This guide walks you through the core Margin workflow: create a notebook, run code, and share your findings in a brief.
.ipynb fileYou'll see a fresh notebook with one empty code cell.
The Python kernel connects automatically when you open a notebook. Watch the toolbar—the status shows:
Type some Python in the first cell:
import pandas as pd
# Create sample data
data = {
'Month': ['Jan', 'Feb', 'Mar', 'Apr'],
'Revenue': [12000, 15000, 13500, 18000]
}
df = pd.DataFrame(data)
df
Run the cell with Shift + Enter (or click the play button). You'll see the DataFrame rendered below the cell.
Margin notebooks support Jupyter‑style shortcuts:
| Key | Action |
|---|---|
Shift+Enter | Run cell and advance |
Ctrl/Cmd+Enter | Run all cells |
B | Insert cell below |
A | Insert cell above |
DD | Delete cell |
M | Change to Markdown |
Y | Change to code |
J/K or arrows | Navigate cells |
Margin auto‑saves as you work. The status indicator in the navbar shows:
You can also press Ctrl/Cmd + S to save immediately.
Now let's share your findings:
You'll land in the brief editor—a rich text editor for writing your narrative.
If your brief is linked to a notebook, you can embed outputs directly:
/ and select "Artifact from Notebook")Ready to publish?
q1-revenue)Your brief is now live at marginfordata.com/@username/briefs/q1-revenue.
Viewers see your narrative and embedded outputs—but not your raw data or notebook code.