# 데이터셋 생성 함수
look_back = 1
def create_dataset(dataset, look_back=1):
dataX, dataY = [], []
for i in range(len(dataset)-look_back-1):
a = dataset[i:(i + look_back)]
dataX.append(a)
dataY.append(dataset[i + look_back])
return np.array(dataX), np.array(dataY)
#
# 저장되어있는 주식데이터 불러오기
#
sydtpath = os.path.join(settings.BASE_DIR, 'chart_data/%s' % (settings.get_today_str()))
stock_code = "lgdisplay"
fullpath = sydtpath + os.path.sep + stock_code + '.csv'
pandf = pd.read_csv(fullpath, index_col="Date")
# 데이터 전처리
nparr = pandf['Close'].values[1:] # 맨처음 'Close'데이터부터 차례대로 nparr에 저장
print(nparr)
nparr.astype('float32') # float형으로 변환
print(nparr)
nparr = nparr.reshape(-1,1)
print(nparr)
# 정규화 (0~1사이의 값으로 바꿔준다)
scaler = MinMaxScaler(feature_range=(0, 1))
nptf = scaler.fit_transform(nparr)
sql = "select stock_price from stock_hye WHERE company_name='삼성'"
cursor.execute("set names utf8")
cursor.execute(sql)
result_stock_price = cursor.fetchone()
for i in result_stock_price:
price = i
#
# 저장되어있는 주식데이터 불러오기
#
sydtpath = os.path.join(settings.BASE_DIR,
'chart_data/%s' % (settings.get_today_str()))
stock_code = "samsung"
fullpath = sydtpath + os.path.sep + stock_code + '.csv'
pandf = pd.read_csv(fullpath, index_col="Date")
# 데이터 전처리
now = pandf['Close'].values[-1] # 맨마지막 'Close'데이터
now.astype('int') # int형으로 변환
sql = "UPDATE `stock_hye` SET `rate` = %s WHERE `company_name` = %s"
accuracy = float((price - now) / now * 100)
#if accuracy > 0 :
#accuracy = "+" + str(accuracy)
#print(accuracy)
# coding: utf-8
# In[1]:
#
# csv파일 저장
#
import FinanceDataReader as fdr
import settings
import os
import locale
from datetime import date, timedelta
start_date = '2009-01-01' # 최근 10년간 데이터
end_date = settings.get_today_str() # 오늘날짜
#end_date = date.today() - timedelta(1) # 어제날짜
stocks = ['samsung', 'kakao', 'naver', 'cj', 'lg', 'sk', 'lgdisplay', 'dusan', 'asiana', 'jeju', 'hanhwa', 'hyundai', 'hite']
#stocks = ['005930', '035720', '035420', '001040', '066570', '034730', '034220', '000150', '020560', '089590', '000880', '005380', '000080']
# .csv파일을 저장할 디렉토리
data_dir = os.path.join(
settings.BASE_DIR, 'chart_data/%s' % (
settings.get_today_str())) # timestr : 날짜, 시간
if not os.path.isdir(data_dir):
os.makedirs(data_dir)
############################ csv파일 추가 ############################
## samsung
df = fdr.DataReader('005930', start_date, end_date)
#df.to_csv('./chart_data/%s/%s.csv' % (settings.get_today_str(), stocks[0]))
