October 2018
Beginner to intermediate
328 pages
7h 58m
Korean
Content preview from 데이터 과학을 위한 통계: 데이터 분석에서 머신러닝까지 50가지 핵심 개념
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53
1
장
탐색적 데이터 분석
일변량분석과 마찬가지로, 이변량분석 역시 요약통계를 계산하고 시각화하는 것을 기본으로
한다. 이변량분석 혹은 다변량분석의 형태는 데이터가 수치형인지 아니면 범주형인지, 데이터
의 특성에 따라 달라진다.
1.8.1
육각형 구간과 등고선(수치형 변수 대 수치형 변수를 시각화)
산점도는 데이터의 개수가 상대적으로 적을 때는 괜찮다. [그림
1
-
7
]의 주가 이익 도표는 약
750
개의 점으로 이루어졌다. 수십, 수백만의 레코드를 나타내기에는 산점도의 점들이 너무 밀
집되어 알아보기 어렵다. 따라서 이러한 관계를 나타내는 다른 방법이 필요하다. 예시로 워싱
턴 주에 위치한 킹 카운티의 주택 시설에 대한 과세 평가 금액 정보를 담고 있는 데이터 집합
kc
_
tax
를 살펴보겠다. 데이터의 주요 부분에 집중하기 위해, 아주 비싸거나, 너무 작은 혹은
너무 큰 주택들은
subset
함수를 이용해 제거한다.
kc_tax0 <- subset(kc_tax, TaxAssessedValue < 750000 & SqFtTotLiving>100 &
SqFtTotLiving<3500)
nrow(kc_tax0)
[1] 432733
[그림
1
-
8
]의
육각형 구간
그림은 킹 카운티에 위치한 집들의 과세 평가액과 크기 사이의 관계
를 나타낸다. 마치 먹구름처럼 보이기도 ...
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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.
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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.