Sharing Python analyses is painful. Datapane makes it easy: build rich reports in Python, publish them to the web, and share them with your community or team.
Build beautiful reports from blocks of DataFrames, plots, and files without leaving Python. Publish to Datapane to share and embed them online.
Write code and analyze data in your own editor or environment, whether its Jupyter, Colab, or Airflow.
Datapane's framework makes it easy to create rich reports from DataFrames, output files, and libraries like Altair and Plotly.
Export as standalone HTML files, or publish to Datapane.com for free, where your reports can be shared and embedded.
import pandas as pd import altair as alt import datapane as dp dataset = pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv') df = dataset.groupby(['continent', 'date'])['new_cases_smoothed_per_million'].mean().reset_index() plot = alt.Chart(df).mark_area(opacity=0.4, stroke='black').encode( x='date:T', y=alt.Y('new_cases_smoothed_per_million:Q', stack=None), color=alt.Color('continent:N', scale=alt.Scale(scheme='set1')), tooltip='continent:N' ).interactive().properties(width='container') dp.Report( dp.Plot(plot), dp.Table(df) ).publish(name='covid_report', open=True)
- import pandas as pd
- import altair as alt
- import datapane as dp
- dataset = pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv')
- df = dataset.groupby(['continent', 'date'])['new_cases_smoothed_per_million'].mean().reset_index()
- plot = alt.Chart(df).mark_area(opacity=0.4, stroke='black').encode(
- y=alt.Y('new_cases_smoothed_per_million:Q', stack=None),
- color=alt.Color('continent:N', scale=alt.Scale(scheme='set1')),
- ).publish(name='covid_report', open=True)
Get started with the open source library, and use Datapane.com as a free publishing platform for your reports, datasets, and visualizations.
Want to share plots, visualisations, and datasets from Python? Publish Datapane reports online for free, and share them with your community.
Publish reports created with Datapane library
Collaborate and share with Datapane community
Share interactive reports with your team or community
Embed into social platforms, like Reddit and Medium
The end-to-end platform for Python analytics and reporting. Securely share Python reports, and deploy scripts and notebooks as self-service reporting tools.
Build flexible self-service reporting tools in Python which run in the cloud and can be used by everyone in the organization.
Turn Python scripts into reporting tools. Include your own Python libraries, folders, models, and SQL, and connect your scripts to live data sources, such as APIs or databases.
Expose your scripts using web forms, with rich inputs such as dates, multi-select, and ranges, to allow self-service report generation.
Create realtime reports by scheduling your script to run automatically, or trigger report generation through the tools you already use, like Slack, Teams, and GitHub.
Control access to your reports with organizational sharing, or share reports with third-parties using signed tokens.
Share reports securely, with versioning and authentication, or share with clients using secure signed URLs.
Embed reports into your own product, or into knowledge platforms like Confluence, Salesforce, Teams, and Notion.
Use Datapane's Blob and Secret Variables APIs to manage, authenticate, and version your credentials, models, and datasets.
We have been been hard at work with users building features to make Datapane even better.
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