Search Results for "google-visualization-python" - Page 24
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Showing 30660 open source projects for "google-visualization-python"
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LinearOperators.jl
Linear Operators for Julia
Operators behave like matrices (with some exceptions - see below) but are defined by their effect when applied to a vector. They can be transposed, conjugated, or combined with other operators cheaply. The costly operation is deferred until multiplied with a vector. -
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Flask
The Python micro framework for building web applications
...Flask has become one of the most popular Python web application frameworks, and has amassed a great number of extensions provided by the community that make adding new functionality easy. -
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Memento.jl
A flexible logging library for Julia
Memento is a flexible hierarchical logging library for Julia. -
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SuiteSparseGraphBLAS.jl
Sparse, General Linear Algebra for Graphs
A fast, general sparse linear algebra and graph computation package, based on SuiteSparse:GraphBLAS. -
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Octo.jl
Octo.jl is an SQL Query DSL in Julia
Octo.jl is an SQL Query DSL in Julia. It also comes with a very useful tool called Repo. You could Repo.get, Repo.insert! Repo.update! Repo.delete! for many database drivers without hand-written SQL. -
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ECharts
A powerful, interactive charting and visualization library for browser
ECharts is a free and open source charting and visualization library that gives you an easy way to add interactive, intuitive, custom charts to your commercial products, projects, presentations and more. It offers a rich set of features that includes rendering ability for ten-million-level data, Wechart and Powerpoint support, multi-dimension data analysis, and more. It also has a number of extensions for various applications. -
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Search with Lepton
Lightweight demo to build a conversational AI search engine quickly
...The implementation is intentionally minimal, containing fewer than 500 lines of code while still providing a complete working example of an AI-powered search system. It includes both a backend service written in Python and a web interface that allows users to interact with the search engine in a conversational format. Developers can configure different search providers and language models through environment variables, making it flexible for experimentation and prototyping. -
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TextFSM
Python module for parsing semi-structured text into python tables
TextFSM is a Python library created by Google that provides a template-based state machine engine for parsing semi-structured text. It is particularly useful for extracting structured data from command-line interface (CLI) outputs, such as those from network devices, routers, and switches. By defining parsing logic through reusable template files, TextFSM transforms unstructured text into structured data like lists or tables without requiring complex regular expression code. ... -
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SciMLBenchmarks.jl
Benchmarks for scientific machine learning (SciML) software
SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem. -
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Retrobios
Complete BIOS and firmware packs for RetroArch, Batocera, Recalbox
Retrobios is a low-level systems programming project focused on recreating or emulating BIOS-like functionality for legacy or experimental computing environments. It is designed to provide a minimal firmware layer that initializes hardware and prepares systems to boot, often used for educational purposes or retrocomputing experiments. The project likely explores how early computing systems managed hardware abstraction, memory initialization, and device communication before modern operating... -
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s-tui
Terminal-based CPU stress and monitoring utility
s-tui (Stress Terminal UI) is a terminal-based performance monitoring and stress-testing tool focused specifically on CPU behavior analysis in Linux and other UNIX-like systems. It provides real-time graphical visualization of CPU temperature, frequency, power consumption, and utilization directly within a text-based interface, eliminating the need for a graphical desktop environment. The utility is particularly useful for diagnosing thermal throttling, validating cooling solutions, and evaluating system stability under heavy load conditions. In addition to passive monitoring, s-tui can integrate with external stress tools to actively push the CPU to its limits while simultaneously displaying performance metrics. ... -
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jlpkg
A command line interface (CLI) for Pkg, Julia's package manager
A command line interface (CLI) to Pkg, Julia's package manager. -
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VoronoiFVM.jl
Solution of nonlinear multiphysics partial differential equations
Solver for coupled nonlinear partial differential equations (elliptic-parabolic conservation laws) based on the Voronoi finite volume method. It uses automatic differentiation via ForwardDiff.jl and DiffResults.jl to evaluate user functions along with their jacobians and calculate derivatives of solutions with respect to their parameters. -
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ReservoirComputing.jl
Reservoir computing utilities for scientific machine learning (SciML)
ReservoirComputing.jl provides an efficient, modular and easy-to-use implementation of Reservoir Computing models such as Echo State Networks (ESNs). For information on using this package please refer to the stable documentation. Use the in-development documentation to take a look at not-yet-released features. -
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XLSX.jl
Excel file reader and writer for the Julia language
XLSX.jl is a Julia package to read and write Excel spreadsheet files. Internally, an Excel XLSX file is just a Zip file with a set of XML files inside. The formats for these XML files are described in the Standard ECMA-376. This package follows the EMCA-376 to parse and generate XLSX files. -
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PaddleX
PaddlePaddle End-to-End Development Toolkit
...Therefore, we need to divide the above data. Using the paddlex command, the data set can be randomly divided into 70% training set, 20% validation set and 10% test set. If you use the PaddleX visualization client for model training, the data set division function is integrated in the client, and you do not need to use command division by yourself. -
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Zabbix plugin for Grafana
Zabbix plugin for Grafana dashboard
Grafana Zabbix is a plugin that integrates Zabbix monitoring with Grafana, enabling advanced visualization and analysis of Zabbix metrics using Grafana's powerful dashboard features. -
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Maid
Maid is a cross-platform Flutter app for interfacing with GGUF
Maid is a cross-platform Flutter app for interfacing with GGUF / llama.cpp models locally, and with Ollama and OpenAI models remotely. Maid is a cross-platform free and open source application for interfacing with llama.cpp models locally, and remotely with Ollama, Mistral, Google Gemini and OpenAI models remotely. Maid supports Sillytavern character cards to allow you to interact with all your favorite characters. Maid supports downloading a curated list of Models in-app directly from hugging face. -
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srsly
Modern high-performance serialization utilities for Python
This package bundles some of the best Python serialization libraries into one standalone package, with a high-level API that makes it easy to write code that's correct across platforms and Pythons. This allows us to provide all the serialization utilities we need in a single binary wheel. Currently supports JSON, JSONL, MessagePack, Pickle, and YAML. Serialization is hard, especially across Python versions and multiple platforms. -
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CatBoost
High-performance library for gradient boosting on decision trees
CatBoost is a fast, high-performance open source library for gradient boosting on decision trees. It is a machine learning method with plenty of applications, including ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. CatBoost offers superior performance over other GBDT libraries on many datasets, and has several superb features. It has best in class prediction speed, supports both numerical and categorical features, has a fast and scalable GPU version, and readily comes with visualization tools. CatBoost was developed by Yandex and is used in various areas including search, self-driving cars, personal assistance, weather prediction and more. -
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Mito
AI-powered Jupyter spreadsheet that converts workflows into Python
Mito is an open source set of Jupyter extensions designed to speed up Python workflows and data analysis. It combines a spreadsheet-style interface with AI-assisted coding, allowing users to explore, clean, and transform data without switching tools. Mito includes a context-aware AI assistant that helps generate code, debug errors, and guide workflows directly inside Jupyter. Its spreadsheet layer supports familiar functions such as filters, pivot tables, and formulas, while automatically converting every action into production-ready Python code. ... -
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ImageFiltering.jl
Julia implementations of multidimensional array convolution
Julia implementations of multidimensional array convolution and nonlinear stencil operations. ImageFiltering implements blurring, sharpening, gradient computation, and other linear filtering operations, as well nonlinear filters like min/max. -
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MarketData.jl
Time series market data
The MarketData package provides open-source financial data for research and testing. The data is from Quandl and is free end-of-day stock data. It is public domain without restrictions. The TimeSeries TimeArray data structure is used to store the data, but conversion to other data structures, including DataFrames and AxisArrays, is supported. -
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Latexify.jl
Convert julia objects to LaTeX equations, arrays or other environments
This is a package for generating LaTeX maths from Julia objects. This package utilizes Julia's homoiconicity to convert expressions to LaTeX-formatted strings. Latexify.jl supplies functionalities for converting a range of different Julia objects. -
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pandas
Fast, flexible and powerful Python data analysis toolkit
pandas is a Python data analysis library that provides high-performance, user friendly data structures and data analysis tools for the Python programming language. It enables you to carry out entire data analysis workflows in Python without having to switch to a more domain specific language. With pandas, performance, productivity and collaboration in doing data analysis in Python can significantly increase.
