Showing 14 open source projects for "numerical python"

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  • 1
    Sweetviz

    Sweetviz

    Visualize and compare datasets, target values and associations

    ...Shows how a target value (e.g. "Survived" in the Titanic dataset) relates to other features. Sweetviz integrates associations for numerical (Pearson's correlation), categorical (uncertainty coefficient) and categorical-numerical (correlation ratio) datatypes seamlessly, to provide maximum information for all data types. Automatically detects numerical, categorical and text features, with optional manual overrides. min/max/range, quartiles, mean, mode, standard deviation, sum, median absolute deviation, coefficient of variation, kurtosis, skewness.
    Downloads: 0 This Week
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  • 2
    VisPy

    VisPy

    Main repository for Vispy

    Vispy is an open-source, high-performance interactive visualization library in Python, designed for creating scientific visualizations and interactive plots. It leverages the power of modern Graphics Processing Units (GPUs) through OpenGL to render large datasets efficiently. Vispy supports a wide range of visualization types, including 2D plots, 3D visualizations, volume rendering, and more, making it suitable for scientific research, data analysis, and educational purposes.
    Downloads: 0 This Week
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  • 3
    Population Shift Monitoring

    Population Shift Monitoring

    Monitor the stability of a Pandas or Spark dataframe

    popmon is a package that allows one to check the stability of a dataset. popmon works with both pandas and spark datasets. popmon creates histograms of features binned in time-slices, and compares the stability of the profiles and distributions of those histograms using statistical tests, both over time and with respect to a reference. It works with numerical, ordinal, categorical features, and the histograms can be higher-dimensional, e.g. it can also track correlations between any two...
    Downloads: 0 This Week
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  • 4
    ydata-profiling

    ydata-profiling

    Create HTML profiling reports from pandas DataFrame objects

    ydata-profiling primary goal is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. Like pandas df.describe() function, that is so handy, ydata-profiling delivers an extended analysis of a DataFrame while allowing the data analysis to be exported in different formats such as html and json.
    Downloads: 0 This Week
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  • 5
    FiniteDifferences.jl

    FiniteDifferences.jl

    High accuracy derivatives, estimated via numerical finite differences

    FiniteDifferences.jl estimates derivatives with finite differences. See also the Python package FDM. FiniteDiff.jl and FiniteDifferences.jl are similar libraries: both calculate approximate derivatives numerically. You should definitely use one or the other, rather than the legacy Calculus.jl finite differencing, or reimplementing it yourself. At some point in the future, they might merge, or one might depend on the other.
    Downloads: 0 This Week
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  • 6
    Euler Math Toolbox

    Euler Math Toolbox

    Numerical and Symbolic Math Tool

    Euler is a powerful all-in-one numerical software and includes Maxima for seamless symbolic computations. Euler supports Latex for math display, Povray for photo-realistic 3D scenes, Python, Matplotlib and C for scripting, and contains a full programming language. Features include libraries for numerical algorithms, optimization, plotting in 2D and 3D, graphics export, a complete help system, tutorials and examples.
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    Downloads: 83 This Week
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  • 7
    WxMAP2
    A python-based system to diagnosis and make weather maps (wxmap) of numerical weather prediction models using the Grid Analysis and Display System (GrADS) from opengrads.org
    Downloads: 4 This Week
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  • 8
    Kinetic.jl

    Kinetic.jl

    Universal modeling and simulation of fluid mechanics upon ML

    Kinetic is a computational fluid dynamics toolbox written in Julia. It aims to furnish efficient modeling and simulation methodologies for fluid dynamics, augmented by the power of machine learning. Based on differentiable programming, mechanical and neural network models are fused and solved in a unified framework. Simultaneous 1-3 dimensional numerical simulations can be performed on CPUs and GPUs.
    Downloads: 1 This Week
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  • 9

    PythonStatsLab

    A collection of useful statistical functions written in Python

    There are functions for numerical integration of the standard normal probability distribution. They can be used to find probabilities, find z-alpha values, calculate confidence interval, etc. New functionality I wish to add are hypothesis testing and calculation of p-value, type I & II errors, etc. These functions would come in handy to anyone taking introductory or intermediate-level courses in probability, statistics and data analysis. There are several numerical integration techniques...
    Downloads: 0 This Week
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  • 10
    PyMaTi is a simple and easy to use GUI for numerical and scientific computing in Python. It surrounds well know packages NumPy and Matplotlib and provides possibility to immediately play with numerical python from intuitive user interface.
    Downloads: 0 This Week
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  • 11
    The main purpose of "python2xlw" is to create an Excel-compatible file which can be sent to users via the web as an excel application. The motivation is mainly to support the display of XY Scatter plots and tabular numerical data(eg engineering data)
    Downloads: 0 This Week
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  • 12
    VisAD is a Java component library for interactive and collaborative visualization and analysis of numerical data.
    Downloads: 0 This Week
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  • 13
    MatPy is a Python package for numerical linear algebra and plotting with a MatLab-like interface. It currently consists of wrappers around Numeric and Gnuplot packages, but eventually may be implemented directly in C/C++, or as interface to Octave.
    Downloads: 0 This Week
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  • 14

    CoSimA+

    The Co-Simulation Adaptation Platform

    The co-simulation adapation platform serves as programming framework and middleware to enable coupling of distributed, heterogeneous numerical models. The framework facilitates the adaptation and integration of new sub-models into a common simulation platform.
    Downloads: 0 This Week
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