"Although many of the techniques are relevant to molecular bioinformatics, the motivation for the text is much broader, focusing on topics and techniques that are applicable to a range of scientific endeavors."

Clearly written guide to using R for data science, visualization, tidying data, and more, by the author of "tidyverse" package. Highly recommended!

"For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all--IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. "

"Python Data Analytics will help you tackle the world of data acquisition and analysis using the power of the Python language. At the heart of this book lies the coverage of pandas, an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. "

Based on their extensive experience with teaching R & statistics to applied scientists, the authors provide a beginner's guide to R. To avoid the difficulty of teaching R & statistics at the same time, statistical methods are kept to a minimum.

Pages 151-245 cover using Microsoft Excel on iPads.

Chemists across all subdisciplines use Excel to record data in tabular form, but few have learned to take full advantage of the scientific calculating power within this program. Excel is capable of helping chemists process, analyze, and present scientific data, from the relatively simple to the highly complex.

"guides the reader through both programming and built-in functions to easily exploit MATLAB's extensive capabilities for tackling engineering and scientific problems. Assuming no knowledge of programming, this book starts with programming concepts, such as variables, assignments, and selection statements, moves on to loops, and then solves problems using both the programming concept and the power of MATLAB."

"Whether you are new to MATLAB, new to version 7.0, or simply in need of a hands-on, to-the-point reference, MATLAB® Primer provides the tools you need in a conveniently sized [...] pocketbook."

"The overall aim of the book is to introduce students to the typical course followed by a data analysis project in earth sciences. A project usually involves searching relevant literature, reviewing and ranking published books and journal articles, extracting relevant information from the literature in the form of text, data, or graphs, searching and processing the relevant original data using MATLAB, and compiling and presenting the results as posters, abstracts, oral presentations and multimedia publications using graphics design software."

The nine chapters cover SAS basics, data access, data step programming, data manipulation, data management, data presentation, efficiency and performance, configuration and support, and SAS 9.

This book is an easy-to-understand introduction to SAS as well as to univariate and multivariate statistics. Clear explanations and simple language guide you through the research terminology, data input, data manipulation, and types of statistical analysis that are most commonly used in the social and behavioral sciences.

Packed with real-world examples and case studies, the book supports students through every stage of qualitative data analysis. Contains fully integrated instructions for using NVivo on both Mac and PC, with screenshots and click-by-click guidance.

"This book will take you through GIS techniques, geodatabases, geospatial raster data, and much more using the latest built-in tools and libraries in Python 3.7." Recommended by a grad student who found chapters 2 and 3 explained a lot of concepts that get glossed over in courses.

This concise book covers concepts central to digital illustration using the Inkscape 0.91 open source software package as well as the Adobe Illustrator professional Illustration package. The book builds on the foundational concepts of vector graphics and the SVG format, and gets more advanced as chapters progress, covering what vector new media formats are best for use with Android Studio, Java and JavaFX, iOS, Kindle and HTML5, as well as key factors regarding the data footprint optimization work process, and why data footprint optimization is important.

"Adobe Illustrator Classroom in a Book (2021 release) contains lessons that cover the basics and beyond, providing countless tips and techniques to help you become more productive with the program. You can follow the book from start to finish or choose only those lessons that interest you."

"learn how and when to create art point-by-point through rough building and refinement as well as through shape-building techniques using Illustrator's Pathfinder palette."

"Readers can follow the steps in a tutorial fashion, or use the book as a reference guide to individual program features. Many of the key illustrations used in the book are available via Web download for practice by readers.