Stock Python Utils
read yahoo data from datareader
read yahoo data from datareader
pip install fix_yahoo_finance
from pandas_datareader import data as pdr
import fix_yahoo_finance as yf
yf.pdr_override()
data = pdr.get_data_yahoo("SPY",start="2017-01-01",end="2017-04-30")
data = pdr.get_data_yahoo(["SPY","IWM"],start="2017-01-01",end="2017-04-30")
Receive Kospi data using data-reader from Yahoo
Receive Kospi data using data-reader from Yahoo
import pandas_datareader as wb
import pandas as pd
import datetime
import matplotlib.pyplot as plt
pd.set_option('precision', 3)
start = datetime.datetime(2014, 12, 8)
end = datetime.datetime(2017, 11, 7)
df_null = wb.DataReader("003490.KS","yahoo",start,end)
df = df_null.dropna()
kospi_chart = df.Close.plot(style='b')
kospi_chart.set_title("Korean Air")
kospi_chart.set_ylabel("Price")
kospi_chart.set_xlim(str(start), str(end))
print(df)
print("Close Median", df['Close'].median())
print()
print(df['Close'].describe())
print()
print(df.corr())
print()
original_price = df.iloc[0,3]
nextday_price = df.iloc[1,3]
current_price = df.iloc[-1,3]
month_after_price = df.iloc[30,3]
nextday_change = ((nextday_price-original_price) / original_price)
month_change = ((month_after_price-original_price) / original_price)
current_change = ((current_price-original_price) / original_price)
print("Next day Change: {:.2%}.".format(nextday_change))
print("Month After Change: {:.2%}.".format(month_change))
print("Current Change: {:.2%}.".format(current_change))
plt.show()
Financial price data reader (an alternative to google finance and yahoo finance in pandas-datareader)
Install
pip install finance-datareader # for install
pip install -U finance-datareader # for update
Usage
import FinanceDataReader as fdr
# Apple(AAPL), 2017~Now
df = fdr.DataReader('AAPL', '2017')
# AMAZON(AMZN), 2010~Now
df = fdr.DataReader('AMZN', '2010')
# Celltrion(068270), 2018-07-01~Now
df = fdr.DataReader('068270', '2018-07-01')
# country code: ex) 000150: Doosan(KR), Yihua Healthcare(CN)
df = fdr.DataReader('000150', '2018-01-01', '2018-03-30') # default: 'KR'
df = fdr.DataReader('000150', '2018-01-01', '2018-03-30', country='KR')
df = fdr.DataReader('000150', '2018-01-01', '2018-03-30', country='CN')
# KOSPI index, 2015~Now
df = fdr.DataReader('KS11', '2015')
# Dow Jones Industrial(DJI), 2015년~Now
df = fdr.DataReader('DJI', '2015')
# USD/KRW, 1995~Now
df = fdr.DataReader('USD/KRW', '1995')
# Bitcoin KRW price (Bithumbs), 2016 ~ Now
df = fdr.DataReader('BTC/KRW', '2016')
# KRX stock symbols and names
df_krx = fdr.StockListing('KRX')
# S&P 500 symbols
df_spx = fdr.StockListing('S&P500')
거래소 상장회사검색
네이버재무제표 가져오기
KRX 종목 마스터 만들기
종목마스터+만들기mysql과+sqlalchemy.ipynb
종목마스터+만들기mysql과+sqlalchemy.ipynb
mysql install
pip3 install mysqlclient
sudo apt-get install python3-dev libmysqlclient-dev
pip3 install mysql-connector
pip3 install configparser
sudo apt-get install -y python3-mysqldb
sudo apt-get install libmysqlclient-dev
sudo pip3 install mysqlclient
pip3 install MySQL-python
sudo apt-get install python3-mysql.connector # import mysql
sudo pip3 install sqlalchemy
distutils install problem
Reduced version,
pip install --upgrade --force-reinstall pip==9.0.3
#Tried to re-install package
pip install xxx --disable-pip-version-check
#At last, recover the latest version for pip
pip install --upgrade pip
The Trading Economics Application Programming Interface (API)
The Trading Economics Application Programming Interface (API)
pip install tradingeconomics
import tradingeconomics as te
te.login('Your_Key:Your_Secret')
te.login()
te.getIndicatorData(country=['united states', 'china'], output_type='df')
Output:
Country ... PreviousValueDate
0 United States ... 2018-04-30T00:00:00
1 United States ... 2018-06-15T00:00:00
2 United States ... 2017-12-31T00:00:00
... ... ...
314 China ... 2016-12-31T00:00:00
315 United States ... 2016-12-31T00:00:00
316 United States ... 2018-04-30T00:00:00
317 United States ... 2018-04-30T00:00:00
yahoo finance
pip install yahoo-finance
from yahoo_finance import Share
import pandas as pd
from pandas import DataFrame, Series
samsung = Share('005930.KS')
df = DataFrame(samsung.get_historical('2016-07-04','2016-07-08'))
google finance
from googlefinance.get import get_code
# get_code('NASDAQ')
get_code('KOSPI')
Code Code_int Google Name
0 001040 1040 KRX:001040 CJ
1 012630 12630 KRX:012630 HDC
2 082740 82740 KRX:082740 HSD엔진
Getting Historical Financial Data
Getting the Only Single Company’s Historical Financial Data
code = ‘NASDAQ: code list’
period = ‘30d’: 30 days (default), ‘1M’ : Month , ‘1Y’ : year
interval = 86400 : 1 day (default), 60 * integer (seconds)
>>> from googlefinance.get import get_datum
>>> df = get_datum('KRX:005930', period='2M'， interval =86400)
date Open High Low Close Volume
2018-05-04 53000.0 53900.0 51800.0 51900.0 39290305
2018-05-08 52600.0 53200.0 51900.0 52600.0 22907823
2018-05-09 52600.0 52800.0 50900.0 50900.0 15914664
import pandas as pd
pd.core.common.is_list_like = pd.api.types.is_list_like
from pandas_datareader import data
import fix_yahoo_finance as yf
yf.pdr_override()
start_date = '1996-05-06' #startdate를 1996년으로 설정해두면 가장 오래된 데이터부터 전부 가져올 수 있다.
tickers = ['067160.KQ', '035420.KS'] #1 아프리카tv와 네이버의 ticker(종목코드)
afreeca = data.get_data_yahoo(tickers[0], start_date)
naver = data.get_data_yahoo(tickers[1], start_date)
skhynix = data.get_data_yahoo('000660.KS', start_date)
kospi = data.get_data_yahoo('^KS11', start_date)