Software Alternatives & Reviews

Bokeh VS Matplotlib

Compare Bokeh VS Matplotlib and see what are their differences

Bokeh logo Bokeh

Bokeh visualization library, documentation site.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Bokeh Landing page
    Landing page //
    2022-11-01
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Bokeh

Categories
  • Charting Libraries
  • Data Visualization
  • Data Dashboard
  • Javascript UI Libraries
Website docs.bokeh.org
Details $-

Matplotlib

Categories
  • Data Visualization
  • Technical Computing
  • Javascript UI Libraries
  • Data Science And Machine Learning
Website matplotlib.org
Details $

Bokeh videos

"Bokeh" - Netflix Film Review

More videos:

Matplotlib videos

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Bokeh and Matplotlib)
Charting Libraries
100 100%
0% 0
Technical Computing
0 0%
100% 100
Data Visualization
34 34%
66% 66
Data Science And Machine Learning

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Bokeh and Matplotlib

Bokeh Reviews

Top 8 Python Libraries for Data Visualization
Pygal is a Python data visualization library that is made for creating sexy charts! (According to their website!) While Pygal is similar to Plotly or Bokeh in that it creates data visualization charts that can be embedded into web pages and accessed using a web browser, a primary difference is that it can output charts in the form of SVG’s or Scalable Vector Graphics. These...

Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesn’t support all file formats.
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...

Social recommendations and mentions

Based on our record, Matplotlib seems to be a lot more popular than Bokeh. While we know about 97 links to Matplotlib, 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.

Bokeh mentions (5)

  • [OC] Chemical Diversity of The GlobalChem Common Chemical Universe
    Visualization: https://docs.bokeh.org/en/latest/. Source: almost 2 years ago
  • Profiling workflows with the Amazon Genomics CLI
    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 / almost 2 years ago
  • 10 Python Libraries For Data Visualization
    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 / about 2 years ago
  • Graphic library Bokeh is underrated and underdocumented
    It's not in the least bit "underrated" and it's documentation is extensive. Source: almost 3 years ago
  • Help with Bokeh Interactive Plot
    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: almost 3 years ago

Matplotlib mentions (97)

  • Releasing The Force Of Machine Learning: A Novice’s Guide 😃
    Matplotlib: Acomprehensive library for creating static, animated, and interactive visualizations in Python. - Source: dev.to / about 1 month ago
  • How to retrieve and analyze crypto order book data using Python and a cryptocurrency API
    Data visualization: utilizing Python's Matplotlib for visualizing order book information. - Source: dev.to / 4 months ago
  • Ask HN: What plotting tools should I invest in learning?
    For random, quick and dirty, ad-hoc plotting tasks my default is GNUPlot[1]. Otherwise I tend to use either Python with matplotlib, or R with ggplot2. I keep saying I'm going to invest the time to properly learn D3[4] or something similar for doing web-based plotting, but somehow never quite seem to find time to do it. sigh [1]: http://www.gnuplot.info/ [2]: https://matplotlib.org/ [3]:... - Source: Hacker News / 8 months ago
  • PSA: You don't need fancy stuff to do good work.
    Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: 11 months ago
  • What else should I complete before applying for a data analyst role?
    Programming language: basic python, pandas, matplotlib -- you'll probably do these in school, but if not Https://cs50.harvard.edu/python/2022/ Https://matplotlib.org/. Source: 11 months ago
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What are some alternatives?

When comparing Bokeh and Matplotlib, you can also consider the following products

Plotly - Low-Code Data Apps

GnuPlot - Gnuplot is a portable command-line driven interactive data and function plotting utility.

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.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...

Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application