resources

  |   Source

A - totally incomplete - list of resources I have come across on Python and Python for data analysis and visualization, loosely organized by category:


Object Oriented Programming in Python

Python as a glue: wrapping of C, C++, Fortran or the Cython module

Real-time acquisition, physical programming

Image processing

Symbolic maths

  • The SymPy library is a Python library for symbolic mathematics. It supports polynomials, calculus, solving equations, etc
  • The sage software: Mission: Creating a viable free open source alternative to Magma, Maple, Mathematica and Matlab

Geospatial statistics

  • PySAL: PySAL is a cross-platform library of spatial analysis functions written in Python. It is intended to support the development of high level applications for spatial analysis.
  • GeoPandas: A project based on Pandas to make working with geospatial data in python easier
  • Rasterio: Clean and fast and geospatial raster I/O with Numpy support, developed by the team at https://www.mapbox.com/
  • Pyproj: Performs cartographic transformations and geodetic computations. Wrapper around the Proj version 4 library
  • Python GDAL/OGR: Python bindings + tools around the Geospatial Data Abstraction Library
  • Python GIS resources: a blog on geospatial python
  • High Performance Geostatistics Library: A library written in C++ / Python implementing geostatistical algorithms (e.g. kriging, correlograms, etc)

Biology, ecology

  • Biopython: Biopython is a set of freely available tools for biological computation written in Python by an international team of developers.
  • GeoEco: Open source geoprocessing toolbox designed for coastal and marine researchers and GIS analysts who work with spatially-explicit ecological and oceanographic data. For Windows (> XP) only.
  • Galaxy: Galaxy is a scientific workflow, data integration and data and analysis persistence and publishing platform that aims to make computational biology accessible to research scientists that do not have computer programming experience.

Computational Fluid Dynamics and PDE solvers

Python on the GPU

  • PyCUDA: PyCUDA lets you access Nvidia‘s CUDA parallel computation API from Python

Parallel computing with Python / IPython

Signal processing in Python

Python for Matlab and R users

Some URLs and blogs

Github repositories: notebooks and accompanying material

Some books

Some interesting libraries, built on top of the main Scientific stack

  • xray: N-D labeled arrays and datasets in Python.

  • PYMC: By Chris Fonnesbeck, Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo.

  • Seaborn: Statistical data visualization, by Michael Waskom. Its graphical representation of linear models is particularly interesting.

  • ggplot: For R users, a 'port' of the ggplot2 package to Python, see here for what's new in the latest release.

  • coards: A COARDS compliant time parser. See also netcdftime which is part of the NetCDF4 module

  • seawater: Similar to the MATLAB toolboxes SEAWATER from CSIRO and parts of OCEANS from Woods Hole Institute.

  • fluid: Procedures to study fluids on Python, focused for oceanography, meteorology and related sciences.

  • kyPyWavelet: Continuous wavelet transform module for Python ala Torrence and Compo. Some manual edits were necessary to make it work for me ...

  • pyresample: Resampling (reprojection) of geospatial image data in Python

  • Rpy2: calling R from Python

Some articles on open and reproducible research

Comments powered by Disqus
    Share