csv747 B

Tern Client Services: Expense claim whose mileage was paid at a superseded rate

Expense claim whose mileage was paid at a superseded rate for Tern Client Services. The same 6 lines as expense-claim.csv, but the three mileage amounts were computed at the superseded 0.58 per kilometre while the rate column still reads 0.62. The mileage subtotal is 136.88 where 236 km at the stated rate is 146.32, so the claim is 9.44 light and totals 212.13 instead of 221.57.

Data import Error handling

Preview, first 8 linescsv

line_id,expense_date,project_id,category,description,quantity,unit,rate,amount,receipt_reference
EXPL-001,2026-08-05,PROJECT-1,Mileage,Site visit and content audit,48,km,0.62,27.84,mileage-log.csv MIL-001
EXPL-002,2026-08-12,PROJECT-2,Mileage,Handbook workshop with the client team,112,km,0.62,64.96,mileage-log.csv MIL-002
EXPL-003,2026-08-19,PROJECT-3,Mileage,Booking system handover session,76,km,0.62,44.08,mileage-log.csv MIL-003
EXPL-004,2026-08-05,PROJECT-1,Parking,All-day parking at the client site,1,each,14.00,14.00,RCPT-2026-0004
EXPL-005,2026-08-12,PROJECT-2,Materials,Printed workshop handouts,1,each,38.50,38.50,RCPT-2026-0005
EXPL-006,2026-08-19,PROJECT-3,Subsistence,Meal during the handover day,1,each,22.75,22.75,RCPT-2026-0006

Specifications

Document Set: professional-services
Industry: professional-services
Source Kit: crm-services
Synthetic: true
As Of: 2026-09-08
Rows: 6
Stated Rate Per Km: 0.62
Rate Actually Applied: 0.58
Stated Total Usd: 212.13
Correct Total Usd: 221.57
Difference Usd: 9.44
Intentionally Invalid: true

Testing contract

Expected to fail

Scenario: Recompute every claim line from its own quantity and rate columns.
Expected result: The 3 receipted lines recompute. All 3 mileage lines fail: 48 km at 0.62 is 29.76 but the file states 27.84. The shortfall is 9.44, which is 236 km times the 0.04 difference between the two rates.

What is a .csv file?

CSV (Comma-Separated Values) is a plain-text tabular format where rows are lines and fields are separated by commas, with quoting rules for values that contain delimiters, quotes, or newlines. It has no formal type system and depends on encoding and dialect conventions. It is the most portable format for tabular data exchange.

How to use this file

Use an example CSV to test parsers against quoting and embedded-delimiter edge cases, header handling, encoding detection, and import pipelines into databases or spreadsheets.

How to use this file for testing

“Tern Client Services: Expense claim whose mileage was paid at a superseded rate” is a deterministic Testaroo fixture for Data import, Error handling. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.

Documented properties for this file: 6 rows. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.

Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such, expect parsers to fail loudly rather than silently accept them.

Data fixtures document their exact quirks (delimiters, encodings, null handling, schema, and row counts) in the spec table. Point your parser or importer at the file and assert it handles the documented edge cases; clean and deliberately-messy siblings make before/after diffs straightforward.

Code examples

import pandas as pd

df = pd.read_csv("expense-claim-mileage-rate-drift.csv")
print(df.head())
print(df.dtypes)

Generated by generation/industry_documents.py. Free for any use, no attribution required, license.