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Component Library solution for developers
About NetworkX
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Generators for classic graphs, random graphs, and synthetic networks. Additional benefits from Python include fast prototyping, easy to teach, and multi-platform. Network structure and analysis measures.
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PyQtGraph
PyQtGraph is a pure-python graphics and GUI library built on PyQt/PySide and NumPy. It is intended for use in mathematics/scientific/engineering applications. Despite being written entirely in python, the library is very fast due to its heavy leverage of NumPy for number crunching and Qt's GraphicsView framework for fast display. PyQtGraph is distributed under the MIT open-source license. Basic 2D plotting in interactive view boxes. Line and scatter plots. Data can be panned/scaled by mouse. Fast drawing for real-time data display and interaction. Displays most data types (int or float; any bit depth; RGB, RGBA, or luminance). Functions for slicing multidimensional images at arbitrary angles (great for MRI data). Rapid update for video display or real-time interaction. Image display with interactive lookup tables and level control. Mesh rendering with isosurface generation. Interactive viewports rotate/zoom with mouse. Basic 3D scenegraph for easier programming.
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pandas
pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language. Tools for reading and writing data between in-memory data structures and different formats: CSV and text files, Microsoft Excel, SQL databases, and the fast HDF5 format. Intelligent data alignment and integrated handling of missing data: gain automatic label-based alignment in computations and easily manipulate messy data into an orderly form.Aggregating or transforming data with a powerful group by engine allowing split-apply-combine operations on data sets. Time series-functionality: date range generation and frequency conversion, moving window statistics, date shifting and lagging. Even create domain-specific time offsets and join time series without losing data.
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CVXOPT
CVXOPT is a free software package for convex optimization based on the Python programming language. It can be used with the interactive Python interpreter, on the command line by executing Python scripts, or integrated in other software via Python extension modules. Its main purpose is to make the development of software for convex optimization applications straightforward by building on Python’s extensive standard library and on the strengths of Python as a high-level programming language. Efficient Python classes for dense and sparse matrices (real and complex), with Python indexing and slicing and overloaded operations for matrix arithmetic. Interfaces to the linear programming solver in GLPK, the semidefinite programming solver in DSDP5, and the linear, quadratic and second-order cone programming solvers in MOSEK.
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h5py
The h5py package is a Pythonic interface to the HDF5 binary data format. It lets you store huge amounts of numerical data, and easily manipulate that data from NumPy. For example, you can slice into multi-terabyte datasets stored on disk, as if they were real NumPy arrays. Thousands of datasets can be stored in a single file, categorized and tagged however you want. H5py uses straightforward NumPy and Python metaphors, like dictionary and NumPy array syntax. For example, you can iterate over datasets in a file, or check out the .shape or .dtype attributes of datasets. You don't need to know anything special about HDF5 to get started. In addition to the easy-to-use high level interface, h5py rests on a object-oriented Cython wrapping of the HDF5 C API. Almost anything you can do from C in HDF5, you can do from h5py.
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Starting Price:
Free
Free Version:
Free Version available.
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NetworkX
networkx.org
Videos and Screen Captures
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MongoDB Atlas runs apps anywhere
MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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