Python libraries for data visualisation, data analysis and scientific computing

Python libraries for data visualisation, data analysis and scientific computing mainly used for Big Data.

Libraries for Data Visualization

• matplotlib – A Python 2D plotting library.
• bokeh – Interactive Web Plotting for Python.
• ggplot – Same API as ggplot2 for R.
• plotly – Collaborative web plotting for Python and matplotlib.
• pygal – A Python SVG Charts Creator.
• pygraphviz – Python interface to Graphviz.
• PyQtGraph – Interactive and realtime 2D/3D/Image plotting and science/engineering widgets.
• SnakeViz – A browser based graphical viewer for the output of Python’s cProfile module.
• vincent – A Python to Vega translator.
• VisPy – High-performance scientific visualization based on OpenGL.

Libraries for Scientific Computing and Data Analysis

• astropy – A community Python library for Astronomy.
• bcbio-nextgen – A toolkit providing best-practice pipelines for fully automated high throughput sequencing analysis.
• bccb – Collection of useful code related to biological analysis.
• Biopython – Biopython is a set of freely available tools for biological computation.
• blaze – NumPy and Pandas interface to Big Data.
• cclib – A library for parsing and interpreting the results of computational chemistry packages.
• NetworkX – A high-productivity software for complex networks.
• Neupy – Running and testing different Artificial Neural Networks algorithms.
• NIPY – A collection of neuroimaging toolkits.
• Numba – Python JIT (just in time) complier to LLVM aimed at scientific Python by the developers of Cython and NumPy.
• NumPy – A fundamental package for scientific computing with Python.
• Open Babel – A chemical toolbox designed to speak the many languages of chemical data.
• Open Mining – Business Intelligence (BI) in Python (Pandas web interface)
• orange – Data mining, data visualization, analysis and machine learning through visual programming or Python scripting.
• Pandas – A library providing high-performance, easy-to-use data structures and data analysis tools.
• PyDy – Short for Python Dynamics, used to assist with workflow in the modeling of dynamic motion based around NumPy, SciPy, IPython, and matplotlib.
• PyMC – Markov Chain Monte Carlo sampling toolkit.
• RDKit – Cheminformatics and Machine Learning Software.
• SciPy – A Python-based ecosystem of open-source software for mathematics, science, and engineering.
• statsmodels – Statistical modeling and econometrics in Python.
• SymPy – A Python library for symbolic mathematics.
• zipline – A Pythonic algorithmic trading library.