Showing 8 open source projects for "matplotlib"

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  • 1
    Matplotlib

    Matplotlib

    matplotlib: plotting with Python

    Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a projection and mapping toolkit (Cartopy). ...
    Downloads: 24 This Week
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  • 2
    Peroxide

    Peroxide

    Rust numeric library with high performance and friendly syntax

    Rust numeric library contains linear algebra, numerical analysis, statistics and machine learning tools with R, MATLAB, Python-like macros. Peroxide uses a 1D data structure to represent matrices, making it straightforward to integrate with BLAS (Basic Linear Algebra Subprograms). This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. For users familiar with numerical computing libraries like...
    Downloads: 6 This Week
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  • 3
    Homemade Machine Learning

    Homemade Machine Learning

    Python examples of popular machine learning algorithms

    ...The purpose is pedagogical: you’ll see linear regression, logistic regression, k-means clustering, neural nets, decision trees, etc., built in Python using fundamentals like NumPy and Matplotlib, not hidden behind API calls. It is well suited for learners who want to move beyond library usage to understand how algorithms operate internally—how cost functions, gradients, updates and predictions work.
    Downloads: 0 This Week
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  • 4
    vim-jukit

    vim-jukit

    Jupyter-Notebook inspired Neovim/Vim Plugin

    REPL plugin and Jupyter-Notebook alternative for (Neo)Vim. This plugin is aimed at users in search for a REPL plugin with lots of additional features.
    Downloads: 8 This Week
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    Zipline

    Zipline

    Zipline, a Pythonic algorithmic trading library

    Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python...
    Downloads: 0 This Week
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  • 6
    Brand new cheatsheets and handouts

    Brand new cheatsheets and handouts

    Matplotlib 3.1 cheat sheet

    ...For practitioners working on data-heavy projects, dashboards, or research code where plotting is frequent, it helps speed up development by reducing context-switching and documentation navigation overhead. It is especially useful when you know roughly what you want (e.g. “I need a scatter + histogram marginal plot”) but don’t remember the exact Matplotlib call.
    Downloads: 0 This Week
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  • 7
    The Neural Process Family

    The Neural Process Family

    This repository contains notebook implementations

    ...Each notebook includes theoretical explanations, key building blocks, and executable code that runs directly in Google Colab, requiring no local setup. Implementations rely only on standard dependencies such as NumPy, TensorFlow, and Matplotlib, and provide visualizations of model performance.
    Downloads: 2 This Week
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  • 8
    data-science-ipython-notebooks

    data-science-ipython-notebooks

    Data science Python notebooks: Deep learning

    Data Science IPython Notebooks is a broad, curated set of Jupyter notebooks covering Python, data wrangling, visualization, machine learning, deep learning, and big data tools. It aims to be a practical map of the ecosystem, showing hands-on examples with libraries such as NumPy, pandas, matplotlib, scikit-learn, and others. Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action. Advanced sections touch on neural networks and distributed computing topics, helping you bridge from basics to production-adjacent workflows. The collection is suitable for self-paced study, quick reference, or as teaching materials in workshops. ...
    Downloads: 0 This Week
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