rossant / Awesome Scientific Python
A curated list of awesome scientific Python resources
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Awesome Scientific Python
A curated list of awesome scientific Python resources.
Contents
- Contents
- Libraries
- Books
- Courses
- Tutorials
- Videos
- License
Libraries
Core libraries
IPython/Jupyter
Effective interactive computing, data analysis, and visualization.
- IPython - Interactive Python computing in the terminal.
- Jupyter - Open interactive computing in many programming languages.
- Jupyter Notebook - Web-based environment for interactive computing.
- JupyterLab - Next-generation web-based interactive programming and computing environment.
NumPy
Multidimensional array computing.
SciPy
Numerical computing library.
pandas
Data analysis library.
scikit-learn
Machine learning library.
matplotlib
Data visualization and graphics library.
SymPy
Symbolic computing library.
Other scientific libraries
Data visualization
- Bokeh - Interactive visualization for the web.
- Altair - Declarative visualization in Python.
- seaborn - Statistical data visualization.
- bqplot - 2D interactive visualization in Jupyter.
- plotnine - Grammar of Graphics implementation in Python based on ggplot2.
- plotly - Interactive data visualization on the web.
- HoloViews - Data visualization library.
- Napari - Multi-dimensional image viewer for python.
3D visualization
- ipyvolume - 3D visualization with Jupyter.
- VisPy - Interactive GPU-accelerated visualization.
- Glumpy - Scientific visualization in modern OpenGL.
- vedo - Scientific analysis and visualization based on VTK.
Image processing
- scikit-image - Image processing in Python.
- Pillow - Python Imaging Library (PIL) fork in Python.
- OpenCV - Computer vision library.
Graphs
- NetworkX - Graph and network structures and algorithms.
- Graph-tool - Manipulation and statistical analysis of graphs.
Neural networks
- PyTorch - Neural networks and deep learning in Python.
- Keras - Python deep learning library.
- TensorFlow - Machine learning framework.
- Caffe - Deep learning framework.
Statistics
- PyMC3 - Bayesian statistical modeling.
- statsmodels - Statistical models.
- emcee - ensemble sampler for markov chain monte carlo.
Compilation
Parallel computing
- ipyparallel - Parallel computing with IPython
- Dask - Parallel computing with task scheduling.
GPU computing
Domain-specific libraries
Geospatial data
- GeoPandas - pandas for geospatial data.
- Shapely - Manipulation and analysis of geometric objects.
- Folium - Interactive maps in Python with leaflet.js.
Astrophysics
Molecular simulations
- MGLTools - Visualization and analysis of molecular structures.
- MDAnalysis - Molecular dynamics simulations
- pysimm - Molecular simulations
- PyMOL - Molecular visualization
- Molecular Modeling Toolkit
Bioinformatics
- Biopython - Biological computations.
- PyBioMed - Descriptors of biological molecules.
- khmer - k-mer counting, filtering, and graph traversal.
Neuroimaging
- NiBabel - Neuro-imaging file formats.
- Nilearn - Machine learning for neuro-imaging.
- NiTime - Time series.
- MNE - MEG and EEG.
- DIPY - Diffusion MR imaging.
- Expyriment - Behavioral and neuroimaging experiments.
Neuroscience
- Brian2 - Simulations of spiking neural networks.
- Spyking Circus - Spike sorting on large extracellular recordings.
- Klusta - Spike detection and clustering-based spike sorting.
- phy - Manual spike sorting for high-density multielectrode arrays.
- NeuroTools - Tools for neural simulations.
- Neo - File formats for neuroscience.
- PsychoPy - Psychology and neuroscience experiments.
- Nengo - Simulation of large-scale brain models
- PyGaze - Eye tracking.
Mathematics
Lists of libraries
- Python Numeric and Scientific - on python.org.
- Scientific Computing Tools for Python - on scipy.org.
- Useful libraries for data science in Python - by Sebastian Raschka.
- Python for Scientific Audio - by Fabian-Robert Stöter.
Books
- Python Data Science Handbook - Jake VanderPlas, O'Reilly, 2016, 541 pages.
- Python for Data Analysis - William McKinney, O'Reilly, 2017, 544 pages (second edition).
- Learning IPython for Interactive Computing and Data Analysis, Cyrille Rossant, Packt Publishing, 2015, 200 pages (second edition).
- IPython Interactive Computing and Visualization Cookbook, Cyrille Rossant, Packt Publishing, 2018, 548 pages (second edition).
- A Primer on Scientific Programming with Python - Hans Petter Langtangen, Springer, 2014, 872 pages.
- Exploring Data with Python - Naomi Ceder, Manning 2018, 110 pages.
- Deep Learning with Python - François Chollet, Manning, 2017, 384 pages.
- Python Machine Learning - Sebastian Raschka & Vahid Mirjalili, Packt Publishing, 2017, 622 pages (second edition).
Courses
- Stat 159/259, Reproducible and Collaborative Data Science - Fernando Perez, Berkeley University, 2017.
- CME 193, Introduction to Scientific Python - Stanford University, Sven Schmit, 2015.
- Using Python for Research - Jukka-Pekka Onnela, Harvard University Online Learning.
- Introduction to Data Analytics and Machine Learning with Python - University of London.
- PHY 546: Python for Scientific Computing - Stony Brook University, Michael Zingale, 2018.
- Python for Data Analysis - Luke Thompson, NOAA.
- Coursera Data Science with Python - University of Michigan.
- edX Python for Data Science - UC San Diego, Ilkay Altintas, Leo Porter.
- edX Foundations of Data Science: Computational Thinking with Python - UC Berkeley, Ani Adhikari, John DeNero, David Wagner.
- Python Course - Bernd Klein.
- Intro to Python for Data Science - DataCamp, Filip Schouwenaars.
- Schools using Python - on python.org.
Tutorials
- SciPy Lecture Notes
- Lectures on scientific computing with Python - Robert Johansson.
- Python NumPy tutorial - Justin Johnson, Stanford University.
- Real Python Python Data Science Tutorials
- A gallery of interesting Jupyter Notebooks
- List of Python Data Science Tutorials - Ujjwal Karn.
Videos
- SciPy 2018: Scientific Computing with Python Conference - 97 YouTube videos.
- SciPy 2017: Scientific Computing with Python Conference - 91 YouTube videos.
- SciPy 2016: Scientific Computing with Python Conference - 92 YouTube videos.
- SciPy 2015: Scientific Computing with Python Conference - 116 YouTube videos.
- SciPy 2014: Scientific Computing with Python Conference - 121 YouTube videos.
- SciPy 2013: Scientific Computing with Python Conference - 33 YouTube videos.
License
To the extent possible under law, Cyrille Rossant has waived all copyright and related or neighboring rights to this work.
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].