Cellules, noyaux et ordre d’exécution

A Jupyter notebook is built from cells, small editable boxes you fill and run one at a time. This is what makes analysis feel interactive.

Type code in a cell, then press Shift+Enter to run it. The output appears right below, so you never lose sight of what happened.

Behind your notebook runs a kernel, a live Python process that executes each cell and remembers everything between them.

Because the kernel stays alive, a variable set in one cell is still there in the next. Run this, then use total later.

In a fresh cell you can reuse total without redefining it. The kernel kept it in memory for you, ready to build on.

Cells run in the order you press run, not top to bottom. That run order is the single biggest source of confusing notebook bugs.

The number in [ ] beside a cell shows when it last ran. Tracking that execution count tells you the true order things happened.

If you edit an early cell but skip rerunning it, later cells use stale values. Your run order no longer matches the code you see.

When state feels tangled, use Restart Kernel. It wipes all variables so you start from a blank, trustworthy slate.

After restarting, choose Run All to execute every cell top to bottom. This proves your notebook works as a clean, repeatable story.

Green means you are typing inside a cell; blue means you are commanding the notebook. Esc and Enter flip between the two.

Your notebook gives odd results and you suspect cells ran out of order.

You learned that cells run on a stateful kernel, that run order can fool you, and that Restart plus Run All keeps a notebook honest. 👍