Datapane is the world's most popular way to share data science insights from Python.
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Build beautiful reports from blocks of DataFrames, plots, and files without leaving Python. Publish to Datapane to share and embed them online.
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"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 dpdf = 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)
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"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."