Science

Coding is becoming a crucial part of research. Scientists commonly use languages such as Python and R to conduct and automate analyses, because in this way they can speed data crunching, increase reproducibility, protect data from accidental deletion or alteration and handle data sets that would overwhelm commercial applications. Researchers who use these languages can tackle questions that would be impractical to address if data were manipulated manually. Reconfiguring an analysis or revising graphs becomes quick and straightforward, and researchers can more easily build on their own or others' work.