Cleaning Data for Effective Data Science

Doing the other 80% of the work with Python, R, and command-line tools

af David Mertz

Data in its raw state is rarely ready for productive analysis. This book not only teaches you data preparation, but also what questions you should ask of your data. It focuses on the thought processes necessary for successful data cleaning as much as on concise and precise code examples that express these thoughts.