├── PULL_REQUEST_TEMPLATE.md ├── CONTRIBUTING.md ├── LICENSE.md ├── CODE_OF_CONDUCT.md └── README.md /PULL_REQUEST_TEMPLATE.md: -------------------------------------------------------------------------------- 1 | Add/remove to/from the "
" section. 2 | 3 | 4 | 5 | 6 | - [ ] Table of contents has been updated (if needed). 7 | - [ ] Contents have been sorted alphabetically. 8 | -------------------------------------------------------------------------------- /CONTRIBUTING.md: -------------------------------------------------------------------------------- 1 | # Contributing 2 | 3 | Contributions are welcome, and they are greatly appreciated! 4 | 5 | Every little bit helps, and credit will always be given. 6 | 7 | ## Types of Contributions 8 | 9 | ### Bug Reports, Feature Requests, and Feedback 10 | 11 | Create a [new project issue][1]! Try to be as descriptive as possible. 12 | 13 | ### Suggesting new resources, Fixes, and Documentation 14 | 15 | Create a [new merge/pull request][2]! Make sure to follow the guidelines. 16 | 17 | Look through the GitHub issues for features, bugs and other requests. 18 | Anything tagged with "help wanted" is open to whoever wants to implement it. 19 | 20 | ## Merge/Pull Request Guidelines 21 | 22 | Before you submit a pull request, check that it meets these guidelines 23 | 1. Make sure to have atomic commits and contextual commit messages! 24 | 2. Make sure links are properly working. 25 | 3. Update the table of contents if necesseray 26 | 27 | Thank you for your suggestions! 28 | 29 | ## Code of Conduct 30 | 31 | Please note that this project is released with a [Contributor Code of Conduct](CODE_OF_CONDUCT.md). 32 | By participating in this project you agree to abide by its terms. 33 | -------------------------------------------------------------------------------- /LICENSE.md: -------------------------------------------------------------------------------- 1 | BSD 3-Clause License 2 | 3 | Copyright (c) 2022, Max Planck Institute for Astronomy 4 | All rights reserved. 5 | 6 | Redistribution and use in source and binary forms, with or without 7 | modification, are permitted provided that the following conditions are met: 8 | 9 | 1. Redistributions of source code must retain the above copyright notice, this 10 | list of conditions and the following disclaimer. 11 | 12 | 2. Redistributions in binary form must reproduce the above copyright notice, 13 | this list of conditions and the following disclaimer in the documentation 14 | and/or other materials provided with the distribution. 15 | 16 | 3. Neither the name of the copyright holder nor the names of its 17 | contributors may be used to endorse or promote products derived from 18 | this software without specific prior written permission. 19 | 20 | THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" 21 | AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 22 | IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 23 | DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE 24 | FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL 25 | DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR 26 | SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 27 | CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, 28 | OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE 29 | OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 30 | -------------------------------------------------------------------------------- /CODE_OF_CONDUCT.md: -------------------------------------------------------------------------------- 1 | We are committed to providing a strong and 2 | enforced code of conduct and expect everyone in our community to follow these 3 | guidelines when interacting with others in all forums. Our goal is to keep ours 4 | a positive, inclusive, successful, and growing community. The community of 5 | participants in open source Astronomy projects is made up of members from 6 | around the globe with a diverse set of skills, personalities, and experiences. 7 | It is through these differences that our community experiences success and 8 | continued growth. 9 | 10 | As members of the `mpi-astronomy` community: 11 | 12 | 1. We pledge to treat all people with respect and provide a harassment- and bullying-free environment, regardless of sex, sexual orientation and/or gender identity, disability, physical appearance, body size, race, nationality, ethnicity, and religion. In particular, sexual language and imagery, sexist, racist, or otherwise exclusionary jokes are not appropriate. 13 | 2. We pledge to respect the work of others by recognizing acknowledgment/citation requests of original authors. As authors, we pledge to be explicit about how we want our own work to be cited or acknowledged. 14 | 3. We pledge to welcome those interested in joining the community, and realize that including people with a variety of opinions and backgrounds will only serve to enrich our community. In particular, discussions relating to pros/cons of various technologies, programming languages, and so on are welcome, but these should be done with respect, taking proactive measure to ensure that all participants are heard and feel confident that they can freely express their opinions. 15 | 4. We pledge to welcome questions and answer them respectfully, paying particular attention to those new to the community. We pledge to provide respectful criticisms and feedback in forums, especially in discussion threads resulting from code contributions. 16 | 5. We pledge to be conscientious of the perceptions of the wider community and to respond to criticism respectfully. We will strive to model behaviors that encourage productive debate and disagreement, both within our community and where we are criticized. We will treat those outside our community with the same respect as people within our community. 17 | 6. We pledge to help the entire community follow the code of conduct, and to not remain silent when we see violations of the code of conduct. We will take action when members of our community violate this code such as such as contacting conduct@stsci.edu (all emails sent to this address will be treated with the strictest confidence) or talking privately with the person. 18 | This code of conduct applies to all community situations online and offline, including mailing lists, forums, social media, conferences, meetings, associated social events, and one-to-one interactions. 19 | 20 | All Max Planck researchers are bound to adhere to the 21 | [Max Plack Society Code of Conduct](https://www.mpg.de/14172230/code-of-conduct.pdf). 22 | All MPIA employees should attach importance to creating a respectful and healthy atmosphere 23 | and a level playing field for research and work. The goal is to ensure good working conditions 24 | for everyone and to provide the basis for individual job satisfaction, personal development, 25 | motivation, collegiality and positive interpersonal relations. The MPIA Code of Conduct is 26 | specified in the MPIA Work Agreement. 27 | 28 | **Reporting**: Any violations of the Code of Conduct should be reported to the 29 | [MPIA Ombudsperson](https://www2.mpia-hd.mpg.de/homes/fendt/ombud.html). If this information 30 | is not available, please reach out to the owners of the [`mpi-astronomy` GitHub organization](https://github.com/mpi-astronomy). 31 | 32 | Parts of this code of conduct have been adapted from the Astropy and NumFOCUS codes of conduct: 33 | 34 | https://www.astropy.org/code_of_conduct.html 35 | https://www.numfocus.org/about/code-of-conduct/ 36 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # List of resources for Astronomy Data Science [![awesome][awesome-badge]][awesome-link] 2 | 3 | An [awesome list](https://github.com/sindresorhus/awesome) of resources for astronomers interested in Data Science. *Everyone* is invited to [contribute](CONTRIBUTING.md) by pull request. 4 | 5 | ## Table of Contents 6 | 7 | - [Books](#Books) 8 | - [Blogs](#Blogs) 9 | - [Twitter](#twitter) 10 | - [Popular Websites](#popular-websites) 11 | - [Courses](#Courses) 12 | - [Repositories](#Repositories) 13 | - [Other](#Other) 14 | - [Other Awesome Lists](#other-awesome-lists) 15 | - [Contribute](#contribute) 16 | - [License](#license) 17 | 18 | ### Books 19 | 20 | - [Modern Statistical Methods for Astronomy](https://astrostatistics.psu.edu/MSMA/) by Eric D. Feigelson & G. Jogesh Babu. R scripts and datasets available for download from the website. 21 | - [Statistics, Data Mining, and Machine Learning in Astronomy](https://github.com/astroML/astroML-notebooks) by Željko Ivezić, Andrew Connolly, Jacob Vanderplas, and Alex Gray 22 | - [Python for Astronomers](https://github.com/prappleizer/prappleizer.github.io) by Imad Pasha and Chris Agostino. Also [interactive webpage](https://prappleizer.github.io/) and [textbook](https://prappleizer.github.io/textbook.pdf). 23 | - [Machine Learning for Physics and Astronomy](https://press.princeton.edu/books/paperback/9780691206417/machine-learning-for-physics-and-astronomy) by Viviana Acquaviva. Notebooks and slide decks with resources available for download under the "Resources" tab. 24 | 25 | ### Blogs 26 | 27 | - [AAS Policy Blog](http://aas.org/policy/policy-blog) Josh Shiode 28 | - [AstroBetter](http://www.astrobetter.com/) Kelle Cruz, Joanna Bridge and many other contributors 29 | - [astrobites](https://astrobites.org/) The astro-ph reader's digest 30 | - [AstroWright](http://sites.psu.edu/astrowright/) Jason Wright 31 | - [Hogg Blog](http://hoggresearch.blogspot.com/) David W. Hogg 32 | - [gully](http://gully.github.io/blog/) Michael Gully-Santiago 33 | - [Statistical Modeling Columbia](https://statmodeling.stat.columbia.edu/) Andrew Gelman et al. 34 | - [Xi'An' OG](https://xianblog.wordpress.com/) Christian Robert 35 | - [Statistical Thinking](https://www.fharrell.com/#posts) Frank Harrell 36 | - [Statisticians React to the News](https://blog.isi-web.org/react/) 37 | - [Robert Kosara](https://eagereyes.org/) Visualization & communication 38 | - [Junk Charts](https://junkcharts.typepad.com/) Kaiser Fung 39 | - [Multiple Views](https://medium.com/multiple-views-visualization-research-explained) visualization research explained 40 | 41 | ### Twitter 42 | 43 | People who work in this space and are occasionally active on Twitter: 44 | 45 | - [Daniela Huppenkothen](https://twitter.com/Tiana_Athriel) 46 | - [Dustin Lang](https://twitter.com/dstndstn) 47 | - [Gautham Narayan](https://twitter.com/gsnarayan) 48 | - [Jake VanderPlas](https://twitter.com/jakevdp) 49 | - [John Wu](https://twitter.com/jwuphysics) 50 | - [Joshua Bloom](https://twitter.com/profjsb) 51 | - [Josh Peek](https://twitter.com/jegpeek) 52 | - [Marc Huertas-Company](https://twitter.com/MHuertasCompany) 53 | - [Michelle Ntampaka](https://twitter.com/astro_michelle) 54 | - [NOIRLab DataLab](https://twitter.com/DataLabAstro) 55 | - [Peter Melchior](https://twitter.com/peter_melchior) 56 | - [Viviana Aquaviva](https://twitter.com/AstroVivi) 57 | 58 | ### Popular websites 59 | 60 | In the following, be critical, not all articles are written by specialists. Some are also experiements and others are just for fun. 61 | 62 | - [Towards data science](https://towardsdatascience.com/) 63 | - [Medium/Data Science](https://medium.com/tag/data-science) 64 | - [Techradar](https://www.techradar.com/pro) 65 | - [devblogs/python](https://devblogs.microsoft.com/python/) Formerly Planet Python 66 | - [KDnuggests](https://www.kdnuggets.com/) Machine Learning, Data Science, Big Data, Analytics, AI. 67 | - [Machine Learning Mastery](https://machinelearningmastery.com/blog/) by Jason Brownlee 68 | - [Unofficial Google Data Science](https://www.unofficialgoogledatascience.com/) 69 | - [TechXplore/ML](https://techxplore.com/machine-learning-ai-news/) 70 | 71 | ### Courses 72 | - [Analytics Vidhya](https://www.analyticsvidhya.com/) 73 | - [Google ML Crash Course](https://developers.google.com/machine-learning/crash-course) 74 | 75 | ### Repositories 76 | 77 | #### Libraries 78 | - [Astronomaly](https://github.com/MichelleLochner/astronomaly) A flexible framework for anomaly detection in astronomy. 79 | 80 | #### Tutorials 81 | - [Rubin Observatory Tutorial Jupyter Notebooks for Data Preview 0](https://github.com/rubin-dp0/tutorial-notebooks) 82 | - STScI [general Jupyter Notebooks](https://github.com/spacetelescope/notebooks) 83 | - STScI [JWST Jupyter Notebooks](https://github.com/spacetelescope/jdat_notebooks) showcasing pipeline and analysis tools via science use cases 84 | - [Tutorials for creating figures, tables, or other content](https://github.com/AASJournals/Tutorials) by AAS Journals 85 | 86 | #### Course and Workshop Materials 87 | - Astro Hack Week tutorial materials: [2015](https://github.com/AstroHackWeek/AstroHackWeek2015), [2016](https://github.com/AstroHackWeek/AstroHackWeek2016), [2017](https://github.com/AstroHackWeek/AstroHackWeek2017), [2018](https://github.com/AstroHackWeek/AstroHackWeek2018), [2019](https://github.com/AstroHackWeek/AstroHackWeek2019), [2020](https://github.com/AstroHackWeek/AstroHackWeek2020). Also see YouTube for recordings of some events: [2015](https://www.youtube.com/watch?v=BBDCCvY9knI&list=PLFyFNCb8irhOjeD9G7e4myw6Ot7DaBk2W), [2016](https://www.youtube.com/watch?v=EjnR_Ehz-9M&list=PLKW2Azk23ZtQSHmwOpObPEr58Pe1rpIdB), [2020](https://www.youtube.com/user/SimonsFoundation/search?query=%22Astro%20Hack%20Week%22) 88 | - [Code/Astro Workshop Workshop materials](https://github.com/semaphoreP/codeastro) by Jason Wang. A Software Engineering Workshop for Astronomy. 89 | - [ESCAPE data science summer school 2021](https://github.com/escape2020/school2021) Materials on software development and open science by the European Science Cluster of Astronomy & Particle physics ESFRI research infrastructures project. 90 | - [Foundations of Astronomical Data Science](https://datacarpentry.org/astronomy-python/) Carpentries Curriculum 91 | - [Kavli 2019 Summer Program in Astrophysics Lectures](https://github.com/dkirkby/kavli2019) by David Kirkby. Machine Learning in the era of large astronomical surveys. 92 | - [GROWTH Astronomy School 2019](https://www.growth.caltech.edu/growth-astro-school-2019-resources.html): a school on multi-messenger time domain astronomy 93 | - [Machine Learning and Statistics for Physicists](https://github.com/dkirkby/MachineLearningStatistics) by David Kirby. Material for a UC Irvine course offered by the Department of Physics and Astronomy. 94 | - [Analytical Methods and Applications to Astrophysics and Astronomy](https://www.youtube.com/watch?v=SXPdI_P0_cQ&list=PLUG23R), Statistical and Applied Mathematical Sciences Institute (SAMSI), 2016 95 | - [Time Series Methods for Astronomy](https://www.youtube.com/watch?v=chcpop1a-g8&list=PLUG23RFb_6KftdxAP6e0IRbSlnojX5Zq9), Statistical and Applied Mathematical Sciences Institute (SAMSI), 2017 96 | - [Big Data Physics: Methods of Machine Learning](https://github.com/gtrichards/PHYS_440_540) by Gordon Richards at Drexel University; lots of useful links in the readme. 97 | - [Astrostatistics and Machine Learning class for the MSc degree in Astrophysics at the University of Milan-Bicocca](https://github.com/dgerosa/astrostatistics_bicocca_2024) by Davide Gerosa 98 | - [Machine Learning for Physics and Astronomy (2022-2023)](https://github.com/LHCfitNikhef/ML4PA) by Juan Rojo, Tanjona Rabemananjara and Ryan van Mastrigt 99 | - [Big Data in Astrophysics, Spring 2023](https://github.com/mcoughlin/ast8581_2023_Spring) by Michael Coughlin and Jie Ding, University of Minnesota 100 | - [ASTR 596: Fundamentals of Data Science, Spring 2023](https://github.com/gnarayan/ast596_2023_Spring) by Gautham Narayan, University of Illinois Urbana Champaign 101 | - [Astrostatistics, Vanderbuilt, Spring 2022](https://github.com/VanderbiltAstronomy/astr_8070_s22) by Stephen R. Taylor 102 | - [La Serena School for Data Science, 2023](http://lssds.aura-astronomy.org/winter_school/content/2023-final-program) 103 | 104 | 105 | #### GitHub Orgs 106 | - [Astronomy Commons GitHub Org](https://github.com/astronomy-commons) Software Infrastructure for Science Platforms and Scalable Astronomy on Cloud Resources 107 | - [NOIRLab DataLab GitHub Org](https://github.com/astro-datalab) Resources for working with the NOIRLab archives, including Jupyter Notebooks. 108 | - [SDSS](https://github.com/sdss) 109 | 110 | 111 | ### Other 112 | - [Deep Skies](https://deepskieslab.com/) A community that fosters knowledge transfer for the accelerated application of artificial intelligence to astronomical challenges. 113 | - [ML Club](https://docs.google.com/document/d/1GGtE-YIuAWlmpKSr38_kyiF-Fklszhkh4FkiYWzBAho/pub) An online discussion on Machine Learning 114 | for astrophysicists. Slides and recordings of events from 2018 to 2021. Currently on hiatus. 115 | 116 | 117 | ## Other Awesome Lists 118 | 119 | * [awesome-datascience](https://github.com/academic/awesome-datascience) 120 | * [awesome-astronomy](https://github.com/jonathansick/awesome-astronomy) by Jonathan Sick 121 | * [awesome-awesome](https://github.com/emijrp/awesome-awesome) 122 | * [awesome-awesomeness](https://github.com/bayandin/awesome-awesomeness) per coding language 123 | * [sindresorhus/awesome](https://github.com/sindresorhus/awesome) The original 124 | * [The Warren](https://github.com/torchhound/warren) 125 | 126 | ## Contribute 127 | 128 | Contributions welcome! Read the [contribution guidelines](CONTRIBUTING.md) first. 129 | 130 | ## License 131 | 132 | [![CC0][CC0-badge]][CC0-link] 133 | 134 | 135 | See [LICENSE](LICENSE). 136 | 137 | [awesome-badge]: https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg 138 | [awesome-link]: https://github.com/sindresorhus/awesome 139 | [CC0-badge]: http://mirrors.creativecommons.org/presskit/buttons/88x31/svg/cc-zero.svg 140 | [CC0-link]: https://creativecommons.org/publicdomain/zero/1.0/ 141 | --------------------------------------------------------------------------------