Domestically Significant Ports

So far, we've focused on globally significant ports — the major ones that handle huge volumes of vessels. These are clearly important: if any of them were disrupted, global trade could feel the impact.

But what about smaller ports — especially in smaller countries? Let’s consider this idea:

If a country has only a few ports — or even just one — it likely depends heavily on those ports for its imports.

This brings us to the next step: identifying domestically significant ports, i.e., ports that are vital within their own country.

Researchers behind the PortWatch dataset defined:

Domestically significant ports are ports that, together, handle more than 80% of a country’s total imports.

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🔧 Your tasks:

• Define a dummy variable where dummy = 1 if a port is domestically significant

• Calculate:

  • How many ports are domestically significant (dummy = 1)?

  • How many ports are not (dummy = 0)?

• 💬 Comment your code clearly so that someone else can easily follow your logic

• You can use numpy.where() or .loc[] to create a dummy variable based on a given condition.

• To count how many ports fall into each group (1 or 0), try using .value_counts() on your dummy column

📌 Tip: You may already have a column showing each port’s percent share of imports within its country — use this to calculate cumulative shares for each country.