Search Results for "statistical"

spaCy is a library built on the very latest research for advanced Natural Language Processing (NLP) in Python and Cython. Since its inception it was designed to be used for real world applications-- for building real products and gathering real insights. It comes with pretrained statistical models and word vectors, convolutional neural network models, easy deep learning integration and so much more. spaCy is the fastest syntactic parser in the world according to independent benchmarks, with an accuracy within 1% of the best available. It's blazing fast, easy to install and comes with a simple and productive API.

WeasyPrint is a smart solution helping people to create PDF documents. You can generate gorgeous statistical reports, invoices, tickets, and anything you want as long as you have some webdesign skills! Design your documents just as you design your websites! WeasyPrint follows the widely used HTML and CSS specifications from the W3C. You can use your usual web tools, languages and frameworks, but for print. Creating high-quality digital documents requires features that you love to use as readers, tables of contents, links, annotations, optimized images, attachments, WeasyPrint provides many features out of the box, and even gives you the possibility to add your own ways to customize your PDF files. ...

plotly.py is a browser-based, open source graphing library for Python that lets you create beautiful, interactive, publication-quality graphs. Built on top of plotly.js, it is a high-level, declarative charting library that ships with more than 30 chart types. Everything from statistical charts and scientific charts, through to maps, 3D graphs and animations, plotly.py lets you create them all. Graphs made with plotly.py can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using Chart Studio Cloud.

Zipline Reloaded is a maintained Python library for event-driven backtesting of algorithmic trading strategies. It continues the original Zipline project after Quantopian ended operations. Developers write trading algorithms while the engine simulates orders, market events, portfolio changes, and strategy performance over historical data. Common statistics such as moving averages and linear regression are available within algorithm workflows. Pandas-based input and output integrate naturally...

The open-source framework for precision data testing for data scientists and ML engineers. Pandera provides a simple, flexible, and extensible data-testing framework for validating not only your data but also the functions that produce them. A simple, zero-configuration data testing framework for data scientists and ML engineers seeking correctness. Access a comprehensive suite of built-in tests, or easily create your own validation rules for your specific use cases. Validate the functions...

darts is a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn. The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models...

PyG2Plot is a Python 3 binding for AntV G2Plot, an interactive and responsive charting library. It lets Python users create statistical charts through a small amount of code while relying on G2Plot’s grammar-of-graphics foundation. The library is inspired by pyecharts and is designed to make web-based charts available from Python workflows. Users create a Plot instance, set chart options, and render the result as an HTML file, HTML string, notebook preview, or JupyterLab output. ...

Java-based scientific graphics with support for Java, Groovy, MATLAB, Python, the R statistical environment, Scala and SciLab.

The purpose of the Metabrain library is to give developers a way to extract this information from the Internet without resorting to natural language parsing or other complex techniques, using instead statistical methods and patterns/trends analysis.

PyAnnotation is a Python Library to access and manipulate linguistically annotated corpus files. Supported file formats are Kura XML, Elan XML and Toolbox files. A Corpus Reader API is provided to support statistical analysis within the NLTK.

This project hosts tools used for analysis of Gaussian Mixture Distributions (GMDs) which are used for statistical signal processing. The tools are libraries for implementing GMD operations and programs used to analyze properties of GMDs.