| Scikit-learn: Machine learning in Python F Pedregosa, G Varoquaux, A Gramfort, V Michel, B Thirion, O Grisel, ... the Journal of machine Learning research 12, 2825-2830, 2011 | 35422 | 2011 |
| SciPy 1.0: fundamental algorithms for scientific computing in Python P Virtanen, R Gommers, TE Oliphant, M Haberland, T Reddy, ... Nature methods 17 (3), 261-272, 2020 | 2474 | 2020 |
| The Astropy project: Building an open-science project and status of the v2. 0 core package AM Price-Whelan, BM Sipőcz, HM Günther, PL Lim, SM Crawford, ... The Astronomical Journal 156 (3), 123, 2018 | 1908 | 2018 |
| API design for machine learning software: experiences from the scikit-learn project L Buitinck, G Louppe, M Blondel, F Pedregosa, A Mueller, O Grisel, ... arXiv preprint arXiv:1309.0238, 2013 | 1051 | 2013 |
| First-year Sloan Digital Sky Survey-II supernova results: Hubble diagram and cosmological parameters R Kessler, AC Becker, D Cinabro, J Vanderplas, JA Frieman, J Marriner, ... The Astrophysical Journal Supplement Series 185 (1), 32, 2009 | 786 | 2009 |
| Statistics, data mining, and machine learning in astronomy: a practical Python guide for the analysis of survey data Ž Ivezić, AJ Connolly, JT VanderPlas, A Gray Princeton University Press, 2014 | 313 | 2014 |
| Lsst science book, version 2.0 PA Abell, J Allison, SF Anderson, JR Andrew, JRP Angel, L Armus, ... arXiv preprint arXiv:0912.0201, 2009 | 269 | 2009 |
| Python data science handbook: Essential tools for working with data J VanderPlas " O'Reilly Media, Inc.", 2016 | 266 | 2016 |
| Understanding the lomb–scargle periodogram JT VanderPlas The Astrophysical Journal Supplement Series 236 (1), 16, 2018 | 253 | 2018 |
| Snana: A public software package for supernova analysis R Kessler, JP Bernstein, D Cinabro, B Dilday, JA Frieman, S Jha, ... Publications of the Astronomical Society of the Pacific 121 (883), 1028, 2009 | 230 | 2009 |
| Snana: A public software package for supernova analysis R Kessler, JP Bernstein, D Cinabro, B Dilday, JA Frieman, S Jha, ... Publications of the Astronomical Society of the Pacific 121 (883), 1028, 2009 | 230 | 2009 |
| Scikit-learn: Machine learning without learning the machinery G Varoquaux, L Buitinck, G Louppe, O Grisel, F Pedregosa, A Mueller GetMobile: Mobile Computing and Communications 19 (1), 29-33, 2015 | 226 | 2015 |
| duchesnay E F Pedregosa, G Varoquaux, A Gramfort, V Michel, B Thirion, O Grisel, ... Scikit-learn: Machine Learning in Python. J. Mach. Learn. Res 12, 2825-2830, 2010 | 179 | 2010 |
| First-year sloan digital sky survey-II (SDSS-II) supernova results: constraints on nonstandard cosmological models J Sollerman, E Mörtsell, TM Davis, M Blomqvist, B Bassett, AC Becker, ... The Astrophysical Journal 703 (2), 1374, 2009 | 178 | 2009 |
| mwaskom/seaborn: v0. 8.1 (September 2017) M Waskom, O Botvinnik, D O’Kane, P Hobson, S Lukauskas, ... Zenodo, doi 10, 2017 | 173 | 2017 |
| Introduction to astroML: Machine learning for astrophysics J VanderPlas, AJ Connolly, Ž Ivezić, A Gray 2012 conference on intelligent data understanding, 47-54, 2012 | 143 | 2012 |
| Periodograms for multiband astronomical time series JT VanderPlas, Ž Ivezic The Astrophysical Journal 812 (1), 18, 2015 | 142 | 2015 |
| First-year Sloan Digital Sky Survey-II supernova results: consistency and constraints with other intermediate-redshift data sets H Lampeitl, RC Nichol, HJ Seo, T Giannantonio, C Shapiro, B Bassett, ... Monthly Notices of the Royal Astronomical Society 401 (4), 2331-2342, 2010 | 114 | 2010 |
| Exploring the variable sky with LINEAR. III. Classification of periodic light curves L Palaversa, Ž Ivezić, L Eyer, D Ruždjak, D Sudar, M Galin, A Kroflin, ... The Astronomical Journal 146 (4), 101, 2013 | 106 | 2013 |
| mwaskom/seaborn: v0. 9.0 (July 2018) M Waskom, O Botvinnik, D O’Kane, P Hobson, J Ostblom, S Lukauskas, ... DOI: https://doi. org/10.5281/zenodo 1313201, 2018 | 100 | 2018 |
