This guide is ideal if you’re a professional, manager, or student who wants practical knowledge of analyzing data, without having to get a PhD in statistics. It’s also good for people who have a PhD i
Turn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author Had
What exactly is data science? With this book, you’ll gain a clear understanding of this discipline for discovering natural laws in the structure of data. Along the way, you’ll learn how to use the ver
Looking for complete instructions on manipulating, processing, cleaning, and crunching structured data in Python? The second edition of this hands-on guide—updated for Python 3.5 and Pandas 1.0—is packed with practical cases studies that show you how to effectively solve a broad set of data analysis problems, using Python libraries such as NumPy, pandas, matplotlib, and IPython.Written by Wes McKinney, the main author of the pandas library, Python for Data Analysis also serves as a practical, modern introduction to scientific computing in Python for data-intensive applications. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.
