Sales Pivot Table

A company's sales arrive as (region, month, amount) rows, where month is a string 'YYYY-MM' and amount is a whole number of dollars (negative for a refund). Several rows can share the same region and month.

Write sales_pivot(rows) that returns a nested dictionary in which pivot[region][month] is the total of that region's sales in that month. Like a spreadsheet pivot table, every region gets an entry for every month that appears anywhere in rows, with 0 where the region sold nothing that month.

Order the keys: the regions in alphabetical order, and inside each region the months from earliest to latest.

Examples

rows = [
    ('North', '2026-02', 300),
    ('South', '2026-01', 120),
    ('North', '2026-01', 200),
    ('North', '2026-02', 50),
]
sales_pivot(rows)
# returns {'North': {'2026-01': 200, '2026-02': 350},
#          'South': {'2026-01': 120, '2026-02': 0}}

South sold nothing in February, but it still gets a '2026-02' entry of 0.

Constraints

• 0 <= len(rows) <= 100000
• Region names start with a capital letter followed by lower-case letters.
• -10000 <= amount <= 10000