주식 분석을 위한 모든 주가 데이터 수집

February 25, 2022 8 분 소요

주식 데이터 받아오기

주가 데이터를 가져오는 라이브러리들이 있습니다.

finance-datareader
pykrx
pandas_datareader

finance-datareader

!pip install finance-datareader

Collecting finance-datareader
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Installing collected packages: requests-file, finance-datareader
Successfully installed finance-datareader-0.9.31 requests-file-1.5.1

import FinanceDataReader as fdr
import matplotlib.pyplot as plt
import pandas as pd

전체 종목 정보 가져오기

df = fdr.StockListing('KRX')      # 국내 종목
# df = fdr.StockListing('KOSPI')    # KOSPI 종목 
# df = fdr.StockListing('KOSDAQ')   # KOSDAQ 종목
# df = fdr.StockListing('KONEX')    # KONEX 종목

# df = fdr.StockListing('NASDAQ')   # 나스닥 종목
# df = fdr.StockListing('NYSE')     # 뉴욕 증권거래소 종목
# df = fdr.StockListing('AMEX')     # AMEX 종목
# df = fdr.StockListing('SP500')    # S&P500 종목

df

	Symbol	Market	Name	Sector	Industry	ListingDate	SettleMonth	Representative	HomePage	Region
0	060310	KOSDAQ	3S	전자부품 제조업	반도체 웨이퍼 캐리어	2002-04-23	03월	김세완	http://www.3sref.com	서울특별시
1	095570	KOSPI	AJ네트웍스	산업용 기계 및 장비 임대업	렌탈(파렛트, OA장비, 건설장비)	2015-08-21	12월	박대현	http://www.ajnet.co.kr	서울특별시
2	006840	KOSPI	AK홀딩스	기타 금융업	지주사업	1999-08-11	12월	채형석, 이석주(각자 대표이사)	http://www.aekyunggroup.co.kr	서울특별시
3	054620	KOSDAQ	APS홀딩스	기타 금융업	인터넷 트래픽 솔루션	2001-12-04	12월	정기로	http://www.apsholdings.co.kr	경기도
4	265520	KOSDAQ	AP시스템	특수 목적용 기계 제조업	디스플레이 제조 장비	2017-04-07	12월	김영주	http://www.apsystems.co.kr	경기도
...	...	...	...	...	...	...	...	...	...	...
7883	000547	KOSPI	흥국화재2우B	NaN	NaN	NaT	NaN	NaN	NaN	NaN
7884	000545	KOSPI	흥국화재우	NaN	NaN	NaT	NaN	NaN	NaN	NaN
7885	003280	KOSPI	흥아해운	해상 운송업	외항화물운송업(케미컬탱커)	1976-06-29	12월	이환구	http://www.heung-a.com	서울특별시
7886	037440	KOSDAQ	희림	건축기술, 엔지니어링 및 관련 기술 서비스업	설계 및 감리용역	2000-02-03	12월	정영균, 이목운, 허철호 (각자대표)	http://www.heerim.com	서울특별시
7887	238490	KOSDAQ	힘스	특수 목적용 기계 제조업	OLED Mask 인장기, OLED Mask 검사기 등	2017-07-20	12월	김주환	http://www.hims.co.kr	인천광역시

7888 rows × 10 columns

특정 종목 주가 데이터 가져오기

국내

df = fdr.DataReader(‘종목코드’,’시작일자’,’종료일자’)

해외

df = fdr.DataReader(‘티커’,’시작일자’,’종료일자’)

삼성주식 분석

df = fdr.DataReader('005930','2021-01-01','2022-02-24')   # 삼성전자: 005930
df

	Open	High	Low	Close	Volume	Change
Date
2021-01-04	81000	84400	80200	83000	38655276	0.024691
2021-01-05	81600	83900	81600	83900	35335669	0.010843
2021-01-06	83300	84500	82100	82200	42089013	-0.020262
2021-01-07	82800	84200	82700	82900	32644642	0.008516
2021-01-08	83300	90000	83000	88800	59013307	0.071170
...	...	...	...	...	...	...
2022-02-18	74600	74800	73700	74300	10122226	-0.009333
2022-02-21	73200	74300	72600	74200	10489717	-0.001346
2022-02-22	73000	73400	72800	73400	11692469	-0.010782
2022-02-23	73800	73800	72800	73000	10397964	-0.005450
2022-02-24	72300	72300	71300	71500	15502410	-0.020548

284 rows × 6 columns

plt.figure(figsize=(12, 8))
plt.plot(df['Close'])
plt.show()

캔들 차트 그리기

fdr.chart.plot(df)

pykrx

https://github.com/sharebook-kr/pykrx

KRX, Naver 등의 웹사이트에서 주가정보를 스크래핑하는 모듈

!pip install pykrx

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Installing collected packages: zope.interface, deprecated, datetime, pykrx
Successfully installed datetime-4.4 deprecated-1.2.13 pykrx-1.0.32 zope.interface-5.4.0

from pykrx import stock

전체 종목 정보 가져오기

전체 종목 코드: get_market_ticker_list(date=”YYYYMMDD”, market=”거래소명”)

특정 일자 전체 종목 시세: get_market_ohlcv_by_ticker(date=”YYYYMMDD”, market=”거래소명”)

모든 종목의 가격 변동 조회: get_market_price_change_by_ticker(fromdate=”조회시작일”, todate=”조회종료일”, market=”거래소명”)

stock.get_market_ticker_list("20220224")[:6]

['095570', '006840', '027410', '282330', '138930', '001460']

df = stock.get_market_ohlcv_by_ticker(date="20220224")
df

	시가	고가	저가	종가	거래량	거래대금	등락률
티커
095570	5450	5450	5260	5300	66711	354912630	-2.93
006840	21400	21400	20500	21000	50468	1055142950	-2.78
027410	5080	5100	5000	5030	65005	327341580	-0.79
282330	161000	165000	159500	161500	21861	3538699500	-0.92
138930	7920	7930	7750	7790	1382061	10816326070	-2.38
...	...	...	...	...	...	...	...
069260	21650	22200	21600	21700	110504	2413462250	-2.03
000540	3690	3700	3580	3585	25472	92364185	-2.85
000547	28450	28450	27150	28400	1555	42868050	-0.18
000545	7880	8000	7790	7890	1985	15529770	0.13
003280	3400	3835	3230	3460	34135710	121297048360	12.70

940 rows × 7 columns

df = stock.get_market_price_change_by_ticker(fromdate="20220222", todate="20220224")
df.head()

	종목명	시가	종가	변동폭	등락률	거래량	거래대금
티커
095570	AJ네트웍스	5520	5300	-220	-3.99	147733	794939110
006840	AK홀딩스	22000	21000	-1000	-4.55	172797	3734119550
027410	BGF	5140	5030	-110	-2.14	258600	1311909710
282330	BGF리테일	166000	161500	-4500	-2.71	76115	12401949500
138930	BNK금융지주	8140	7790	-350	-4.30	4009541	31779723550

특정 종목 가져오기

일자별 OHLCV(시가, 고가, 저가, 종가, 거래량) 조회

stock.get_market_ohlcv("20210101", "20220224", "005930")

	시가	고가	저가	종가	거래량
날짜
2021-01-04	81000	84400	80200	83000	38655276
2021-01-05	81600	83900	81600	83900	35335669
2021-01-06	83300	84500	82100	82200	42089013
2021-01-07	82800	84200	82700	82900	32644642
2021-01-08	83300	90000	83000	88800	59013307
...	...	...	...	...	...
2022-02-18	74600	74800	73700	74300	10122226
2022-02-21	73200	74300	72600	74200	10489717
2022-02-22	73000	73400	72800	73400	11692469
2022-02-23	73800	73800	72800	73000	10397964
2022-02-24	72300	72300	71300	71500	15502410

284 rows × 5 columns

DIV/BPS/PER/EPS 조회

특정일자의 종목별 DIV/BPS/PER/EPS 조회

ㄴ get_market_fundamental_by_ticker(date=”YYYYMMDD”, market=”거래소명”)

일자별 DIV/BPS/PER/EPS 조회

ㄴ get_market_fundamental_by_date(fromdate, todate, ticker, freq=’d’, name_display=False)

stock.get_market_fundamental_by_ticker(date="20220224", market='KOSPI')

	BPS	PER	PBR	EPS	DIV	DPS
티커
095570	6089	0.000000	0.870117	0	3.960938	210
006840	50471	0.000000	0.419922	0	1.900391	400
027410	15781	17.656250	0.320068	285	2.189453	110
282330	40317	22.734375	4.011719	7103	1.490234	2400
138930	26781	5.199219	0.290039	1498	4.109375	320
...	...	...	...	...	...	...
069260	16351	16.796875	1.330078	1292	4.609375	1000
000540	11107	13.382812	0.320068	268	0.000000	0
000547	0	0.000000	0.000000	0	0.000000	0
000545	0	0.000000	0.000000	0	0.000000	0
003280	0	0.000000	0.000000	0	0.000000	0

913 rows × 6 columns

stock.get_market_fundamental_by_date(fromdate="20220222", todate="20220224", ticker="005930")

	BPS	PER	PBR	EPS	DIV	DPS
날짜
2022-02-22	39406	19.11	1.86	3841	4.08	2994
2022-02-23	39406	19.01	1.85	3841	4.10	2994
2022-02-24	39406	18.61	1.81	3841	4.19	2994

공매도 거래비중 상위 50 종목

get_shorting_trade_top50(“날짜”)

stock.get_shorting_volume_top50("20220223").head()

	순위	공매도거래대금	총거래대금	공매도비중	직전40일거래대금평균	공매도거래대금증가율	직전40일공매도평균비중	공매도비중증가율	주가수익률
티커
023530	1	1497378700	4654956200	32.17	1069107545	1.40	14.84	2.17	-0.92
090430	2	14113889500	47737739000	29.57	7608746575	1.85	17.37	1.70	-1.59
008560	3	2890286100	9881029600	29.25	1896946657	1.52	14.34	2.04	-3.34
003240	4	153127000	556363000	27.52	44369800	3.45	5.31	5.19	0.59
003670	5	4384209500	18154011500	24.15	4528691925	0.97	13.98	1.73	0.44

pandas_datareader

!pip install requests_cache

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import pandas_datareader as pdr
import requests_cache

코스피 코스닥 지수 가져오기

pdr.DataReader(‘종목’, ‘yahoo’, start, end)

session = requests_cache.CachedSession(cache_name='cache', backend='sqlite')
# just add headers to your session and provide it to the reader
session.headers = {'User-Agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:89.0) Gecko/20100101 Firefox/89.0', 'Accept': 'application/json;charset=utf-8'}

kospi = pdr.DataReader('^KS11','yahoo', "20210101", "20220224", session=session)
kospi

	High	Low	Open	Close	Volume	Adj Close
Date
2021-01-04	2946.540039	2869.110107	2874.500000	2944.449951	1026500	2944.449951
2021-01-05	2990.570068	2921.840088	2943.669922	2990.570068	1519900	2990.570068
2021-01-06	3027.159912	2961.370117	2993.340088	2968.209961	1793400	2968.209961
2021-01-07	3055.280029	2980.750000	2980.750000	3031.679932	1524700	3031.679932
2021-01-08	3161.110107	3040.110107	3040.110107	3152.179932	1297900	3152.179932
...	...	...	...	...	...	...
2022-02-18	2747.080078	2711.879883	2714.520020	2744.520020	512900	2744.520020
2022-02-21	2746.620117	2694.899902	2706.649902	2743.800049	495000	2743.800049
2022-02-22	2721.840088	2690.090088	2705.080078	2706.790039	648100	2706.790039
2022-02-23	2729.560059	2705.310059	2727.429932	2719.530029	537700	2719.530029
2022-02-24	2694.550049	2642.629883	2689.280029	2648.800049	903880	2648.800049

283 rows × 6 columns

plt.figure(figsize=(12, 8))
plt.plot(kospi['Close'])
plt.show()

WARNING:matplotlib.font_manager:findfont: Font family ['Malgun Gothic'] not found. Falling back to DejaVu Sans.

fdr.chart.plot(kospi)

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