Dive into the world of scientific computing with 'SciPy Recipes', a practical guide tailored for anyone seeking hands-on experience with the SciPy stack. With over 110 detailed recipes, you'll gain expertise in handling real-world data challenges, from statistical computations to crafting intricate visualizations and beyond. What this Book will help me do Learn to use the SciPy Stack libraries like NumPy, pandas, and matplotlib effectively for scientific computing tasks. Master data wrangling techniques using pandas for efficient data manipulation. Understand the process of creating informative visualizations using matplotlib. Perform advanced statistical and numerical computations with simplicity. Solve real-world problems like numerical analysis and linear algebra using SciPy components. Author(s) None Martins, Ruben Oliva Ramos, and V Kishore Ayyadevara bring years of experience in scientific computing and Python programming to this book. Individually, they have contributed extensively to the implementation of computational tools and systems. Together, they've crafted this book to be both accessible to learners and insightful for practitioners, blending instruction with real-world practical applications. Who is it for? This book is designed for Python developers, data scientists, and analysts eager to venture into scientific computing. If you have a basic understanding of Python and aspire to effectively manipulate and visualize data using the SciPy stack, this book is perfect for you. It's equally beneficial for those who seek practical solutions to complex computational challenges. Begin your journey into scientific computing with this essential guide.

In "Advanced Analytics with R and Tableau," you will learn how to combine the statistical computing power of R with the excellent data visualization capabilities of Tableau to perform advanced analysis and present your findings effectively. This book guides you through practical examples to understand topics such as classification, clustering, and predictive analytics while creating compelling visual dashboards. What this Book will help me do Integrate advanced statistical computations in R with Tableau's visual analysis for comprehensive analytics. Master making R function calls from Tableau through practical applications such as RServe integration. Develop predictive and classification models in R, visualized wonderfully in Tableau dashboards. Understand clustering and unsupervised learning concepts, applied to real-world datasets for business insights. Leverage the combination of Tableau and R for making impactful, data-driven decisions in your organization. Author(s) Ruben Oliva Ramos, Jen Stirrup, and Roberto Rösler are accomplished professionals with extensive experience in data science and analytics. Their combined expertise brings practical insights into combining R and Tableau for advanced analytics. Advocates for hands-on learning, they emphasize clarity and actionable knowledge in their writing. Who is it for? "Advanced Analytics with R and Tableau" is ideal for business analysts, data scientists, and Tableau professionals eager to expand their capabilities into advanced analytics. Readers should be familiar with Tableau and have basic knowledge of R, though the book starts with accessible examples. If you're looking to enhance your analytics with R's statistical power seamlessly integrated into Tableau, this book is for you.