
Datapane is a Python framework for building beautiful data science documents for your company, clients, or community.
Datapane makes sharing Python analyses easy: build rich reports in Python, publish them to the web, and share them with your community, team, or clients.
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.
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(
- 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)
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