PT - JOURNAL ARTICLE AU - Jack B. Greisman AU - Kevin M. Dalton AU - Doeke R. Hekstra TI - Reciprocalspaceship: A Python Library for Crystallographic Data Analysis AID - 10.1101/2021.02.03.429617 DP - 2021 Jan 01 TA - bioRxiv PG - 2021.02.03.429617 4099 - http://biorxiv.org/content/early/2021/02/03/2021.02.03.429617.short 4100 - http://biorxiv.org/content/early/2021/02/03/2021.02.03.429617.full AB - X-ray crystallography is an invaluable technique for studying the atomic structure of macromolecules. Much of crystallography’s success is due to the software packages developed to enable the automated processing of diffraction data. However, the analysis of unconventional diffraction experiments can still pose significant challenges—many existing programs are closed-source, sparsely documented, or are challenging to integrate with modern libraries for scientific computing and machine learning. Here we describe reciprocalspaceship, a Python library for exploring reciprocal space. It provides a tabular representation for reflection data from diffraction experiments that extends the widely-used pandas library with built-in methods for handling space group, unit cell, and symmetry-based operations. As we illustrate, this library facilitates new modes of exploratory data analysis while supporting the prototyping, development, and release of new methods.Competing Interest StatementThe authors have declared no competing interest.