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datachart

Data visualization package, simple to use, highly customizable

More than twenty chart types, each a single function call on plain lists of dicts. Built on matplotlib, styled by one global theme. Combine several charts into one plot, or arrange them side by side in a grid.

Get started Browse the charts
pip install datachart
Line chart Line chart Bar chart Bar chart Scatter chart Scatter chart Sankey chart Sankey chart Heatmap Heatmap Bump chart Bump chart Violin plot Violin plot Treemap Treemap Gantt chart Gantt chart Contour chart Contour chart Pyramid chart Pyramid chart Ridgeline plot Ridgeline plot Network chart Network chart
Stacked area chart Stacked area chart Histogram Histogram Dumbbell chart Dumbbell chart Hexbin chart Hexbin chart Radial chart Radial chart Raincloud plot Raincloud plot Parallel coordinates Parallel coordinates Box plot Box plot Swarm plot Swarm plot Scatter matrix Scatter matrix Calendar heatmap Calendar heatmap Panel Panel Grid Grid Highlighting Highlighting Text annotations Text annotations

Every chart above has a how-to guide. Hover to pause, click to open. See all chart types

Documentation

Find your way around

Start with a guide, look things up in the reference, or point your AI assistant at the docs.

How-to guides

Every chart type, composition with Panel and Grid, styling, and the utilities, each a runnable notebook on real data.

Open the guides →

API reference

Signatures and attribute tables for the charts, utils, config, themes, constants, and typings modules.

Browse the reference →

Themes and styling

Seven predefined themes, the global config, colormaps, and emphasis for the series that matters.

See the theme gallery →

Composition

Overlay charts on one axes with Panel, or lay them out with Grid. Grids nest.

Compose figures →

AI assistants

llms.txt, per-page markdown, and MCP servers, so a coding assistant writes datachart code from the current docs.

Point your assistant here →

Source and changelog

Bug reports, feature requests, and pull requests are welcome on GitHub.

Go to the repository →

Install

Two commands, Python 3.10 or higher

Install from PyPI with pip or uv. Add the interactive extra for zoom, pan, and hover-to-inspect.

pip install -U datachart

uv add datachart

pip install -U "datachart[interactive]"

Every chart returns a plain matplotlib Figure, so anything matplotlib can do with it still works. See Saving Figures and Interactive Figures.

First chart

A line chart in one call

Every chart takes a list of series, each a list of dicts. Set a theme once and every chart follows it.

from datachart.charts import LineChart
from datachart.config import config
from datachart.constants import THEME

config.set_theme(THEME.INK)

months = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul"]
signups = [420, 465, 430, 510, 560, 545, 610]
churned = [380, 400, 440, 435, 480, 520, 550]

figure = LineChart(
    [
        [{"x": x, "y": y} for x, y in enumerate(signups)],
        [{"x": x, "y": y} for x, y in enumerate(churned)],
    ],
    title="Monthly signups vs. churn",
    subtitle=["Signups", "Churned"],
    xlabel="Month",
    ylabel="Users",
    xticks=list(range(len(months))),
    xticklabels=months,
    show_legend=True,
)

Two lines, signups and churned users, over seven months in the INK theme