| Scikit-learn: Machine learning in Python F Pedregosa, G Varoquaux, A Gramfort, V Michel, B Thirion, O Grisel, ... Journal of machine learning research 12 (Oct), 2825-2830, 2011 | 25236 | 2011 |
| 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 | 940 | 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 | 720 | 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 | 395 | 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, 2019 | 292* | 2019 |
| Lsst science book, version 2.0 PA Abell, DL Burke, M Hamuy, M Nordby, TS Axelrod, D Monet, B Vrsnak, ... | 224 | 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 | 198 | 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 | 198 | 2009 |
| 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 | 176 | 2009 |
| Understanding the lomb–scargle periodogram JT VanderPlas The Astrophysical Journal Supplement Series 236 (1), 16, 2018 | 161 | 2018 |
| Python data science handbook: Essential tools for working with data J VanderPlas " O'Reilly Media, Inc.", 2016 | 151 | 2016 |
| SciPy 1.0: fundamental algorithms for scientific computing in Python P Virtanen, R Gommers, TE Oliphant, M Haberland, T Reddy, ... Nature methods, 1-12, 2020 | 135 | 2020 |
| Introduction to astroML: Machine learning for astrophysics J VanderPlas, AJ Connolly, Ž Ivezić, A Gray 2012 conference on intelligent data understanding, 47-54, 2012 | 120 | 2012 |
| 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 | 112 | 2010 |
| Periodograms for multiband astronomical time series JT VanderPlas, Ž Ivezic The Astrophysical Journal 812 (1), 18, 2015 | 104 | 2015 |
| 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 | 95 | 2013 |
| seaborn: v0. 7.1 (june 2016) M Waskom, O Botvinnik, D O’Kane, P Hobson, YH David, S Lukauskas, ... Zenodo. doi 10, 2016 | 93* | 2016 |
| Hierarchical probabilistic models for group anomaly detection L Xiong, B Póczos, J Schneider, A Connolly, J VanderPlas Proceedings of the fourteenth international conference on artificial …, 2011 | 70 | 2011 |
| Tests of modified gravity with dwarf galaxies B Jain, J VanderPlas Journal of Cosmology and Astroparticle Physics 2011 (10), 032, 2011 | 68 | 2011 |
| Astrophysical tests of modified gravity: the morphology and kinematics of dwarf galaxies V Vikram, A Cabré, B Jain, JT VanderPlas Journal of Cosmology and Astroparticle Physics 2013 (08), 020, 2013 | 63 | 2013 |
