Money Manager Analyzer · tools.crrm.dev

How it works

Upload an xlsx exported from the Money Manager app.
The analyzer aggregates income / expense and slices it by month, category, account, merchant, and a few special-case merchants (Shopee, Lazada, 711, etc.).
Nothing leaves your browser session — the file is parsed in memory and discarded.
The xlsx must follow the expected shape. Click Required xlsx shape above to see the column list.

Required xlsx shape

The analyzer expects an xlsx export from the Money Manager app with a header row on row 1 and these columns (exact names, any order):

Column	Type	Used for
`Period`	date	Month grouping & "first instance" timestamps
`Accounts`	text	Expense account breakdown
`Category`	text	Category pie + Food/Grocery/Transport rules
`Subcategory`	text	Coffee-shop detection (`Cafe Hopping`, `Grab`, `Foodpanda`)
`Amount`	number	Totals & all aggregations
`Income/Expense`	text	Must be `Exp.` or `Income`
`Note`	text	Merchant / source name (e.g. `Starbucks`, `GrabCar`, `711 SM`)
`Description`	text	Free text; `@Name` tags split shoulder costs

Conventions the analyzer relies on

Income/Expense must literally be Exp. or Income — other values are skipped.
Amount must be numeric (no currency symbol in the cell — the app exports a bare number).
Period must be a real date cell, not a string. If it's a string, the row is skipped.
Special-case merchants are detected by regex on Note:
- Shopee at end → Shopee order
- Lazada at end → Lazada order
- Amazon at end → Amazon order
- ^711 → 7-Eleven
- ^Grab (in Transportation) → GrabCar
Coffee-shop detection matches a fixed list (Starbucks, Dunkin, Pickup Coffee, …) against Note on rows whose Subcategory is Cafe Hopping, Grab, or Foodpanda.
Tagged expenses: every @Name token in Description (e.g. Lunch @Shane @Christian, Gift @Mom) is aggregated into the Tagged Expenses section. Each mention adds the full row amount; duplicates in the same row are deduped case-insensitively.

Exporting from the app

In Money Manager: Settings → Backup & Restore → Export to Excel (xlsx). Pick the date range you want analyzed, then upload the resulting file here. No category renaming or column reshuffling needed — leave it as the app exports.