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Tern Client Services: Statement of work deliverables

Statement of work deliverables for Tern Client Services. 9 deliverables across the three statements of work, each with a due date, an allocation, the not-to-exceed value of its own statement of work and a single testable acceptance criterion. Grouped by sow_id the allocations sum to exactly 2000.00, 3000.00 and 4000.00, matching the sow_not_to_exceed_usd column on every row of the group. Two rows are marked accepted on 2026-08-24 and carry an accepted_date; the other seven have an empty accepted_date.

csv

text/csv

1.6 KB
Document Set
contracts
Industry
professional-services
Source Kit
crm-services
Entity
Tern Client Services
Synthetic
true
As Of
2026-09-08

Binary csv: no in-browser preview. Download it above to open in a compatible application.

Specifications

Document Set
contracts
Industry
professional-services
Source Kit
crm-services
Entity
Tern Client Services
Synthetic
true
As Of
2026-09-08
Rows
9
Statements Of Work
3
Accepted
2
Empty Accepted Dates
7
Delimiter
comma
Encoding
UTF-8

Testing contract

Expected to pass
Scenario
Group by sow_id, sum allocation_usd and compare each group total with the sow_not_to_exceed_usd value carried on its rows.
Expected result
All three groups balance exactly: 400.00 plus 900.00 plus 700.00 is 2000.00, 600.00 plus 1500.00 plus 900.00 is 3000.00, and 800.00 plus 2200.00 plus 1000.00 is 4000.00.

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: Statement of work deliverables” is a deterministic Novus Examples fixture for Data import, CSV parsing. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.

Documented properties for this file: 9 rows · UTF-8. 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("sow-deliverables.csv")
print(df.head())
print(df.dtypes)

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