| 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 | 102761 | 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 | 32035 | 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 | 9032 | 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 | 3728 | 2013 |
| Seaborn: statistical data visualization ML Waskom Journal of Open Source Software 6 (60), 3021, 2021 | 3704 | 2021 |
| JAX: composable transformations of Python+ NumPy programs J Bradbury, R Frostig, P Hawkins, MJ Johnson, C Leary, D Maclaurin, ... | 2935 | 2018 |
| Understanding the lomb–scargle periodogram JT VanderPlas The Astrophysical Journal Supplement Series 236 (1), 16, 2018 | 1159 | 2018 |
| Python data science handbook: Essential tools for working with data J VanderPlas " O'Reilly Media, Inc.", 2016 | 1053 | 2016 |
| SciPy 1.0 Contributors P Virtanen, R Gommers, TE Oliphant, M Haberland, T Reddy, ... Nat. Methods 17 (3), 261-272, 2020 | 932 | 2020 |
| 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 | 722* | 2014 |
| S... Contributors,“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 | 608 | 2020 |
| mwaskom/seaborn: v0. 8.1 (September 2017) M Waskom, O Botvinnik, D O'Kane, P Hobson, S Lukauskas, ... Zenodo, 2017 | 472 | 2017 |
| 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 | 466 | 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 | 387 | 2009 |
| Lsst science book, version 2.0 PA Abell, J Allison, SF Anderson, JR Andrew, JRP Angel, L Armus, ... | 366 | 2009 |
| Periodograms for multiband astronomical time series JT VanderPlas, Ž Ivezic The Astrophysical Journal 812 (1), 18, 2015 | 298 | 2015 |
| Altair: interactive statistical visualizations for Python J VanderPlas, B Granger, J Heer, D Moritz, K Wongsuphasawat, ... Journal of open source software 3 (32), 1057, 2018 | 251 | 2018 |
| Introduction to astroML: Machine learning for astrophysics J VanderPlas, AJ Connolly, Ž Ivezić, A Gray 2012 conference on intelligent data understanding, 47-54, 2012 | 231 | 2012 |
| Scikit-learn: Machine learning in python journal of machine learning research F Pedregosa, G Varoquaux, A Gramfort, V Michel, B Thirion, O Grisel, ... Journal of machine learning research 12, 2825-2830, 2011 | 212 | 2011 |
| 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 | 198 | 2009 |