Seattle Safety Data

Seattle Fire Department 911 dispatches.

Note

Microsoft provides Azure Open Datasets on an “as is” basis. Microsoft makes no warranties, express or implied, guarantees or conditions with respect to your use of the datasets. To the extent permitted under your local law, Microsoft disclaims all liability for any damages or losses, including direct, consequential, special, indirect, incidental or punitive, resulting from your use of the datasets.

This dataset is provided under the original terms that Microsoft received source data. The dataset may include data sourced from Microsoft.

Volume and retention

This dataset is stored in Parquet format. It's updated daily, and contains about 800,000 rows (20 MB) in 2019.

This dataset contains historical records accumulated from 2010 to the present. You can use parameter settings in our SDK to fetch data within a specific time range.

Storage location

This dataset is stored in the East US Azure region. We recommend locating compute resources in East US for affinity.

Additional information

This dataset is sourced from city of Seattle government. For more information, see the city of Seattle website. View the Licensing and Attribution for the terms of using this dataset. Email open.data@seattle.gov if you have any questions about the data source.

Columns

Name Data type Unique Values (sample) Description
address string 196,965 517 3rd Av 318 2nd Av Et S Location of Incident.
category string 232 Aid Response Medic Response Response Type.
dataSubtype string 1 911_Fire “911_Fire”
dataType string 1 Safety “Safety”
dateTime timestamp 1,533,401 2020-11-04 06:49:00 2019-06-19 13:49:00 The date and time of the call.
latitude double 94,332 47.602172 47.600194 This is the latitude value. Lines of latitude are parallel to the equator.
longitude double 79,492 -122.330863 -122.330541 This is the longitude value. Lines of longitude run perpendicular to lines of latitude, and all pass through both poles.

Preview

dataType dataSubtype dateTime category subcategory status address latitude longitude source extendedProperties
Safety 911_Fire 4/28/2021 5:22:00 AM Rubbish Fire null null 200 University St 47.607299 -122.337087 null
Safety 911_Fire 4/28/2021 5:15:00 AM Triaged Incident null null 6th Ave / Olive Way 47.61313 -122.336282 null
Safety 911_Fire 4/28/2021 5:12:00 AM Aid Response null null 4th Ave S / Seattle Blvd S 47.596486 -122.329046 null
Safety 911_Fire 4/28/2021 5:09:00 AM Rubbish Fire null null 3rd Ave / University St 47.607763 -122.335976 null
Safety 911_Fire 4/28/2021 4:57:00 AM Low Acuity Response null null 533 3rd Ave W 47.623717 -122.360635 null
Safety 911_Fire 4/28/2021 4:57:00 AM Trans to AMR null null 4638 S Austin St 47.534702 -122.274812 null
Safety 911_Fire 4/28/2021 4:55:00 AM Triaged Incident null null 8th Ave N / Harrison St 47.622051 -122.341066 null

Data access

Azure Notebooks

Tip

Contents of DownloadNotebook?serviceType=AzureNotebooks&package=azureml-opendatasets&registryId=city_safety_seattle. Open in GitHub.

# This is a package in preview.
from azureml.opendatasets import SeattleSafety

from datetime import datetime
from dateutil import parser


end_date = parser.parse('2016-01-01')
start_date = parser.parse('2015-05-01')
safety = SeattleSafety(start_date=start_date, end_date=end_date)
safety = safety.to_pandas_dataframe()
safety.info()

Azure Databricks

# This is a package in preview.
# You need to pip install azureml-opendatasets in Databricks cluster. https://docs.microsoft.com/en-us/azure/data-explorer/connect-from-databricks#install-the-python-library-on-your-azure-databricks-cluster
from azureml.opendatasets import SeattleSafety

from datetime import datetime
from dateutil import parser


end_date = parser.parse('2016-01-01')
start_date = parser.parse('2015-05-01')
safety = SeattleSafety(start_date=start_date, end_date=end_date)
safety = safety.to_spark_dataframe()
display(safety.limit(5))

Azure Synapse

# This is a package in preview.
from azureml.opendatasets import SeattleSafety

from datetime import datetime
from dateutil import parser


end_date = parser.parse('2016-01-01')
start_date = parser.parse('2015-05-01')
safety = SeattleSafety(start_date=start_date, end_date=end_date)
safety = safety.to_spark_dataframe()
# Display top 5 rows
display(safety.limit(5))

Examples

Next steps

View the rest of the datasets in the Open Datasets catalog.