Star Schema — Sales Fact Table (CSV, 300 rows)
The sales fact table at the centre of a star schema — 300 sale lines with foreign keys to the date, product, and customer dimensions plus quantity and amount measures. A fixture for testing joins, star-schema imports, and BI tools.
sale_id,date_key,product_key,customer_key,quantity,amount
1,20260124,12,20,2,247.48
2,20260119,1,3,3,531.93
3,20260121,20,8,5,960.7
4,20260117,2,15,2,297.06
5,20260119,10,15,4,1422.84
6,20260120,16,38,5,611.65
7,20260102,20,19,1,192.14
8,20260112,18,37,5,1734.75
9,20260119,9,27,2,138.52
10,20260122,13,27,5,356.35
11,20260124,2,27,3,445.59
12,20260105,17,30,1,363.83
13,20260110,18,5,2,693.9
14,20260127,8,7,2,325.78
15,20260128,14,38,1,155.22
16,20260117,11,32,2,415.3
17,20260112,8,27,2,325.78
18,20260109,5,32,2,216.3
19,20260106,7,31,5,462.9
20,20260109,6,2,5,560.15
21,20260102,1,30,5,886.55
22,20260128,1,13,4,709.24
23,20260124,16,26,3,366.99
24,20260111,6,9,2,224.06
25,20260115,9,36,5,346.3
26,20260110,5,40,3,324.45
27,20260104,6,39,1,112.03
28,20260126,5,5,3,324.45
29,20260130,9,12,2,138.52
30,20260115,10,30,5,1778.55
31,20260122,19,1,5,1128.35
32,20260127,2,39,1,148.53
33,20260105,13,7,4,285.08
34,20260103,15,20,2,168.32
35,20260102,11,34,4,830.6
36,20260104,18,25,4,1387.8
37,20260121,8,9,2,325.78
38,20260126,4,25,5,694.25
39,20260122,19,34,3,677.01
40,20260126,17,2,2,727.66
41,20260111,7,27,3,277.74
42,20260111,7,35,1,92.58
43,20260112,16,21,4,489.32
44,20260106,9,29,1,69.26
45,20260116,5,9,5,540.75
46,20260107,17,37,4,1455.32
47,20260125,4,27,1,138.85
48,20260110,11,24,5,1038.25
49,20260118,1,10,2,354.62Specifications
- Rows
- 300
- Grain
- one row per sale line
- Foreign Keys
- date_key, product_key, customer_key
- Role
- fact
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.
Code examples
import pandas as pd
df = pd.read_csv("fact_sales.csv")
print(df.head())
print(df.dtypes)Related files
- csvE-commerce Customers (CSV, 500 rows)A realistic e-commerce customer directory (500 rows) — part of a relational dataset (products, customers, orders) with CSV, JSON, SQL, and Parquet twins for testing joins, imports, and conversion.
- csvE-commerce Orders (CSV, 2000 rows)A realistic e-commerce order lines (customer_id → customers, product_id → products) (2000 rows) — part of a relational dataset (products, customers, orders) with CSV, JSON, SQL, and Parquet twins for testing joins, imports, and conversion.
- csvE-commerce Products (CSV, 200 rows)A realistic e-commerce product catalogue (200 rows) — part of a relational dataset (products, customers, orders) with CSV, JSON, SQL, and Parquet twins for testing joins, imports, and conversion.
- avroAvro — Row Binary + SchemaThe same records as Apache Avro — a compact row-based binary format that embeds its own schema, widely used in Kafka pipelines. For testing Avro decoders and schema evolution.
- csvBank Transactions (CSV, 60 rows)A bank-transaction statement — 60 debits and credits across three accounts (masked numbers) with running balances, categories, and merchants. Synthetic data for testing statement parsers, categorisation, and reconciliation.
- jsonBank Transactions (JSON, 60 records)The bank transactions as a JSON array — the format twin of the CSV, for import and reconciliation testing.
Generated by generation/data_edgecases.py. Free for any use, no attribution required — license.