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US Population by County

US Census Population Decennial County

A população dos EUA por género e etnia de cada condado dos EUA extraída do Census de decénio de 2000 e 2010.

Este conjunto de dados foi extraído das APIs Decennial Census Dataset (Conjunto de Dados do Censo de Decénio) do Instituto de Censo dos Estados Unidos. Reveja os Termos do Serviço e as Políticas e Avisos para obter os termos e condições relativos à utilização deste conjunto de dados.

Volume e Retenção

Este conjunto de dados está armazenado no formato Parquet e tem dados relativos aos anos de 2000 e 2010.

Localização do Armazenamento

Este conjunto de dados é armazenado na região do Azure E.U.A. Leste. A alocação de recursos de computação nos E.U.A. Leste é recomendada por questões de afinidade.

Conjuntos de Dados Relacionados

Avisos

A MICROSOFT DISPONIBILIZA OS CONJUNTOS DE DADOS ABERTOS DO AZURE TAL COMO ESTÃO. A MICROSOFT NÃO FAZ GARANTIAS, EXPRESSAS OU IMPLÍCITAS, NEM CONDIÇÕES RELATIVAMENTE À SUA UTILIZAÇÃO DOS CONJUNTOS DE DADOS. ATÉ AO LIMITE MÁXIMO PERMITIDO PELA LEGISLAÇÃO LOCAL, A MICROSOFT REJEITA QUALQUER RESPONSABILIDADE POR DANOS OU PERDAS, INCLUINDO DIRETOS, CONSEQUENCIAIS, ESPECIAIS, INDIRETOS, INCIDENTAIS OU PUNITIVOS, QUE RESULTEM DA SUA UTILIZAÇÃO DOS CONJUNTOS DE DADOS.

Este conjunto de dados é disponibilizado de acordo com os termos originais em que a Microsoft recebeu os dados de origem. O conjunto de dados pode incluir dados obtidos junto da 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

decennialTime stateName countyName population race sex minAge maxAge year
2010 Texas Crockett County 123 WHITE ALONE Male 5 9 2010
2010 Texas Crockett County 1 ASIAN ALONE Female 67 69 2010
2010 Texas Crockett County 111 WHITE ALONE Female 55 59 2010
2010 Texas Crockett County 64 TWO OR MORE RACES null 2010
2010 Texas Crockett County 18 null Male 85 2010
2010 Texas Crockett County 16 AMERICAN INDIAN AND ALASKA NATIVE ALONE Female 2010
2010 Texas Crockett County 7 WHITE ALONE Male 21 21 2010
2010 Texas Crockett County 45 null Female 85 2010
2010 Texas Crockett County 0 NATIVE HAWAIIAN AND OTHER PACIFIC ISLANDER ALONE Female 67 69 2010
2010 Texas Crockett County 4 SOME OTHER RACE ALONE Male 67 69 2010
Name Data type Unique Values (sample) Description
countyName string 1,960 Washington County
Jefferson County

O nome do país.

decennialTime string 2 2010
2000

A altura em que o Census de decénio foi realizado, por exemplo, 2010, 2000.

maxAge int 23 61
20

O máximo do intervalo de idades. Se for nulo, compreende todas as idades ou o intervalo de idades não tem um limite superior (por exemplo, idade > 85).

minAge int 23 5
55

O mínimo do intervalo de idades. Se for nulo, é transversal a todas as idades.

population int 47,229 1
2

A população deste segmento.

race string 8 ASIAN ALONE
TWO OR MORE RACES

Categoria de etnia nos dados do Census. Se for nulo, é transversal a todas as etnias.

sex string 3 Female
Male

Masculino ou feminino. Se for nulo, é transversal a ambos os géneros.

stateName string 52 Texas
Georgia

O nome do estado dos EUA.

year int 2 2010
2000

O ano (número inteiro) da hora do decénio.

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 UsPopulationCounty

population = UsPopulationCounty()
population_df = population.to_pandas_dataframe()
ActivityStarted, to_pandas_dataframe
ActivityStarted, to_pandas_dataframe_in_worker
Looking for parquet files...
Reading them into Pandas dataframe...
Reading release/us_population_county/year=2000/part-00177-tid-926394737839939592-51ecde30-440a-40fd-9b41-831814678ab5-1919150.c000.snappy.parquet under container censusdatacontainer
Reading release/us_population_county/year=2010/part-00178-tid-926394737839939592-51ecde30-440a-40fd-9b41-831814678ab5-1919151.c000.snappy.parquet under container censusdatacontainer
Done.
ActivityCompleted: Activity=to_pandas_dataframe_in_worker, HowEnded=Success, Duration=11624.4 [ms]
ActivityCompleted: Activity=to_pandas_dataframe, HowEnded=Success, Duration=11659.25 [ms]
In [2]:
population_df.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 3664512 entries, 0 to 1855295
Data columns (total 8 columns):
decennialTime    object
stateName        object
countyName       object
population       int32
race             object
sex              object
minAge           float64
maxAge           float64
dtypes: float64(2), int32(1), object(5)
memory usage: 237.6+ MB
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 = "censusdatacontainer"
folder_name = "release/us_population_county/"
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.
from azureml.opendatasets import UsPopulationCounty

population = UsPopulationCounty()
population_df = population.to_spark_dataframe()
ActivityStarted, to_spark_dataframe ActivityStarted, to_spark_dataframe_in_worker ActivityCompleted: Activity=to_spark_dataframe_in_worker, HowEnded=Success, Duration=3770.1 [ms] ActivityCompleted: Activity=to_spark_dataframe, HowEnded=Success, Duration=3771.78 [ms]
In [2]:
display(population_df.limit(5))
decennialTimestateNamecountyNamepopulationracesexminAgemaxAgeyear
2010TexasCrockett County123WHITE ALONEMale592010
2010TexasCrockett County1ASIAN ALONEFemale67692010
2010TexasCrockett County111WHITE ALONEFemale55592010
2010TexasCrockett County64TWO OR MORE RACESnullnullnull2010
2010TexasCrockett County18nullMale85null2010
In [1]:
# Azure storage access info
blob_account_name = "azureopendatastorage"
blob_container_name = "censusdatacontainer"
blob_relative_path = "release/us_population_county/"
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 [39]:
# This is a package in preview.
from azureml.opendatasets import UsPopulationCounty

population = UsPopulationCounty()
population_df = population.to_spark_dataframe()
In [40]:
# Display top 5 rows
display(population_df.limit(5))
Out[40]:
In [1]:
# Azure storage access info
blob_account_name = "azureopendatastorage"
blob_container_name = "censusdatacontainer"
blob_relative_path = "release/us_population_county/"
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'))