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Boston Safety Data

Boston 311 CRM Case Management City Services Public Safety

311 calls reported to the city of Boston.

Refer to this link to learn more about BOS:311.

Volume and Retention

This dataset is stored in Parquet format. It is updated daily, and contains about 100K rows (10MB) in total as of 2019.

This dataset contains historical records accumulated from 2011 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. Allocating compute resources in East US is recommended for affinity.

Additional Information

This dataset is sourced from city of Boston government. More details can be found from here. Reference Open Data Commons Public Domain Dedication and License (ODC PDDL) for the license of using this dataset.

Notices

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.

Access

Available inWhen to use
Azure Notebooks

Quickly explore the dataset with Jupyter notebooks hosted on Azure or your local machine.

Azure Databricks

Use this when you need the scale of an Azure managed Spark cluster to process the dataset.

Azure Synapse

Use this when you need the scale of an Azure managed Spark cluster to process the dataset.

Preview

dataType dataSubtype dateTime category subcategory status address latitude longitude source extendedProperties
Safety 311_All 1/19/2021 11:52:50 PM Enforcement & Abandoned Vehicles Parking Enforcement Open 89 Welles Ave Dorchester MA 02124 42.2891 -71.0664 Citizens Connect App
Safety 311_All 1/19/2021 11:36:00 PM Highway Maintenance Work Hours-Loud Noise Complaints Open 1241 Adams St Mattapan MA 02124 42.2713 -71.0694 Constituent Call
Safety 311_All 1/19/2021 11:31:22 PM Enforcement & Abandoned Vehicles Parking Enforcement Open 129 H St South Boston MA 02127 42.3333 -71.0416 Citizens Connect App
Safety 311_All 1/19/2021 11:15:00 PM Fire Hydrant Fire Hydrant Open INTERSECTION of Itasca St & Messinger St Mattapan MA 42.3594 -71.0587 Constituent Call
Safety 311_All 1/19/2021 11:11:00 PM Street Cleaning Requests for Street Cleaning Closed INTERSECTION of Southampton St & Frontage Rd Dorchester MA 42.3594 -71.0587 Constituent Call
Safety 311_All 1/19/2021 11:09:00 PM Weights and Measures Scanning Overcharge Open 370 Western Ave Brighton MA 02135 42.3609 -71.1376 Constituent Call
Safety 311_All 1/19/2021 11:08:00 PM Building Work w/out Permit Open 68 Seaverns Ave Jamaica Plain MA 02130 42.3115 -71.1104 Constituent Call
Safety 311_All 1/19/2021 11:07:00 PM Housing Overcrowding Open 2033 Columbus Ave Roxbury MA 02119 42.3143 -71.0968 Constituent Call
Safety 311_All 1/19/2021 11:04:00 PM Building Working Beyond Hours Open 69 N Margin St Boston MA 02113 42.3657 -71.0568 Constituent Call
Safety 311_All 1/19/2021 11:03:00 PM Building Working Beyond Hours Open 210 Endicott St Boston MA 02113 42.3664 -71.0581 Constituent Call
Name Data type Unique Values (sample) Description
address string 141,822 \" \"
1 City Hall Plz Boston MA 02108

Location.

category string 54 Street Cleaning
Sanitation

Reason of the service request.

dataSubtype string 1 311_All

“311_All”

dataType string 1 Safety

“Safety”

dateTime timestamp 1,705,428 2015-07-23 10:51:00
2015-07-23 10:47:00

Open date and time of the service request.

latitude double 1,622 42.3594
42.3603

This is the latitude value. Lines of latitude are parallel to the equator.

longitude double 1,806 -71.0587
-71.0583

This is the longitude value. Lines of longitude run perpendicular to lines of latitude, and all pass through both poles.

source string 7 Constituent Call
Citizens Connect App

Original source of the case.

status string 2 Closed
Open

Case status.

subcategory string 208 Parking Enforcement
Requests for Street Cleaning

Type of the service request.

Select your preferred service:

Azure Notebooks

Azure Databricks

Azure Synapse

Azure Notebooks

Package: Language: Python Python
In [1]:
# This is a package in preview.
from azureml.opendatasets import BostonSafety

from datetime import datetime
from dateutil import parser


end_date = parser.parse('2016-01-01')
start_date = parser.parse('2015-05-01')
safety = BostonSafety(start_date=start_date, end_date=end_date)
safety = safety.to_pandas_dataframe()
ActivityStarted, to_pandas_dataframe ActivityStarted, to_pandas_dataframe_in_worker Looking for parquet files... Reading them into Pandas dataframe... Reading Safety/Release/city=Boston/part-00196-tid-845600952581210110-a4f62588-4996-42d1-bc79-23a9b4635c63-447039.c000.snappy.parquet under container citydatacontainer Done. ActivityCompleted: Activity=to_pandas_dataframe_in_worker, HowEnded=Success, Duration=2213.69 [ms] ActivityCompleted: Activity=to_pandas_dataframe, HowEnded=Success, Duration=2216.01 [ms]
In [2]:
safety.info()
<class 'pandas.core.frame.DataFrame'> Int64Index: 1 entries, 56262 to 56262 Data columns (total 11 columns): dataType 1 non-null object dataSubtype 1 non-null object dateTime 1 non-null datetime64[ns] category 1 non-null object subcategory 1 non-null object status 1 non-null object address 1 non-null object latitude 1 non-null float64 longitude 1 non-null float64 source 1 non-null object extendedProperties 0 non-null object dtypes: datetime64[ns](1), float64(2), object(8) memory usage: 96.0+ bytes
In [1]:
# Pip install packages
import os, sys

!{sys.executable} -m pip install azure-storage-blob
!{sys.executable} -m pip install pyarrow
!{sys.executable} -m pip install pandas
In [2]:
# Azure storage access info
azure_storage_account_name = "azureopendatastorage"
azure_storage_sas_token = r""
container_name = "citydatacontainer"
folder_name = "Safety/Release/city=Boston"
In [3]:
from azure.storage.blob import BlockBlobServicefrom azure.storage.blob import BlobServiceClient, BlobClient, ContainerClient

if azure_storage_account_name is None or azure_storage_sas_token is None:
    raise Exception(
        "Provide your specific name and key for your Azure Storage account--see the Prerequisites section earlier.")

print('Looking for the first parquet under the folder ' +
      folder_name + ' in container "' + container_name + '"...')
container_url = f"https://{azure_storage_account_name}.blob.core.windows.net/"
blob_service_client = BlobServiceClient(
    container_url, azure_storage_sas_token if azure_storage_sas_token else None)

container_client = blob_service_client.get_container_client(container_name)
blobs = container_client.list_blobs(folder_name)
sorted_blobs = sorted(list(blobs), key=lambda e: e.name, reverse=True)
targetBlobName = ''
for blob in sorted_blobs:
    if blob.name.startswith(folder_name) and blob.name.endswith('.parquet'):
        targetBlobName = blob.name
        break

print('Target blob to download: ' + targetBlobName)
_, filename = os.path.split(targetBlobName)
blob_client = container_client.get_blob_client(targetBlobName)
with open(filename, 'wb') as local_file:
    blob_client.download_blob().download_to_stream(local_file)
In [4]:
# Read the parquet file into Pandas data frame
import pandas as pd

print('Reading the parquet file into Pandas data frame')
df = pd.read_parquet(filename)
In [5]:
# you can add your filter at below
print('Loaded as a Pandas data frame: ')
df
In [6]:
 

Azure Databricks

Package: Language: Python Python
In [1]:
# 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 BostonSafety

from datetime import datetime
from dateutil import parser


end_date = parser.parse('2016-01-01')
start_date = parser.parse('2015-05-01')
safety = BostonSafety(start_date=start_date, end_date=end_date)
safety = safety.to_spark_dataframe()
ActivityStarted, to_spark_dataframe ActivityStarted, to_spark_dataframe_in_worker ActivityCompleted: Activity=to_spark_dataframe_in_worker, HowEnded=Success, Duration=2380.02 [ms] ActivityCompleted: Activity=to_spark_dataframe, HowEnded=Success, Duration=2381.75 [ms]
In [2]:
display(safety)
dataTypedataSubtypedateTimecategorysubcategorystatusaddresslatitudelongitudesourceextendedProperties
Safety311_All2015-07-24T12:48:24.000+0000Call InquiryOCR Front Desk InteractionsClosed 42.3594-71.0587Constituent Callnull
In [1]:
# Azure storage access info
blob_account_name = "azureopendatastorage"
blob_container_name = "citydatacontainer"
blob_relative_path = "Safety/Release/city=Boston"
blob_sas_token = r""
In [2]:
# Allow SPARK to read from Blob remotely
wasbs_path = 'wasbs://%s@%s.blob.core.windows.net/%s' % (blob_container_name, blob_account_name, blob_relative_path)
spark.conf.set(
  'fs.azure.sas.%s.%s.blob.core.windows.net' % (blob_container_name, blob_account_name),
  blob_sas_token)
print('Remote blob path: ' + wasbs_path)
In [3]:
# SPARK read parquet, note that it won't load any data yet by now
df = spark.read.parquet(wasbs_path)
print('Register the DataFrame as a SQL temporary view: source')
df.createOrReplaceTempView('source')
In [4]:
# Display top 10 rows
print('Displaying top 10 rows: ')
display(spark.sql('SELECT * FROM source LIMIT 10'))

Azure Synapse

Package: Language: Python Python
In [1]:
from azureml.opendatasets import BostonSafety

from datetime import datetime
from dateutil import parser


end_date = parser.parse('2016-01-01')
start_date = parser.parse('2015-05-01')
safety = BostonSafety(start_date=start_date, end_date=end_date)
safety = safety.to_spark_dataframe()
ActivityStarted, to_spark_dataframe ActivityStarted, to_spark_dataframe_in_worker ActivityCompleted: Activity=to_spark_dataframe_in_worker, HowEnded=Success, Duration=2380.02 [ms] ActivityCompleted: Activity=to_spark_dataframe, HowEnded=Success, Duration=2381.75 [ms]
In [2]:
display(safety)
dataTypedataSubtypedateTimecategorysubcategorystatusaddresslatitudelongitudesourceextendedProperties
Safety311_All2015-07-24T12:48:24.000+0000Call InquiryOCR Front Desk InteractionsClosed 42.3594-71.0587Constituent Callnull
In [1]:
# Azure storage access info
blob_account_name = "azureopendatastorage"
blob_container_name = "citydatacontainer"
blob_relative_path = "Safety/Release/city=Boston"
blob_sas_token = r""
In [2]:
# Allow SPARK to read from Blob remotely
wasbs_path = 'wasbs://%s@%s.blob.core.windows.net/%s' % (blob_container_name, blob_account_name, blob_relative_path)
spark.conf.set(
  'fs.azure.sas.%s.%s.blob.core.windows.net' % (blob_container_name, blob_account_name),
  blob_sas_token)
print('Remote blob path: ' + wasbs_path)
In [3]:
# SPARK read parquet, note that it won't load any data yet by now
df = spark.read.parquet(wasbs_path)
print('Register the DataFrame as a SQL temporary view: source')
df.createOrReplaceTempView('source')
In [4]:
# Display top 10 rows
print('Displaying top 10 rows: ')
display(spark.sql('SELECT * FROM source LIMIT 10'))

City Safety

From the Urban Innovation Initiative at Microsoft Research, databricks notebook for analytics with safety data (311 and 911 call data) from major U.S. cities. Analyses show frequency distributions and geographic clustering of safety issues within cities.