US Local Area Unemployment Statistics

The Local Area Unemployment Statistics (LAUS) program produces monthly and annual employment, unemployment, and labor force data for Census regions and divisions, States, counties, metropolitan areas, and many cities in the United States.

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.

README containing file for detailed information about this dataset is available at original dataset location.

This dataset is sourced from Local Area Unemployment Statistics data published by US Bureau of Labor Statistics (BLS). Review Linking and Copyright Information and Important Web Site Notices for the terms and conditions related to the use this dataset.

Storage location

This dataset is stored in the East US Azure region. Allocating compute resources in East US is recommended for affinity.

Related datasets

• US National Employment Hours and Earnings
• US State Employment Hours and Earnings
• US Labor Force Statistics

Columns

Name	Data type	Unique	Values (sample)	Description
area_code	string	8,290	ST3400000000000 RD8200000000000	Code identifying the geographic area. See https://download.bls.gov/pub/time.series/la/la.area.
area_text	string	8,238	District of Columbia Oregon	Name of the geographic area. See https://download.bls.gov/pub/time.series/la/la.area
area_type_code	string	14	F G	Unique code defining the type of area. See https://download.bls.gov/pub/time.series/la/la.area_type
areatype_text	string	14	Counties and equivalents Cities and towns above 25,000 population	Name of the area type.
footnote_codes	string	5	nan P
measure_code	string	4	5 4	Code identifying element measured. 03: unemployment rate, 04: unemployment, 05: employment, 06: labor force. See https://download.bls.gov/pub/time.series/la/la.measure.
measure_text	string	4	employment unemployment	Name of element measured. See https://download.bls.gov/pub/time.series/la/la.measure
period	string	13	M07 M05	Identifies period, typically the month. See https://download.bls.gov/pub/time.series/la/la.period
seasonal	string	2	U S
series_id	string	33,476	LASST160000000000006 LASST200000000000006	Code identifying the series. See https://download.bls.gov/pub/time.series/la/la.series for complete list of series.
series_title	string	33,268	Employment: Philadelphia County/city, PA (U) Labor Force: Manassas city, VA (U)	Title identifying the series. See https://download.bls.gov/pub/time.series/la/la.series for complete list of series.
srd_code	string	53	48 23	State, region, or division code.
srd_text	string	53	Texas Maine
value	float	600,099	4.0 5.0	Value for the specific measure.
year	int	44	2009 2008

Preview

area_code	area_type_code	srd_code	measure_code	series_id	year	period	value	footnote_codes	seasonal	series_title	measure_text	srd_text	areatype_text	area_text
CA3653200000000	E	36	3	LAUCA365320000000003	2000	M01	4.7	nan	U	Unemployment Rate: Syracuse-Auburn, NY Combined Statistical Area (U)	unemployment rate	New York	Combined areas	Syracuse-Auburn, NY Combined Statistical Area
CA3653200000000	E	36	3	LAUCA365320000000003	2000	M02	4.7	nan	U	Unemployment Rate: Syracuse-Auburn, NY Combined Statistical Area (U)	unemployment rate	New York	Combined areas	Syracuse-Auburn, NY Combined Statistical Area
CA3653200000000	E	36	3	LAUCA365320000000003	2000	M03	4.2	nan	U	Unemployment Rate: Syracuse-Auburn, NY Combined Statistical Area (U)	unemployment rate	New York	Combined areas	Syracuse-Auburn, NY Combined Statistical Area
CA3653200000000	E	36	3	LAUCA365320000000003	2000	M04	3.6	nan	U	Unemployment Rate: Syracuse-Auburn, NY Combined Statistical Area (U)	unemployment rate	New York	Combined areas	Syracuse-Auburn, NY Combined Statistical Area
CA3653200000000	E	36	3	LAUCA365320000000003	2000	M05	3.6	nan	U	Unemployment Rate: Syracuse-Auburn, NY Combined Statistical Area (U)	unemployment rate	New York	Combined areas	Syracuse-Auburn, NY Combined Statistical Area
CA3653200000000	E	36	3	LAUCA365320000000003	2000	M06	3.6	nan	U	Unemployment Rate: Syracuse-Auburn, NY Combined Statistical Area (U)	unemployment rate	New York	Combined areas	Syracuse-Auburn, NY Combined Statistical Area
CA3653200000000	E	36	3	LAUCA365320000000003	2000	M07	3.6	nan	U	Unemployment Rate: Syracuse-Auburn, NY Combined Statistical Area (U)	unemployment rate	New York	Combined areas	Syracuse-Auburn, NY Combined Statistical Area

Data access

Azure Notebooks

azureml-opendatasets

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

usLaborLAUS = UsLaborLAUS()
usLaborLAUS_df = usLaborLAUS.to_pandas_dataframe()

usLaborLAUS_df.info()

azure-storage

# 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 = "laborstatisticscontainer"
folder_name = "laus/"

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

pyspark

Sample not available for this platform/package combination.

Azure Databricks

azureml-opendatasets

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

usLaborLAUS = UsLaborLAUS()
usLaborLAUS_df = usLaborLAUS.to_spark_dataframe()

display(usLaborLAUS_df.limit(5))

azure-storage

Sample not available for this platform/package combination.

pyspark

# Azure storage access info
blob_account_name = "azureopendatastorage"
blob_container_name = "laborstatisticscontainer"
blob_relative_path = "laus/"
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

azureml-opendatasets

Sample not available for this platform/package combination.

azure-storage

Sample not available for this platform/package combination.

pyspark

# Azure storage access info
blob_account_name = "azureopendatastorage"
blob_container_name = "laborstatisticscontainer"
blob_relative_path = "laus/"
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'))

Next steps

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