datapane 0.10.1

Datapane client library and CLI tool

Datapane.com | Documentation | Twitter | Slack | Enterprise

Datapane is a Python library which makes it simple to build reports from the common objects in your data analysis, such as pandas DataFrames, plots from Python visualisation libraries, and Markdown.

Reports can be exported as standalone HTML documents, with rich components which allow data to be explored and visualisations to be used interactively.

For example, if you wanted to create a report with a table viewer and an interactive plot:

import pandas as pd
import altair as alt
import datapane as dp

df = pd.read_csv('https://query1.finance.yahoo.com/v7/finance/download/GOOG?period2=1585222905&interval=1mo&events=history')

chart = alt.Chart(df).encode(
    x='Date:T',
    y='Open'
).mark_line().interactive()

r = dp.Report(dp.DataTable(df), dp.Plot(chart))
r.save(path='report.html', open=True)

This would package a standalone HTML report such as the following, with a searchable DataTable and Plot component.

Getting Started

Install

• pip3 install datapane OR
• conda install -c conda-forge "datapane>=0.10.0"

Next Steps

• Read the documentation
• Browse samples and demos
• View featured reports

Datapane Public

In addition to saving reports locally, Datapane provides a free hosted platform at https://datapane.com where you to publish your reports online.

Published reports can be:

• shared publicly and become a part of our community,
• embedded within your blogs, CMSs, and elsewhere (see here),
• shared private reports you can share within a close-knit audience,
• include explorations and integrations, e.g. additional DataTable analysis features and GitHub action integration.

It's super simple, just login (see here) and call the publish function on your report,

r = dp.Report(dp.DataTable(df), dp.Plot(chart))
r.publish(name="2020 Stock Portfolio", open=True)

Enterprise

Datapane Enterprise provides automation and secure sharing of reports within in your organization.

• Private report sharing within your organization and within groups, including external clients
• Deploy Notebooks and scripts as automated, parameterised reports that can be run by your team interactively
• Schedule reports to be generated and shared
• Runs managed or on-prem
• and more

Joining the community

Looking to get answers to questions or engage with us and the wider community? Join our Slack and view our GitHub Discussions board.

Submit requests, issues, and bug reports on this GitHub repo.

We look forward to building an amazing open source community with you!