糖尿病資料集

發行項
06/01/2023

糖尿病資料集有 442 份具有 10 項特徵的範例，因此很適合作為機器學習演算法入門。這是最熱門的 Scikit Learn Toy 資料集之一。

注意

Microsoft 依「現況」提供 Azure 開放資料集。針對　貴用戶對資料集的使用方式，Microsoft 不提供任何明示或默示的擔保、保證或條件。在　貴用戶當地法律允許的範圍內，針對因使用資料集而導致的任何直接性、衍生性、特殊性、間接性、附隨性或懲罰性損害或損失，Microsoft 概不承擔任何責任。

此資料集是根據 Microsoft 接收來源資料的原始條款所提供。資料集可能包含源自 Microsoft 的資料。

資料行

名稱	資料類型	唯一	值 (樣本)
AGE	BIGINT	58	53 60
BMI	double	163	24.1 23.5
BP	double	100	93.0 83.0
S1	BIGINT	141	162 184
S2	double	302	125.8 114.8
S3	double	63	46.0 38.0
S4	double	66	3.0 4.0
S5	double	184	4.4427 4.3041
S6	BIGINT	56	92 96
SEX	BIGINT	2	1 2
是	BIGINT	214	72 200

預覽

AGE	SEX	BMI	BP	S1	S2	S3	S4	S5	S6	是
59	2	32.1	101	157	93.2	38	4	4.8598	87	151
48	1	21.6	87	183	103.2	70	3	3.8918	69	75
72	2	30.5	93	156	93.6	41	4	4.6728	85	141
24	1	25.3	84	198	131.4	40	5	4.8903	89	206
50	1	23	101	192	125.4	52	4	4.2905	80	135
23	1	22.6	89	139	64.8	61	2	4.1897	68	97
36	2	22	90	160	99.6	50	3	3.9512	82	138
66	2	26.2	114	255	185	56	4.55	4.2485	92	63
60	2	32.1	83	179	119.4	42	4	4.4773	94	110
29	1	30	85	180	93.4	43	4	5.3845	88	310

資料存取

請使用以下程式碼範例，在 Azure Notebooks、Azure Databricks 或 Azure Synapse 中存取此資料集。

Azure Notebooks

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

diabetes = Diabetes.get_tabular_dataset()
diabetes_df = diabetes.to_pandas_dataframe()

diabetes_df.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 = "mlsamples"
folder_name = "diabetes"

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.
from azureml.opendatasets import Diabetes

diabetes = Diabetes.get_tabular_dataset()
diabetes_df = diabetes.to_spark_dataframe()

display(diabetes_df.limit(5))

# Azure storage access info
blob_account_name = "azureopendatastorage"
blob_container_name = "mlsamples"
blob_relative_path = "diabetes"
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

此平台/封裝組合沒有可用的樣本。

# Azure storage access info
blob_account_name = "azureopendatastorage"
blob_container_name = "mlsamples"
blob_relative_path = "diabetes"
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'))

後續步驟

檢視開放資料集目錄中的其餘資料集。