This book was inspired by an introductory data science course in Python that I taught in Summer 2015 to a small group of select undergraduate students of Suffolk University in Boston. The disjoint cheat sheets quickly turned into lecture notes and then into something much bigger and more useful–this book.
The book covers data acquisition, cleaning, storing, retrieval, transformation, visualization, elements of advanced data analysis (network analysis), statistics, and machine learning, as well as select topics of Python the language. It is intended for graduate and undergraduate students, data science instructors, entry-level data science professionals–especially those converting from R to Python–as well as seasoned developers who want a reference to help them remember all of the Python functions and options.
So, welcome again!