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파이썬을 활용한 금융 분석(2판) : 파이썬의 기초부터 금융공학, 머신러닝, 퀀트 분석, 매매 시스템 구현까지
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파이썬을 활용한 금융 분석(2판) : 파이썬의 기초부터 금융공학, 머신러닝, 퀀트 분석, 매매 시스템 구현까지

by 이브 힐피시, 김도형
March 2022
Beginner to intermediate
796 pages
18h 14m
Korean
Hanbit Media, Inc.
Content preview from 파이썬을 활용한 금융 분석(2판) : 파이썬의 기초부터 금융공학, 머신러닝, 퀀트 분석, 매매 시스템 구현까지
330
3
부
금융 데이터 과학
"No1": Int32Col(shape=(), dflt=0, pos=1),
"No2": Int32Col(shape=(), dflt=0, pos=2),
"No3": Float64Col(shape=(), dflt=0.0, pos=3),
"No4": Float64Col(shape=(), dflt=0.0, pos=4)}
byteorder := 'little'
chunkshape := (2621,)
In [179]: ll $path*
-rw-r--r-- 1 yves staff 262344490 Oct 19 12:12
/Users/yves/Temp/data/pytab.h5
-rw-r--r-- 1 yves staff 41341436 Oct 19 12:12
/Users/yves/Temp/data/pytabc.h5
In [180]: h5.close()
In [181]: !rm -f $path*
➊
ran_int ndarray
객체 저장
➋
ran_flo ndarray
객체 저장
➌
변동사항이 객체 서술에 반영
이런 객체를
HDF5
데이터베이스에 직접 쓰면 객체에 대한 루프를 돌려
Table
객체에 한 행
씩 데이터를 쓰거나 구조화된
ndarray
객체를 사용하는 것보다 빠르다.
TIP
HDF5
기반 데이터 저장
The
HDF5
계층구조 데이터베이스 ...
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Publisher Resources

ISBN: 9791162245170