NetworkX Reviews

PyQtGraph is a pure Python graphics and GUI library based on PyQt/PySide or NumPy. It is intended for use in mathematics/scientific/engineering applications. Although written entirely in Python, the library is extremely fast thanks to its heavy use of NumPy to perform number crunching and Qt GraphicsView framework for fast display. PyQtGraph is available under the MIT open source license. Interactive view boxes for basic 2D plotting. Line and scatter plots. Data can be scaled/panned with the mouse. Rapid drawing allows for real-time data display. Displays all data types (int, float, any bit depth, RGB, RGBA or luminance). Multidimensional images can be sliced at arbitrary angles using these functions (great for MRI data). Rapid update for video display and real-time interaction Image display with interactive level control and lookup tables. Mesh rendering with isosurface generator. Interactive viewports can be rotated/zoomed with the mouse. For easier programming, use the basic 3D scenegraph.

statsmodels is an Python module that provides classes, functions, and methods for the estimation of various statistical models. It also allows for statistical data exploration and statistical tests. Each estimator has a comprehensive list of available result statistics. To ensure accuracy, the results are compared to existing statistical packages. The package is available under the Modified BSD (3 clause) license. statsmodels allows you to specify models using R-style formulas or pandas DataFrames. To see the available results, take a look at dir (results). Results describe attributes. __doc__, results methods have their own documentation strings. Numpy arrays can be used in place of formulas. Installing statsmodels as part of the Anaconda distribution is the easiest way to do so. This cross-platform distribution allows for data analysis and scientific computing. This is the preferred method of installation for most users.