Search Results for "google-visualization-python" - Page 4
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Showing 3551 open source projects for "google-visualization-python"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Karpor
World's most promising Kubernetes Visualization Tool
Karpor is Intelligence for Kubernetes. It brings advanced Search, Insight and AI to Kubernetes. It is essentially a Kubernetes Visualization Tool. With Karpor, you can gain crucial visibility into your Kubernetes clusters across any clouds. -
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PlotJuggler
The Time Series Visualization Tool that you deserve
Fast, intuitive, and extensible time series visualization tool. Its Drag & Drop interface is designed to maximize both simplicity and speed. PlotJuggler is perfect for visualizing logs, offline and real-time data, and it can be used in multiple fields. PlotJuggler can be connected to an external application using any inter-process communication and display data in real time. Thanks to its plugin-based architecture, it is easy to add new data sources and functionalities. -
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Gnuplot.jl
Julia interface to gnuplot
Gnuplot.jl is a simple package able to send both data and commands from Julia to an underlying gnuplot process. Its main purpose it to provide a fast and powerful data visualization framework, using an extremely concise Julia syntax. It also has automatic display of plots in Jupyter, Juno and VS Code. -
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DataEase
Data visualization analysis tool
An open source data visualization analysis tool available to everyone. DataEase is an open-source data visualization analysis tool that helps users quickly analyze data and gain insight into business trends, so as to achieve business improvement and optimization. DataEase supports rich data source connections, can quickly create charts by dragging and dropping, and can easily share with others. -
Paessler: Easy to Use With Enterprise Power. Free TrialYou shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
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Term.jl
Julia library for stylized terminal output
Julia library for stylized terminal output. -
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Matplot++
Matplot++: A C++ Graphics Library for Data Visualization
Data visualization can help programmers and scientists identify trends in their data and efficiently communicate these results with their peers. Modern C++ is being used for a variety of scientific applications, and this environment can benefit considerably from graphics libraries that attend the typical design goals toward scientific data visualization. -
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HypothesisTests.jl
Hypothesis tests for Julia
HypothesisTests.jl is a Julia package that implements a wide range of hypothesis tests. -
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Superset
Apache Superset is a data visualization and data exploration platform
...Superset is lightweight and highly scalable, leveraging the power of your existing data infrastructure without requiring yet another ingestion layer. Superset ships with a wide array of beautiful visualizations. Our visualization plug-in architecture makes it easy to build custom visualizations that drop directly into Superset. -
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SumOfSquares.jl
Sum of Squares Programming for Julia
SumOfSquares.jl is a JuMP extension that, when used in conjunction with MultivariatePolynomial and PolyJuMP, implements a sum of squares reformulation for polynomial optimization. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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F2
An elegant, interactive and flexible charting library for mobile
F2 is an out-of-the-box visualization engine focused on the mobile terminal, oriented to conventional statistical charts, perfectly supporting the H5 environment and compatible with multiple environments (Node, applet), complete graphics grammar theory, to meet your various visualization needs , professional mobile design guidelines to bring you the best mobile graphics experience. -
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Briefer
Dashboards and notebooks in a single place
Briefer is an open-source collaborative data platform that brings notebooks, dashboards, and interactive data apps into a unified workspace that combines the flexibility of code with the simplicity of visual exploration. It’s designed so technical users can write Markdown, SQL, and Python side by side for data analysis, visualization, and reporting, while non-technical viewers can interact with results through inputs, dropdowns, and date pickers without writing any code. Users work in a Notion-style interface where they can build, organize, and share pages that contain executable code blocks, charts, text explanations, and interactive elements within the same document, enabling rich data storytelling and reproducible analytics. ... -
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AMDGPU.jl
AMD GPU (ROCm) programming in Julia
AMD GPU (ROCm) programming in Julia. -
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ggstatsplot
Enhancing {ggplot2} plots with statistical analysis
{ggstatsplot} is an extension of {ggplot2} package for creating graphics with details from statistical tests included in the information-rich plots themselves. In a typical exploratory data analysis workflow, data visualization and statistical modeling are two different phases: visualization informs modeling, and modeling in its turn can suggest a different visualization method, and so on and so forth. Bayesian hypothesis-testing. The central idea of {ggstatsplot} is simple: combine these two phases into one in the form of graphics with statistical details, which makes data exploration simpler and faster. ... -
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libCEED
CEED Library: Code for Efficient Extensible Discretizations
libCEED provides fast algebra for element-based discretizations, designed for performance portability, run-time flexibility, and clean embedding in higher-level libraries and applications. It offers a C99 interface as well as bindings for Fortran, Python, Julia, and Rust. While our focus is on high-order finite elements, the approach is mostly algebraic and thus applicable to other discretizations in factored form, as explained in the user manual and API implementation portion of the documentation. One of the challenges with high-order methods is that a global sparse matrix is no longer a good representation of a high-order linear operator, both with respect to the FLOPs needed for its evaluation, as well as the memory transfer needed for a matvec. ... -
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Sweetviz
Visualize and compare datasets, target values and associations
Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Output is a fully self-contained HTML application. The system is built around quickly visualizing target values and comparing datasets. Its goal is to help quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. -
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Ferrite.jl
Finite element toolbox for Julia
A simple finite element toolbox written in Julia. -
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Space Radar Electron
Disk And Memory Space Visualization App built with Electron & d3.js
Space Radar Electron is an application that offers an interactive and comprehensive visualization of disk space and memory usage of your computer. Built with Electron & d3.js, it currently offers visualizations in the form of Sunburst, Treemap and Flamegraph charts. As it scans the contents of your disk, it produces a preview visualization so you can already see what's been scanned. It allows for drilldown of directories, breadcrumbs and navigation. -
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PlutoUI.jl
A tiny package to make html"input" a bit more Julian
A tiny package to make HTML "input" a bit more Julian. Use it with the @bind macro in Pluto. -
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OnlineStats.jl
Single-pass algorithms for statistics
OnlineStats does statistics and data visualization for big/streaming data via online algorithms. High-performance single-pass algorithms for statistics and data viz. Updated one observation at a time. Algorithms use O(1) memory. Algorithms use O(1) memory. -
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G2
Interactive data-driven visualization grammar for statistical charts
G2 is a highly interactive data-driven visualization grammar for statistical charts. with a high level of usability and scalability. It provides a set of grammar, and takes users beyond a limited set of charts to an almost unlimited world of graphical forms. With G2, you can describe the visual appearance and interactive behavior of visualization just by one statement, and generate web-based views using Canvas or SVG. -
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Polynomials.jl
Polynomial manipulations in Julia
Basic arithmetic, integration, differentiation, evaluation, root finding, and fitting for univariate polynomials in Julia. -
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TaylorIntegration.jl
ODE integration using Taylor's method, and more, in Julia
ODE integration using Taylor's method in Julia. -
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JDF.jl
Julia DataFrames serialization format
...JDF.jl is a pure-Julia solution and there are a lot of ways to do nifty things like compression and encapsulating the underlying struture of the arrays that's hard to do in R and Python. E.g. Python's numpy arrays are C objects, but all the vector types used in JDF are Julia data types. -
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CImGui
Julia wrapper for cimgui
This package provides a Julia language wrapper for cimgui: a thin c-api wrapper programmatically generated for the excellent C++ immediate mode gui Dear ImGui. Dear ImGui is mainly for creating content creation tools and visualization / debug tools. You could browse Gallery to get an idea of its use cases. -
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Scanopy
Clean network diagrams, One-time setup, zero upkeep
...Developers can compose custom pipelines that chain together transforms, filters, and exporters, enabling automation of tedious data preparation steps and accelerating insights with minimal code. The system places a premium on extensibility, allowing contributors to add new extractors or analysis modules tailored to specific industries or datasets. Its visualization tools help users explore captured information interactively, revealing patterns or anomalies that might otherwise require significant manual effort.
