Build data science documents in Python
Stop copying plots into slide decks or rebuilding Python analyses in a BI tool. Start sharing beautiful interactive documents from Python in 3 lines of code.
Stop copying plots into slide decks or rebuilding Python analyses in a BI tool. Start sharing beautiful interactive documents from Python 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")
).upload(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.
"Datapane is a speedy way to generate complex visualizations, and share these with non-technical people. It’s a cool tool that plugs right into our ML stack."
