June 2018
Beginner to intermediate
304 pages
7h 38m
Korean
Content preview from 우아한 사이파이: 수학, 과학, 엔지니어링을 위한 파이썬 데이터 분석 라이브러리 SciPy
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43
1
장
우아한 넘파이 : 파이썬 과학 기초
유전자 길이를 다음과 같이 얻을 수 있다.
# 각 유전자 길이를 포함한
1
차원
ndarray
gene
_
lengths
=
np
.
asarray
(
gene
_
info
.
loc
[
matched
_
index
]['
GeneLength
'],
dtype
=
int
)
두 객체가 몇 차원인지 확인해보자.
print
(
counts
.
shape
)
print
(
gene
_
lengths
.
shape
)
(
20500
,
375
)
(
20500
,)
예상대로 이제 두 데이터는 일치한다.
1.4
정규화
실제 데이터에는 모든 종류의 측정 결과가 포함된다. 데이터를 분석하기 전에 정규화를 어떻게
적용할 것인지가 중요하다. 예를 들어 디지털 온도계로 측정한 값은 수은 온도계로 사람이 측
정한 값과 다를 수 있다. 따라서 샘플을 비교하려면 모든 측정을 공통된 값으로 가져오는 데이
터 랭글링
15
이 필요하다.
이번 예제에서는 두 데이터의 차이가 기술이 아닌 실제 생물학적으로 차이가 있는지 확인한다.
유전자 발현 데이터셋에 공통으로 적용되는 두 가지의 정규화(샘플(열) 간의 정규화, 유전자
(행) 간의 정규화 )를 사용한다.
1.4.1
샘플 간 비교
RNA
염기서열분석 실험에서 각 개체 수는 크게 다를 수 있다. 모든 유전자 발현 수의 분포를
15
역주_
data
wrangling
. ...
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