Bokeh VS NumPy
Compare Bokeh VS NumPy and see what are their differences
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives.
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Bokeh
Plotly
D3.js
RAWGraphs
Highcharts
NVD3
Chart.js
CanvasJS
NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
BokehBased on our record, NumPy seems to be a lot more popular than Bokeh. While we know about 107 links to NumPy, we've tracked only 5 mentions of Bokeh. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Visualization: https://docs.bokeh.org/en/latest/. Source: almost 2 years ago
Now that we can get task timing information in a consistent manner, let’s do some plotting. For this, I’m going to use Bokeh which generates nice interactive plots. - Source: dev.to / about 2 years ago
Bokeh The Bokeh library is native to Python and is mainly used to create interactive, web-ready plots, which can be easily output as HTML documents, JSON objects, or interactive web applications. Like ggplot, its concepts are also based on the Grammar of Graphics. It has the added advantage of managing real-time data and streaming. This library can be used for creating common charts such as histograms, bar plots,... - Source: dev.to / over 2 years ago
It's not in the least bit "underrated" and it's documentation is extensive. Source: almost 3 years ago
Hi guys! I am currently working on a project to enrich my Master thesis with some interactive plots. I have been using the Bokeh library to make a standalone application, which I was then planning to deploy in Heroku. You can find the code in this repository. But I will also add it at the bottom of the post. Source: about 3 years ago
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / 2 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
Plotly - Low-Code Data Apps
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...
OpenCV - OpenCV is the world's biggest computer vision library