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Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis.In particular, it offers data structures and operations for manipulating numerical tables and time series.
PASS Sample Size Software (PASS) – power and sample size software from NCSS; Plotly – plotting library and styling interface for analyzing data and creating browser-based graphs. Available for R, Python, MATLAB, Julia, and Perl; Primer-E Primer – environmental and ecological specific; PV-WAVE – programming language comprehensive data ...
IMSL (International Mathematics and Statistics Library) is a commercial collection of software libraries of numerical analysis functionality that are implemented in the computer programming languages C, Java, C#.NET, and Fortran. A Python interface is also available.
Demonstration doctests ===== This is just an example of what a README text looks like that can be used with the doctest.DocFileSuite() function from Python's doctest module. Normally, the README file would explain the API of the module, like this: >>> a = 1 >>> b = 2 >>> a + b 3 Notice, that we just demonstrated how to add two numbers in Python ...
De facto standard for matrix/tensor operations in Python. Pandas, a library for data manipulation and analysis. SageMath is a large mathematical software application which integrates the work of nearly 100 free software projects and supports linear algebra, combinatorics, numerical mathematics, calculus, and more. [17]
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
pvlib python's documentation is online and includes many theory topics, an intro tutorial, an example gallery, and an API reference. The software is broken down by the steps shown in the PVPMC modeling diagram. irradiance and weather retrieval and solar position calculation; irradiance decomposition and transposition to the plane of the array