# Spending Categorizer
Paste a bank or credit-card CSV export to auto-categorize every transaction by merchant keywords and summarize spending by category. Runs in your browser.
## Run it
- **CLI:** `gizza tool spending-categorizer "Date,Description,Amount
2024-01-05,WALMART SUPERCENTER,-52.30
2024-01-06,STARBUCKS #1234,-4.50
2024-01-10,ACME PAYROLL,2000.00"`
- **Web:** https://gizza.ai/tools/spending-categorizer/
- **Agents:** machine-readable descriptor (parameters JSON Schema) at https://gizza.ai/tools/spending-categorizer/tool.json
## Inputs
- `data` — Bank / credit-card CSV (with a header row) _(field)_
- `description_column` — Description / merchant column (blank = auto-detect) _(field)_
- `amount_column` — Signed amount column (blank = auto-detect) _(field)_
- `debit_column` — Debit / money-out column (if split into two) _(field)_
- `credit_column` — Credit / money-in column (if split into two) _(field)_
- `date_column` — Date column (blank = auto-detect) _(field)_
- `rules` — Your rules (one 'keyword = Category' per line) _(field)_
- `output` — Output _(field)_
- `currency` — Currency ($ prefix or USD suffix; blank = none) _(field)_
- `delimiter` — CSV delimiter _(field)_
- `invert_amount` — Invert amounts (bank exports spending as positive) _(field)_
## Output
- Spending summary (text)
## Query parameters
Open the tool pre-filled and auto-run via URL:
- `data` — Bank / credit-card CSV (with a header row)
- `description_column` — Description / merchant column (blank = auto-detect)
- `amount_column` — Signed amount column (blank = auto-detect)
- `debit_column` — Debit / money-out column (if split into two)
- `credit_column` — Credit / money-in column (if split into two)
- `date_column` — Date column (blank = auto-detect)
- `rules` — Your rules (one 'keyword = Category' per line)
- `output` — Output
- `currency` — Currency ($ prefix or USD suffix; blank = none)
- `delimiter` — CSV delimiter
- `invert_amount` — Invert amounts (bank exports spending as positive)
Example: `https://gizza.ai/tools/spending-categorizer/?data=Date%2CDescription%2CAmount%0A2024-01-05%2CWALMART%20SUPERCENTER%2C-52.30%0A2024-01-06%2CSTARBUCKS%20%231234%2C-4.50%0A2024-01-10%2CACME%20PAYROLL%2C2000.00&description_column=Description&amount_column=Amount&debit_column=Debit&credit_column=Credit&date_column=Date&rules=starbucks%20%3D%20Coffee%0Agym%20%3D%20Health%20%26%20Fitness&output=both¤cy=%24&delimiter=auto&invert_amount=true`
---
## About this tool
Export your transactions from your bank or credit-card site as CSV, paste them above, and get
an instant picture of where the money went. Every row is matched against a built-in table of
merchant keywords — Groceries, Dining & Takeaway, Transport, Fuel, Shopping, Subscriptions &
Streaming, Utilities & Phone, Housing & Rent, Insurance, Health & Fitness, Entertainment,
Travel, Cash & ATM, Transfers, Fees & Interest — and money coming in is recognized as Income.
Anything unmatched lands in `Other`, and you can add your own `keyword = Category` rules
(checked before the built-ins) to route it wherever you want.
The summary shows each category's total, its share of overall spending, the transaction count
and a proportional bar, followed by total spending, income and net cash flow. Switch the output
to *Categorized CSV only* to download the original rows with a `Category` column appended —
ready for a spreadsheet or budgeting app. Everything runs locally in your browser; your
statement never leaves your machine.
### Worked example
Pasting this statement:
```
Date,Description,Amount
2024-01-05,WALMART SUPERCENTER,-52.30
2024-01-06,STARBUCKS #1234,-4.50
2024-01-07,SHELL GAS STATION,-48.90
2024-01-08,NETFLIX.COM,-15.99
2024-01-09,WALMART SUPERCENTER,-34.80
2024-01-10,ACME PAYROLL,2000.00
2024-01-11,CITY PARKING,-12.00
```
produces this summary (plus the categorized rows):
```
Spending by category
====================
Category Total Share Txns
--------------------------------------------------
Groceries $87.10 51.7% 2 ████████████████████
Fuel $48.90 29.0% 1 ███████████
Subscriptions & Streaming $15.99 9.5% 1 ████
Transport $12.00 7.1% 1 ███
Dining & Takeaway $4.50 2.7% 1 █
--------------------------------------------------
Total spending $168.49 100.0% 6
Income $2000.00 1
Net cash flow +$1831.51
```
### Formats and limits
- The first row must be the column headers. Description/merchant, amount and date columns are
auto-detected from common header names — including European ones like `Beschreibung`,
`Omschrijving`, `Libellé`, `Betrag`, `Bedrag`, `Montant`, `Datum` — and you can name them
explicitly when detection guesses wrong.
- Works with one signed amount column (money out negative) **or** separate debit/credit
columns. If your bank exports spending as positive numbers, tick *Invert amounts*.
- Amounts may use US (`1,234.56`) or European (`1.234,56`) separators, parentheses negatives
(`(42.00)`), or trailing `DR`/`CR` markers.
- Comma, semicolon, tab and pipe delimiters are supported (auto-sniffed by default).
- At most **10 000 rows** per run; larger files are rejected with a clear error.
- Categorization is deterministic keyword matching, not machine learning: single-word keywords
match whole words by prefix (so `rent` matches RENT and RENTAL but not PARENT), and rules
you write match anywhere in the description.
## FAQ
Which bank exports does this work with?
Any bank or card provider that exports CSV. The tool auto-detects the usual header names —
`Description`/`Payee`/`Details`/`Memo` for the merchant, `Amount` (or `Debit`/`Credit`) for
the money, `Date`/`Posted` for the date — so most exports work as-is. If your bank uses
unusual headers, type them into the column fields; if it uses semicolons (common in Europe),
the delimiter is sniffed automatically.
How do I fix a transaction that lands in the wrong category (or in Other)?
Add a rule line like `costco = Wholesale` or `my landlord llc = Housing & Rent` in the rules
box. Rules are case-insensitive substring matches, checked before the built-in keyword table,
so they always win. One rule per line; `#` starts a comment. The category name is free text —
you can invent your own categories.
Why are my expenses showing up as income?
The tool expects money out to be negative and money in positive, which is what most banks
export. Some card statements export spending as positive numbers instead — tick *Invert
amounts* and the signs are flipped before categorizing. Statements with separate debit and
credit columns are handled automatically (debits are money out).
Is my bank data uploaded anywhere?
No. The categorizer is WebAssembly running entirely in your browser — the CSV is parsed,
categorized and summarized locally, and nothing is sent to a server. You can disconnect from
the network after the page loads and it keeps working.
Can I get the result into Excel or Google Sheets?
Yes — set *Output* to *Categorized CSV only* and use the download link under the result. You
get your original rows with a `Category` column appended, quoted as standard CSV, which
imports cleanly into any spreadsheet or budgeting app. The date column is passed through
exactly as your bank wrote it.
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