# 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]))