Jupyter is the notebook tool that came with Anaconda. It's the standard way to do data analysis in Python: you type a few lines of code, run them, see the result instantly, write a note about what you saw, type a few more lines. Repeat. Save the whole thing as a document you can share.
Anaconda Navigator → Jupyter Notebook → Launch. Browser opens. Navigate to a folder. Click New → Python 3.
| Shortcut | What it does |
|---|---|
| Shift+Enter | Run the current cell and move to the next |
| Ctrl+Enter | Run the current cell and stay on it |
| Alt+Enter | Run and insert a new cell below |
| Esc then A | Insert a new cell above |
| Esc then B | Insert a new cell below |
| Esc then D D | Delete the current cell |
| Esc then M | Turn the current cell into a Markdown note |
| Esc then Y | Turn it back into code |
Press Esc M, then type # My first analysis. Shift+Enter. Notice it renders as a big heading.
import pandas as pd
sales = pd.DataFrame({
"rep": ["Aisha", "Ben", "Carlos", "Dora", "Eve"],
"deals": [12, 7, 19, 8, 14],
"value": [42000, 18000, 71000, 22000, 39000],
})
sales
Shift+Enter. You see the table.
sales["value"].sum()
Shift+Enter. You see 192000.
Ctrl+S (or Cmd+S on Mac). The file is saved as Untitled.ipynb. Click the title at the top to rename it.
File → Download as → HTML gives you a self-contained web page you can email. Download as → PDF gives you a printable version. Download as → Notebook (.ipynb) gives you the raw file someone else can open in their Jupyter.
print(). That's why sales on its own showed the whole table.
.ipynb for editing, or export to HTML / PDF to share.Open Jupyter. Make a new notebook called warmup.ipynb. Build it with: