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From Jupyter to shareable data app in 10 seconds? Yep.

Datapane is a python framework that makes it super easy to build, host, and share interactive data apps straight from your Jupyter notebook.

What makes Datapane special?

Static generation: Sharing an app shouldn't require deploying an app. Render a standalone HTML bundle which you can share or host on the web.
API-first and programmatic: Programmatically generate apps from inside of Spark, Airflow, or Jupyter. Schedule updates to build real-time dashboards.
Dynamic front-end components: Say goodbye to writing HTML. Build apps from a set of interactive components, like DataTables, tabs, and selects.

Getting Started

Want a head start? Check out our Datapane in 3 minutes video:

Datapane.in.3.minutes.mp4

Installing Datapane

The best way to install Datapane is through pip or conda.

pip

$ pip3 install -U datapane

conda

$ conda install -c conda-forge "datapane>=0.15.4"

Datapane also works well in hosted Jupyter environments such as Colab or Binder, where you can install as follows:

!pip3 install --quiet datapane

Creating apps

📊 Include plots and data

Create an app from pandas DataFrames, plots from your favorite libraries, and text.

import altair as alt
from vega_datasets import data
import datapane as dp

df = data.iris()
fig = (
    alt.Chart(df)
    .mark_point()
    .encode(
      x="petalLength:Q",
      y="petalWidth:Q",
      color="species:N"
    )
)
app = dp.App(
    dp.Plot(fig),
    dp.DataTable(df)
)
app.save(path="my_app.html")

🎛 Layout using interactive blocks

Add dropdowns, selects, grid, pages, and 10+ other blocks to enhance your apps.

...

dp.App(
    dp.Formula("x^2 + y^2 = z^2"),
    dp.Group(
        dp.BigNumber(
            heading="Number of percentage points",
            value="84%",
            change="2%",
            is_upward_change=True
        ),
        dp.BigNumber(
            heading="Simple Statistic", value=100
        ), columns=2
    ),
    dp.Select(
        dp.Plot(fig, label="Chart"),
        dp.DataTable(df, label="Data")
    ),
).save(path="layout_example.html")

Get involved

Discord

Our Discord community is for people who believe that insights, visualizations, and apps are better created with Python instead of drag-and-drop tools. Get help from the team, share what you're building, and get to know others in the space!

💬 Join our discord server

Feedback

Leave us some feedback, ask questions and request features.

📮 Give feedback

Hosting Apps

In addition to saving apps locally or hosting them yourself, you can host and share your apps using Datapane Cloud.

To get your API key, create a free account.

Next, in your Python notebook or script, change the save function to upload:

dp.App(
 ...
#).save(path="hello_world.html")
).upload(name="Hello world")

Demos and Examples

Here a few samples of the top apps created by the Datapane community.

Coindesk analysis by Greg Allan
COVID-19 Trends by Quarter by Keith Johnson
Ecommerce Report by Leo Anthias
Example Academic Paper by Kalvyn Roux
Exploration of Restaurants in Kyoto by Ryan Hildebrandt

Next Steps

Analytics

By default, the Datapane Python library collects error reports and usage telemetry. This is used by us to help make the product better and to fix bugs. If you would like to disable this, simply create a file called no_analytics in your datapane config directory, e.g.

Linux

$ mkdir -p ~/.config/datapane && touch ~/.config/datapane/no_analytics

macOS

$ mkdir -p ~/Library/Application\ Data/datapane && touch ~/Library/Application\ Data/no_analytics

Windows (PowerShell)

PS> mkdir ~/AppData/Roaming/datapane -ea 0
PS> ni ~/AppData/Roaming/datapane/no_analytics -ea 0

You may need to try ~/AppData/Local instead of ~/AppData/Roaming on certain Windows configurations depending on the type of your user-account.

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