September 2022
Intermediate to advanced
549 pages
11h 27m
Chinese
Content preview from 基于AWS的数据科学实践
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探索数据集
｜
161
5.3
查询数据仓库
在此处，我们会使用
Amazon Redshift
来查询并可视化用例。与
Athena
的例子相似，
我们首先需要准备
SageMaker Studio
环境。
5.3.1
从
SageMaker Studio
运行一条
Amazon Redshift
示例查询
在以下示例中，我们会查询数据集来获取与每个产品类别关联的唯一客户的数量。
我们可以使用
pandas
的
read_sql_query
函数来运行
SQLAlchemy
查询并存储查询
结果到
pandas
的数据帧：
df = pd.read_sql_query("""
SELECT product_category, COUNT(DISTINCT customer_id) as num_customers
FROM redshift.amazon_reviews_tsv_2015
GROUP BY product_category
ORDER BY num_customers DESC
""", engine)
df.head(10)
输出应如下所示：
product_category num_customers
Wireless 1979435
Digital_Ebook_Purchase 1857681
Books 1507711
Apparel 1424202
Home 1352314
PC 1283463
Health & Personal Care 1238075
Beauty 1110828 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.