Real-estate Listings (CSV, 30 rows)
A property-listings dataset — 30 homes with address, type, price, beds/baths, size, year built, coordinates, and status. Synthetic data for testing listing importers, map plots, and price analytics.
listing_id,address,city,state,type,price,beds,baths,sqft,year_built,latitude,longitude,status
L0001,8769 Oak St,Denver,CO,apartment,1187000,3,3.0,1608,1987,39.75292,-105.05308,for_sale
L0002,3795 Pine St,Portland,OR,condo,1059000,1,1.5,2998,1978,45.51004,-122.61966,sold
L0003,9786 Ash St,Portland,OR,condo,262000,3,2.5,3520,1955,45.48338,-122.6642,for_sale
L0004,7319 Willow St,Austin,TX,apartment,1335000,5,3.0,2288,2023,30.26339,-97.80275,for_sale
L0005,2860 Alder St,Denver,CO,house,1211000,5,4.0,2024,1965,39.7854,-105.00409,sold
L0006,325 Elm St,Portland,OR,apartment,948000,2,1.0,3569,1971,45.57434,-122.66438,sold
L0007,7577 Cedar St,Portland,OR,condo,1075000,4,3.5,1649,2019,45.46223,-122.67469,for_sale
L0008,1645 Elm St,Portland,OR,condo,597000,3,1.5,3559,1984,45.48775,-122.70524,pending
L0009,8973 Elm St,Austin,TX,apartment,247000,3,3.5,3587,1970,30.33191,-97.6796,for_sale
L0010,4023 Chestnut St,Portland,OR,apartment,1197000,4,1.0,1770,1998,45.47766,-122.6559,for_sale
L0011,2670 Alder St,Austin,TX,townhouse,1058000,2,2.0,3326,1991,30.33115,-97.69485,pending
L0012,5727 Pine St,Denver,CO,condo,240000,4,3.0,2168,1963,39.76537,-104.9712,for_sale
L0013,9053 Birch St,Portland,OR,house,907000,3,2.0,2464,1960,45.49185,-122.72799,sold
L0014,7522 Oak St,Denver,CO,apartment,704000,2,2.5,2001,2022,39.70031,-105.00731,for_sale
L0015,2399 Alder St,Portland,OR,apartment,570000,2,2.5,1307,1958,45.44459,-122.64837,sold
L0016,7272 Pine St,Portland,OR,house,1392000,2,2.5,3724,1988,45.5287,-122.71237,for_sale
L0017,6981 Willow St,Austin,TX,house,676000,2,1.0,774,1950,30.23649,-97.67922,for_sale
L0018,7656 Pine St,Denver,CO,condo,251000,1,1.5,1008,1996,39.78366,-105.01223,for_sale
L0019,1085 Cedar St,Austin,TX,house,366000,3,1.5,3748,1968,30.3037,-97.70205,sold
L0020,1810 Alder St,Portland,OR,apartment,1280000,5,5.5,1746,1952,45.50902,-122.6601,sold
L0021,7329 Birch St,Austin,TX,apartment,1173000,5,1.5,1003,2020,30.33464,-97.73586,for_sale
L0022,3750 Ash St,Austin,TX,house,1267000,2,1.0,1909,2009,30.19924,-97.73751,for_sale
L0023,4740 Maple St,Austin,TX,house,303000,1,1.0,2957,1971,30.23105,-97.80837,for_sale
L0024,7022 Birch St,Austin,TX,townhouse,555000,1,1.0,2322,1971,30.28848,-97.71556,for_sale
L0025,9614 Elm St,Denver,CO,apartment,1173000,5,1.5,785,2014,39.66749,-105.05767,for_sale
L0026,7268 Chestnut St,Denver,CO,house,645000,5,4.5,661,1978,39.68402,-104.97226,pending
L0027,8977 Alder St,Denver,CO,condo,467000,3,3.5,728,1995,39.69428,-104.9854,pending
L0028,8702 Elm St,Portland,OR,condo,971000,3,3.0,2873,1959,45.44494,-122.69302,sold
L0029,4485 Cedar St,Portland,OR,apartment,732000,1,1.0,3004,2010,45.53092,-122.68283,pending
L0030,7863 Cedar St,Denver,CO,townhouse,1178000,4,1.5,860,1989,39.78708,-104.93532,pending
Specifications
- Rows
- 30
- Schema
- listing_id, address, city, state, type, price, beds, baths, sqft, year_built, latitude, longitude, status
- Domain
- real estate
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
“Real-estate Listings (CSV, 30 rows)” is a deterministic Novus Examples fixture for Data import, Geospatial, Conversion testing. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.
Documented properties for this file: 30 rows · schema: listing_id, address, city, state, type, price, beds, baths, sqft, year_built, latitude, longitude, status. 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("listings.csv")
print(df.head())
print(df.dtypes)Related files
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