users will gain a solid understanding of analytics and the data stack.
- Teaches how to conduct exploratory data analysis and hypothesis testing using a programming language.
- Demonstrates key statistical concepts with spreadsheets and transitions knowledge about data manipulation into R and Python programming.
- Guides on transferring skills from Excel to R and Python for data analysis.
- Provides foundations of analytics in Excel and demonstrates the process of moving from Excel to R and Python.
- Written by George Mount, founder and CEO of Stringfest Analytics.
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | May, 2021 |
| Pages | 248 |
| Reading level | Professional and Scholarly |
| Subgenre | Languages |
| Series title | No Series |
| Edition | 1 |
| Publisher | O'Reilly Media |
| Original languages | English |
| Language | English |
| Is collectible | N |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 7.00 x 0.53 x 9.19 in (17.8 x 1.3 x 23.3 cm) |
| Assembled product weight | 0.89 lb (400 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
-
Data Analysts
Ideal for data analysts seeking to enhance their analytical skills from Excel into more powerful languages like Python and R.
-
Beginners in Analytics
Great for beginners who want a structured approach to transition from basic spreadsheet work to data science programming.
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Self-Learners
Perfect for self-learners motivated to understand analytics concepts and apply programming in real-world data scenarios.
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Advanced Users
Not suitable for advanced analytics professionals who are already proficient in Python, R, and other advanced methodologies.
Product Description
Advancing Into Analytics: From Excel to Python and R, (Paperback)
About This Item
Are you ready to take your analytics skills to the next level? Look no further than 'Advancing Into Analytics: From Excel to Python and R.' This comprehensive guidebook will equip you with the knowledge and tools you need to harness the full potential of data analysis. Whether you are a business professional, student, or aspiring data scientist, this paperback guide is suitable for all skill levels. It takes you on a journey from the familiar world of Excel to the powerful languages of Python and R, empowering you to make more informed, data-driven decisions. With 'Advancing Into Analytics,' you will learn how to transition smoothly from Excel to Python and R. These languages offer more robust statistical analysis capabilities, data visualization, and machine learning.
By mastering these languages, you can unlock intricate insights hidden within complex datasets. The book delves into key topics such as Python for Analytics and R for Analytics. You will learn how to manipulate, explore, and analyze data using these languages. Moreover, it offers extensive comparisons between Python and R, helping you choose the right language for your specific analytical needs. 'Data Analytics with Python' and 'Data Analytics with R' sections provide practical use cases and real-world examples.
You'll learn how to clean and transform data, perform statistical analyses, create engaging visualizations, and unleash the power of predictive modeling. The step-by-step tutorials and hands-on exercises ensure that you'll gain a strong foundation in both languages. Whether you're interested in exploring data from finance, marketing, healthcare, or any other industry, this book covers it all. It goes beyond just the basics and introduces you to advanced analytics techniques and tools.
With 'Advancing Into Analytics,' you'll have the knowledge and skills to excel in your analytics journey. Upgrade your analytical capabilities today with 'Advancing Into Analytics: From Excel to Python and R.' This must-have guidebook will be your trusted companion as you navigate the world of data analysis. Don't miss out on this opportunity to enhance your skills and stay ahead in the competitive world of analytics. Grab your copy now!.
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George Mount All Books Editorial Review
Advancing Into Analytics: From Excel to Python and R, (Paperback) is a comprehensive guide designed for professionals looking to enhance their analytical skills. This non-fiction book spans 248 pages and covers essential computing topics aimed at a professional and scholarly reading level. Published by O'Reilly Media in May 2021, it serves as a transition from traditional Excel methods to modern programming languages like Python and R, making it indispensable for anyone interested in advancing their data analysis capabilities. Readers appreciate the clear explanations and practical examples that facilitate understanding complex concepts in analytics.
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Pros
- Provides a smooth transition from Excel to programming
- Covers essential analytical skills for professionals
- Written by reputable publisher O'Reilly Media
- Includes practical examples and hands-on exercises
- Suitable for professional and scholarly audiences
Cons
- Might be challenging for beginners in programming
Product Price History
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GTQ 417
Order now and get it around Wednesday, October 21
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Features & Benefits
- Gain a solid understanding of analytics and the data stack
- Conduct exploratory data analysis and hypothesis testing
- Learn how to transfer your Excel data skills to R and Python
- Build compelling demonstrations of important concepts in statistics and analytics
- Position yourself to learn more advanced data analysis techniques
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