Connect data science insights with end users
Turn a Python analysis into a self-service document or cloud app in 3 lines of code.
Turn a Python analysis into a self-service document or cloud app in 3 lines of code.
Datapane is the world's most popular way to share data science insights from Python.
Share and learn from reports built by Datapane's community of data storytellers.
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, where your reports can be shared and embedded.
"I like to do my analysis and visualization in Python, but I had no way to share results beyond screenshots. Datapane lets me create and share amazing interactive reports from Python in a few seconds."
import pandas as pd
import altair as altimport datapane as dp
df = pd.read_csv('https://covid.ourworldindata.org/data/vaccinations/vaccinations-by-manufacturer.csv', parse_dates=['date'])
df = df.groupby(['vaccine', 'date'])['total_vaccinations'].sum().tail(1000).reset_index()
plot = alt.Chart(df).mark_area(opacity=0.4, stroke='black').encode(
x='date:T', y=alt.Y('total_vaccinations:Q'),
color=alt.Color('vaccine:N', scale=alt.Scale(scheme='set1')),
).interactive().properties(width='container')
total_df = df[df["date"] == df["date"].max()].sort_values("total_vaccinations", ascending=False).reset_index(drop=True)
total_styled = total_df.style.bar(subset=["total_vaccinations"], color='#5fba7d', vmax=total_df["total_vaccinations"].sum())
dp.Report(
"## Vaccination Report",
dp.Plot(plot, caption="Vaccinations by manufacturer over time"),
dp.DataTable(df, caption="Initial Dataset")
).publish(name='Covid Vaccinations Demo', description="Covid Vaccinations report, using data from ourworldindata", open=True)
Deploy Jupyter Notebooks and Python scripts to Datapane Teams, where they can be run by your team or clients with parameters, scheduled to run automatically, and automate your other platforms with data science insights.
Everything you need to share data science insights
Datapane Teams provides a secure environment for sharing private reports and deploying and running data science apps.
Install Datapane securely in your own cloud or bare-metal environment, so your data never leaves your system
Deploy Jupyter Notebooks or Python scripts as accessible, automated internal tools
Allow stakeholders to provide custom parameters through rich web forms
Schedule app runs for dashboarding use-cases, or trigger through an API
Publish reports privately and securely share them with your team or external clients
Embed reports, datasets, and visualizations into your own app or platforms
Datapane Teams can be used for sharing data science with your clients or your team. Learn more about how teams use our APIs to deliver data science.
Generate beautiful data science reports for your clients. Share them securely using Datapane Teams or embed them into your own product.
Instantly turn results into reports for business units. Turn notebooks and scripts into serverless cloud apps to make data science insights self-service.