plotnine vs Bokeh

Side-by-side — pricing, strengths, tradeoffs, and fit.

plotnine

A grammar of graphics for Python based on ggplot2.

Bokeh

Interactive Web Plotting for Python.

At a glance

Open SourceFree Tier
● Established·From $0
Open SourceFree Tier
● Established·From $0

Overview

One-liner

A grammar of graphics for Python based on ggplot2.

One-liner

Interactive Web Plotting for Python.

Maturity

Established

Maturity

Established

Open source

✓ Yes

Open source

✓ Yes

Pricing

Free tier

✓ Available

Open source — free to use

Free tier

✓ Available

Open source — free to use

Starts at

$0

Starts at

$0

Model

Flat rate

Model

Flat rate

Enterprise

✕ None

Enterprise

✕ None

Best for

✓ Best for

Developers familiar with R's ggplot2 who want to use similar functionality in Python
Projects requiring publication-quality graphics and complex plot customization

✓ Best for

Projects requiring high-performance interactivity over large datasets
Web applications that need to visualize streaming data
Developers who want to create interactive plots and charts for web apps without a backend service

Not ideal for

✕ Not for

Users looking for a web-based interface or service for data visualization
Teams that require real-time interactive visualizations without the need for code

✕ Not for

Teams needing real-time streaming (Bokeh is more suited for batch processing)
Projects with strict performance constraints where JavaScript libraries might be lighter-weight options

Strengths

↑ Strengths

Grammar of Graphics implementation in Python
High-level interface for creating complex plots
Inspired by R's ggplot2, making it familiar to users from both ecosystems

↑ Strengths

Interactive plots and charts for web applications
High-performance interactivity over large datasets
Supports streaming data visualization
Customizable visualizations with extensive styling options

Weaknesses

↓ Weaknesses

Steep learning curve for non-Python developers
Limited performance with large datasets
Smaller community compared to alternatives like Matplotlib or Seaborn

↓ Weaknesses

Limited third-party integration support
Performance issues with very large datasets
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