Datasetpublic

pushthetempo/astana_traffic

Flowmatic Smart City Dataset Flowmatic smart-city dataset with hourly UTC CSV partitions. 3 hour file(s), 500 total row(s). Files live under data/hourly/ and are indexed in data/hourly/manifest.json. Pipeline run: cmpmwqy3j005joo3crz8pe451Updated: 2026-05-26T17:27:13.937ZPartition scheme: hourly-utcManifest: data/hourly/manifest.json Hourly CSV layout Rows are grouped by eventTime into one CSV per UTC hour: Directory: data/hourly/ File pattern: YYYY-MM-DDTHH.csv… See the full description on the dataset page: https://huggingface.co/datasets/pushthetempo/astana_traffic.

sourceHugging Facecc-by-4.0updated 4mo agoView on Hugging Face

0likes15downloads

Dataset Card

Flowmatic Smart City Dataset

Flowmatic smart-city dataset with hourly UTC CSV partitions. 3 hour file(s), 500 total row(s). Files live under data/hourly/ and are indexed in data/hourly/manifest.json.

Pipeline run: cmpmwqy3j005joo3crz8pe451 Updated: 2026-05-26T17:27:13.937Z Partition scheme: hourly-utc Manifest: data/hourly/manifest.json

Hourly CSV layout

Rows are grouped by eventTime into one CSV per UTC hour:

—Directory: data/hourly/
—File pattern: YYYY-MM-DDTHH.csv (example: data/hourly/2026-05-21T14.csv)
—Append exports merge only within the touched hour file(s), not the whole dataset.

Hour (UTC)	File	Rows	Updated
2026-05-26 15:00–15:59 UTC	`data/hourly/2026-05-26T15.csv`	424	2026-05-26T17:27:12.017Z
2026-05-26 16:00–16:59 UTC	`data/hourly/2026-05-26T16.csv`	25	2026-05-26T17:27:12.949Z
2026-05-26 17:00–17:59 UTC	`data/hourly/2026-05-26T17.csv`	51	2026-05-26T17:27:13.937Z

Preview (latest exported rows)

stage	eventId	eventTime	sourceId	sourceName	sourceType	sourceMode	sensorType	location	city	Latitude	Severity	latitude	severity	speedKmh	Longitude	Speed_kmh	eventType	longitude	speed_kmh	timestamp	transport	Event_Type	confidence	event_type	sensorKind	streamKind	derivedFrom	vehicleType	vehicle_type	trafficDensity	Traffic_Density	sourceTimestamp	traffic_density
"cleaned"	"76"	"2026-05-26T17:26:41.448Z"	"cmpmsl5eh0003qo3cjopanalb"	"astana traffic"	"WEBSOCKET"	"SIMULATED"	"traffic"	"Astana"	"Astana"	51.166809	"Low"	51.166809	"Low"	34	71.43913	34	"Normal"	71.43913	34	"2026-05-26T17:26:41.425Z"	"WEBSOCKET"	"Normal"	0.971	"Normal"	"traffic"	"astanasemisynthetic"	"astanasyntheticdata.csv"	"Bus"	"Bus"	69.2	69.2	"2024-06-23 00:07:22"	69.2
"cleaned"	"75"	"2026-05-26T17:26:40.424Z"	"cmpmsl5eh0003qo3cjopanalb"	"astana traffic"	"WEBSOCKET"	"SIMULATED"	"traffic"	"Astana"	"Astana"	51.14724	"Low"	51.14724	"Low"	115	71.376652	115	"Normal"	71.376652	115	"2026-05-26T17:26:40.424Z"	"WEBSOCKET"	"Normal"	0.963	"Normal"	"traffic"	"astanasemisynthetic"	"astanasyntheticdata.csv"	"Car"	"Car"	62.47	62.47	"2024-06-22 23:54:44"	62.47
"cleaned"	"74"	"2026-05-26T17:26:39.422Z"	"cmpmsl5eh0003qo3cjopanalb"	"astana traffic"	"WEBSOCKET"	"SIMULATED"	"traffic"	"Astana"	"Astana"	51.163067	"Low"	51.163067	"Low"	47	71.460097	47	"Normal"	71.460097	47	"2026-05-26T17:26:39.422Z"	"WEBSOCKET"	"Normal"	0.971	"Normal"	"traffic"	"astanasemisynthetic"	"astanasyntheticdata.csv"	"Bicycle"	"Bicycle"	66.64	66.64	"2024-06-22 23:46:30"	66.64
"cleaned"	"73"	"2026-05-26T17:26:38.420Z"	"cmpmsl5eh0003qo3cjopanalb"	"astana traffic"	"WEBSOCKET"	"SIMULATED"	"traffic"	"Astana"	"Astana"	51.183151	"Low"	51.183151	"Low"	69	71.373224	69	"Normal"	71.373224	69	"2026-05-26T17:26:38.420Z"	"WEBSOCKET"	"Normal"	0.934	"Normal"	"traffic"	"astanasemisynthetic"	"astanasyntheticdata.csv"	"Bus"	"Bus"	58.75	58.75	"2024-06-22 23:38:36"	58.75
"cleaned"	"72"	"2026-05-26T17:26:37.422Z"	"cmpmsl5eh0003qo3cjopanalb"	"astana traffic"	"WEBSOCKET"	"SIMULATED"	"traffic"	"Astana"	"Astana"	51.131677	"Low"	51.131677	"Low"	61	71.441112	61	"Normal"	71.441112	61	"2026-05-26T17:26:37.417Z"	"WEBSOCKET"	"Normal"	0.965	"Normal"	"traffic"	"astanasemisynthetic"	"astanasyntheticdata.csv"	"Bus"	"Bus"	57.98	57.98	"2024-06-22 23:19:37"	57.98

Usage

python

from datasets import load_dataset

# Loads all hourly CSV parts as one split
ds = load_dataset("pushthetempo/astana_traffic", data_files="data/hourly/*.csv", split="train")