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wtf is chartify?

spotify/chartify — explained in plain English

Analysis updated 2026-05-18

3,632PythonAudience · dataComplexity · 2/5Setup · easy

TL;DR

Chartify is Spotify's Python charting library that uses one consistent data format and good default styles to make building charts faster.

Mindmap

mindmap
  root((chartify))
    What it does
      Python charting library
      Consistent data format
      Smart default styles
      Built on Bokeh
    Tech stack
      Python
      Bokeh
    Use cases
      Quick data charts
      Report visuals
      PNG export
      Custom Bokeh tweaks
    Audience
      Data scientists
      Analysts

Code map

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Why would anyone build with this?

REASON 1

Build a chart quickly from tidy data without reformatting it for each plot type.

REASON 2

Get a good-looking chart out of the box using Chartify's default styles.

REASON 3

Fall back to the underlying Bokeh API when you need finer control than Chartify offers.

REASON 4

Export a chart as a PNG image for reports or presentations.

What's in the stack?

PythonBokeh

How it stacks up

spotify/chartifypallets/quartdataherald/dataherald
Stars3,6323,6323,633
LanguagePythonPythonPython
Setup difficultyeasyeasymoderate
Complexity2/52/54/5
Audiencedatadeveloperpm founder

Figures from each repo's GitHub metadata at analysis time.

How do you spin it up?

Difficulty · easy Time to first run · 5min

PNG export requires an additional Chrome and chromedriver setup step.

No license terms are stated in the README.

Wtf does this do

Chartify is a Python library created by Spotify to make building charts and graphs easier for people who work with data. The goal is to reduce the time spent wrestling with data formatting before you can get a chart to appear. Most charting tools require data to be shaped in specific ways for each chart type, but Chartify uses a consistent format across all of its plot types, so you learn the pattern once and apply it everywhere. The library comes with sensible default styles, meaning you can get a good-looking chart quickly without spending time adjusting colors, fonts, or layout. The API is designed to be straightforward to learn, and there is a tutorial notebook that walks through the core concepts step by step. Under the hood, Chartify is built on top of Bokeh, which is a separate charting library for Python. This matters because it means if you ever need to do something Chartify does not directly support, you can drop down to the underlying Bokeh tools without switching libraries entirely. Installation is done through pip, the standard Python package manager. Exporting charts as PNG image files requires an additional optional setup step involving Google Chrome. The library supports Python 3.9, 3.10, and 3.11. Documentation, a tutorial, and example notebooks are all available online.

Yoink these prompts

Prompt 1
Show me how to create a bar chart from a pandas DataFrame using Chartify.
Prompt 2
Walk me through the Chartify tutorial notebook's core concepts for a beginner.
Prompt 3
How do I export a Chartify chart as a PNG image, including the chromedriver setup?
Prompt 4
When would I drop down to Bokeh directly instead of using Chartify's API?

Frequently asked questions

wtf is chartify?

Chartify is Spotify's Python charting library that uses one consistent data format and good default styles to make building charts faster.

What language is chartify written in?

Mainly Python. The stack also includes Python, Bokeh.

What license does chartify use?

No license terms are stated in the README.

How hard is chartify to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is chartify for?

Mainly data.

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