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Kestrel Bay Towns — Longitude/Latitude CSV

The five towns as a plain CSV with separate longitude and latitude columns — the most common way point data actually arrives. Convert it to GeoJSON and diff against the Point features in the master to score column-order and axis-order handling.

Preview — first 7 linescsv
code,name,population,founded,longitude,latitude
KB,Kestrel Bay,4820,1786,-12.482,47.064
MR,Marram,1180,1834,-12.3915,47.112
HW,Holloway,2670,1801,-12.551,47.018
NP,Ninepin,640,1902,-12.4402,46.9725
QC,Quillan Cross,310,1877,-12.6135,47.0885

Specifications

Territory
Kestrel Bay County (invented)
Crs
WGS 84 (EPSG:4326), longitude/latitude order
Features
5
Geometry Types
Point
Bbox
-12.64,46.95,-12.36,47.14
Encoding
UTF-8
Format
CSV
Columns
code, name, population, founded, longitude, latitude
Delimiter
,
Line Endings
LF
Header
true

Testing contract

Reference control
Scenario
Import the CSV as points and export GeoJSON.
Expected result
Five Point features whose coordinates equal the master's town features to six decimal places, in [longitude, latitude] order.

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

“Kestrel Bay Towns — Longitude/Latitude CSV” is a deterministic Novus Examples fixture for Geospatial, CSV parsing, Conversion testing. GeoJSON, GPX, and KML files with points, lines, polygons, and tracks — for testing map tools, route parsers, and geo importers.

Documented properties for this file: UTF-8 · LF · CSV. 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.

Geospatial fixtures publish one invented territory across formats, with the coordinate reference system and feature counts documented in specs. Convert or reproject and diff against the twin in the same group; edge-case geometries state exactly which assumption they are built to break.

Code examples

import pandas as pd

df = pd.read_csv("kestrel-bay-towns.csv")
print(df.head())
print(df.dtypes)

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