August 2022
Beginner to intermediate
436 pages
9h 43m
Korean
Content preview from SQL로 시작하는 데이터 분석
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131
3
장
시계열 분석
[그림
3
-
10
]은 전체 결과 중
2019
년의 데이터만 가져와 보여줍니다. 두 업종의 시계열 데이
터는 전체적으로 비슷한 추세를 보이지만,
1
월에는 남성 의류업 매출 비율이 여성 의류업 매출
비율보다 큽니다. 남성 의류업 매출 비율은
7
월경 여름에 줄어들고, 여성 의류업 매출 비율은
7
월부터
8
월까지 줄어들지 않고 유지됩니다.
여성 의류업과 남성 의류업의 연간 매출 대비 월간 매출 비율(
2019
년)
연간 매출 대비 비율
월
그림
3-10
여성 의류업과 남성 의류업의 연간 매출 대비 월간 매출 비율(
2019
년)
지금까지
SQL
을 활용해 전체 대비 비율을 계산하는 등 여러 분석법을 살펴봤습니다. 이제 시
간에 따른 비율 변화 계산을 위한 인덱싱을 알아봅시다.
132
SQL로 시작하는 데이터 분석
3.3.4
인덱싱으로 시계열 데이터 변화 이해하기
시계열 데이터에서는 값이 시간에 따라 계속 변동하는 일이 흔합니다. 예를 들어, 엔지니어가
코드를 최적화하면 웹 페이지 응답 속도가 빨라지고 상품이 인기를 얻으면 매출이 오르게 됩
니다. 데이터 인덱싱은 시계열에서 베이스 구간
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and much more.
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.