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波士顿安全数据

项目
12/06/2023

向波士顿市报告了 311 次呼叫。

请参阅此链接以详细了解 BOS:311。

注意

Microsoft 按“原样”提供 Azure 开放数据集。 Microsoft 对数据集的使用不提供任何担保（明示或暗示）、保证或条件。在当地法律允许的范围内，Microsoft 对使用数据集而导致的任何损害或损失不承担任何责任，包括直接、必然、特殊、间接、偶发或惩罚性损害或损失。

此数据集是根据 Microsoft 接收源数据的原始条款提供的。数据集可能包含来自 Microsoft 的数据。

数量和保留期

此数据集以 Parquet 格式存储。每天更新一次，截至 2019 年总共包含约 10 万行 (10 MB) 记录。

此数据集包含从 2011 年至今累积的历史记录。可使用我们的 SDK 中的参数设置来提取特定时间范围内的数据。

存储位置

此数据集存储在美国东部 Azure 区域。建议将计算资源分配到美国东部地区，以实现相关性。

其他信息

此数据集来自波士顿市政府。有关详细信息，请参见波士顿数据集站点。有关数据集许可，请参阅开放数据共享公共领域贡献和许可 (ODC PDDL)。

列

名称	数据类型	唯一	值（示例）	说明
address	string	140,612	" " 1 City Hall Plz Boston MA 02108	位置。
category	string	54	街道清洁卫生设施	服务请求原因。
dataSubtype	字符串	1	311_All	“311_All”
dataType	字符串	1	安全	“安全”
dateTime	timestamp	1,529,075	2015-07-23 10:51:00 2015-07-23 10:47:00	服务请求的公开日期和时间。
latitude	Double	1,622	42.3594 42.3603	这是纬度值。纬线平行于赤道。
longitude	Double	1,806	-71.0587 -71.0583	这是经度值。经度线垂直于纬度线，并且都穿过两个极点。
source	字符串	7	Constituent Call Citizens Connect App	案件的原始来源。
状态	字符串	2	Closed Open	事件状态。
子类别	string	209	Parking Enforcement Requests for Street Cleaning	服务请求类型。

预览

ataType	dataSubtype	dateTime	category	子类别	状态	address	latitude	longitude	source
安全	311_All	4/27/2021 11:45:49 PM	Enforcement & Abandoned Vehicles	Parking Enforcement	打开	51 Gardner St Allston MA 02134	42.3535	-71.1285	Citizens Connect App
安全	311_All	4/27/2021 11:43:43 PM	Sanitation	Missed Trash/Recycling/Yard Waste/Bulk Item	打开	4 Putnam Pl Roxbury MA 02119	42.3298	-71.0883	自助服务
安全	311_All	4/27/2021 11:37:19 PM	Enforcement & Abandoned Vehicles	Parking Enforcement	打开	36 Raven St Dorchester MA 02125	42.3177	-71.0546	Citizens Connect App
安全	311_All	4/27/2021 11:30:00 PM	Sanitation	Missed Trash/Recycling/Yard Waste/Bulk Item	打开	58 Bicknell St Dorchester MA 02121	42.2984	-71.0834	Constituent Call
安全	311_All	4/27/2021 11:10:20 PM	Enforcement & Abandoned Vehicles	Parking Enforcement	打开	2000 Commonwealth Ave Brighton MA 02135	42.3394	-71.1585	Citizens Connect App
安全	311_All	4/27/2021 11:06:00 PM	Noise Disturbance	Loud Parties/Music/People	开放	INTERSECTION of Lewis St & North St Boston MA	42.3594	-71.0587	Constituent Call
安全	311_All	4/27/2021 11:05:00 PM	Enforcement & Abandoned Vehicles	Parking Enforcement	打开	1 Nassau St Boston MA 02111	42.3486	-71.0629	Constituent Call
安全	311_All	4/27/2021 11:00:55 PM	Code Enforcement	Poor Conditions of Property	打开	17 Mercer St South Boston MA 02127	42.3332	-71.0492	Citizens Connect App

数据访问

Azure Notebooks

# 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()

safety.info()

# 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

# Azure storage access info
azure_storage_account_name = "azureopendatastorage"
azure_storage_sas_token = r""
container_name = "citydatacontainer"
folder_name = "Safety/Release/city=Boston"

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)

# 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)

# you can add your filter at below
print('Loaded as a Pandas data frame: ')
df

Azure Databricks

# This is a package in preview.
# You need to pip install azureml-opendatasets in Databricks cluster. https://learn.microsoft.com/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()

display(safety)

# Azure storage access info
blob_account_name = "azureopendatastorage"
blob_container_name = "citydatacontainer"
blob_relative_path = "Safety/Release/city=Boston"
blob_sas_token = r""

# 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)

# 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')

# Display top 10 rows
print('Displaying top 10 rows: ')
display(spark.sql('SELECT * FROM source LIMIT 10'))

Azure Synapse

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()

display(safety)

# Azure storage access info
blob_account_name = "azureopendatastorage"
blob_container_name = "citydatacontainer"
blob_relative_path = "Safety/Release/city=Boston"
blob_sas_token = r""

# 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)

# 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')

# Display top 10 rows
print('Displaying top 10 rows: ')
display(spark.sql('SELECT * FROM source LIMIT 10'))

示例

请参阅 GitHub 上的城市安全分析示例。

后续步骤

查看开放数据集目录中的其余数据集。