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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Bokeh simplifies the creation of standard visualizations while also accommodating unique or specialized scenarios. It allows users to publish plots, dashboards, and applications seamlessly on web pages or within Jupyter notebooks. The Python ecosystem boasts a remarkable collection of robust analytical libraries such as NumPy, Scipy, Pandas, Dask, Scikit-Learn, and OpenCV. With its extensive selection of widgets, plotting tools, and user interface events that can initiate genuine Python callbacks, the Bokeh server serves as a vital link, enabling the integration of these libraries into dynamic, interactive visualizations accessible via the browser. Additionally, Microscopium, a project supported by researchers at Monash University, empowers scientists to uncover new functions of genes or drugs through the exploration of extensive image datasets facilitated by Bokeh’s interactive capabilities. Another useful tool, Panel, which is developed by Anaconda, enhances data presentation by leveraging the Bokeh server. It streamlines the creation of custom interactive web applications and dashboards by linking user-defined widgets to a variety of elements, including plots, images, tables, and textual information, thus broadening the scope of data interaction possibilities. This combination of tools fosters a rich environment for data analysis and visualization, making it easier for researchers and developers to share their insights.

Description

Fast and adaptable, the concepts of vectorization, indexing, and broadcasting in NumPy have become the benchmark for array computation in the present day. This powerful library provides an extensive array of mathematical functions, random number generators, linear algebra capabilities, Fourier transforms, and beyond. NumPy is compatible with a diverse array of hardware and computing environments, seamlessly integrating with distributed systems, GPU libraries, and sparse array frameworks. At its core, NumPy is built upon highly optimized C code, which allows users to experience the speed associated with compiled languages while enjoying the flexibility inherent to Python. The high-level syntax of NumPy makes it user-friendly and efficient for programmers across various backgrounds and skill levels. By combining the computational efficiency of languages like C and Fortran with the accessibility of Python, NumPy simplifies complex tasks, resulting in clear and elegant solutions. Ultimately, this library empowers users to tackle a wide range of numerical problems with confidence and ease.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

3LC No 
Coiled No 
Cython No 
Dash No 
Flower No 
Gensim No 
Google Maps Yes 
JavaScript Yes 
MPI for Python (mpi4py) No 
NVIDIA FLARE No 
PaizaCloud No 
PyCharm No 
Spyder No 
Train in Data No 
Unify AI No 
Visual Studio Code No 
Yamak.ai No 
Yandex Data Proc No 
h5py No 
imageio No 

Integrations

3LC Yes 
Coiled Yes 
Cython Yes 
Dash Yes 
Flower Yes 
Gensim Yes 
Google Maps No 
JavaScript No 
MPI for Python (mpi4py) Yes 
NVIDIA FLARE Yes 
PaizaCloud Yes 
PyCharm Yes 
Spyder Yes 
Train in Data Yes 
Unify AI Yes 
Visual Studio Code Yes 
Yamak.ai Yes 
Yandex Data Proc Yes 
h5py Yes 
imageio Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Bokeh

Website

bokeh.org

Vendor Details

Company Name

NumPy

Website

numpy.org

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Product Features

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