def import_stock_pledged() : db=cx_Oracle.connect('c##stock','didierg160','myoracle') #创建连接 cr=db.cursor() sql = "delete tb_stock_pledged" cr.execute(sql) df = ts.stock_pledged() for row in df.itertuples(): sql = "insert into tb_stock_pledged values (" sql += "'" + str(getattr(row,"code" )) + "'," sql += "'" + str(getattr(row,"name" )) + "'," sql += "'" + str(getattr(row,"deals" )) + "'," sql += "'" + str(getattr(row,"unrest_pledged" )) + "'," sql += "'" + str(getattr(row,"rest_pledged" )) + "'," sql += "'" + str(getattr(row,"totals" )) + "'," sql += "'" + str(getattr(row,"p_ratio" )) + "'," sql += "sysdate" sql += ")" cr.execute(sql) db.commit() cr.close () db.close () print("stock_pledged done")
def pledge_info(): df=ts.stock_pledged() df.to_sql('tb_pledged_base',engine,if_exists='replace') df_list=[] for stock in stocks: df_list.append(df[df['code']==stock]) df=pd.concat(df_list) # print(df) df=df.reset_index(drop=True) # print(df) df= df.sort_values('p_ratio',ascending=False) df['code']=df['code'].astype('str') df['rest_ratio']=df['rest_pledged']/df['totals']*100 df['rest_ratio']=map(lambda x:round(x,2),df['rest_ratio']) df['unrest_ratio']=df['unrest_pledged']/df['totals']*100 df['unrest_ratio']=map(lambda x:round(x,2),df['unrest_ratio'])
def baseAPI(): # df=ts.get_hist_data('002524',start='2017-01-01',end='2017-04-24') # 这个函数只能获取近3年的数据 # 目前这个版本是从最新开始 【0】 # print(df) # print(df['close'].sum()) # stock_info=ts.get_stock_basics() # print(stock_info) # stock_info.to_csv('2.csv',encoding='gbk') # n_df=pd.read_csv('2.csv',encoding='gbk') # n_df.to_excel('2.xls',encoding='gbk') # print(n_df) # 这样子居然搞定了。 # dx_1=ts.get_hist_data('603111',start='2017-01-28',end='2017-04-22') # print(dx_1) # print(len(dx_1)) # ts.get_sz50s() # print(dx_1['close'][0]) ''' print(stock_info.dtypes) cols=stock_info.columns for col in cols: if stock_info[col].dtype == 'O': print("O in " ,col) del stock_info[col] print(stock_info) stock_info.to_excel('new.xls') ''' # 编码出错 # stock_info.to_excel('base.xls',encoding='gb2312') ''' data=stock_info.ix['300141']['timeToMarket'] print(data) print(type(data)) data=str(data) print(type(data)) print(data[1:4]) print(data[4:6]) print(data) date_format=data[0:4]+'-'+data[4:6]+'-'+data[6:8] print(date_format) delta=60*7/5 day0=datetime.date(datetime.date.today().year,datetime.date.today().month,datetime.date.today().day) day30=day0-datetime.timedelta(delta) print(day30) day30=day30.strftime("%Y-%m-%d") day0=day0.strftime("%Y-%m-%d") ''' # df1=ts.new_stocks() # print(df1) # df2=ts.new_stocks(2) # print(df2) # df3=ts.new_stocks(3) # print(df3) # sz_index=ts.get_k_data('399001',index=True,start='2017-01-10',end='2017-04-28') ''' sz_index=ts.get_k_data('300141') print(sz_index) print(sz_index.ix[sz_index['date']=='2014-05-06','high'].values[0]) ''' ''' df = ts.get_realtime_quotes(['600848', '000980', '000981']) #一次过返回3个数据 print(df) ''' # bar 函数 # conn = ts.get_apis() # df =ts.bar('000022',conn,start_date='2000-01-01',adj='qfq') # print(df) # print(df.dtypes) df = ts.get_today_all() print(df) exit() filename = datetime.datetime.now().strftime('%Y-%m-%d') + '.xls' df.to_excel(filename) forecast_filename = '2017-12.xls' forecast_df = ts.forecast_data(2017, 4) print(forecast_df) forecast_df.to_excel(forecast_filename) ts.stock_pledged()
''' Created on 2018年2月8日 @author: moonlit ''' import tushare as ts if __name__ == '__main__': df = ts.stock_pledged() print(df.columns) print(len(df)) df = ts.pledged_detail() print(df.columns) print(len(df))
def baseAPI(): # df=ts.get_hist_data('002524',start='2017-01-01',end='2017-04-24') # 这个函数只能获取近3年的数据 # 目前这个版本是从最新开始 【0】 # print(df) # print(df['close'].sum()) # stock_info=ts.get_stock_basics() # print(stock_info) # stock_info.to_csv('2.csv',encoding='gbk') # n_df=pd.read_csv('2.csv',encoding='gbk') # n_df.to_excel('2.xls',encoding='gbk') # print(n_df) # 这样子居然搞定了。 # dx_1=ts.get_hist_data('603111',start='2017-01-28',end='2017-04-22') # print(dx_1) # print(len(dx_1)) # ts.get_sz50s() # print(dx_1['close'][0]) ''' print(stock_info.dtypes) cols=stock_info.columns for col in cols: if stock_info[col].dtype == 'O': print("O in " ,col) del stock_info[col] print(stock_info) stock_info.to_excel('new.xls') ''' # 编码出错 # stock_info.to_excel('base.xls',encoding='gb2312') ''' data=stock_info.ix['300141']['timeToMarket'] print(data) print(type(data)) data=str(data) print(type(data)) print(data[1:4]) print(data[4:6]) print(data) date_format=data[0:4]+'-'+data[4:6]+'-'+data[6:8] print(date_format) delta=60*7/5 day0=datetime.date(datetime.date.today().year,datetime.date.today().month,datetime.date.today().day) day30=day0-datetime.timedelta(delta) print(day30) day30=day30.strftime("%Y-%m-%d") day0=day0.strftime("%Y-%m-%d") ''' # df1=ts.new_stocks() # print(df1) # df2=ts.new_stocks(2) # print(df2) # df3=ts.new_stocks(3) # print(df3) # sz_index=ts.get_k_data('399001',index=True,start='2017-01-10',end='2017-04-28') ''' sz_index=ts.get_k_data('300141') print(sz_index) print(sz_index.ix[sz_index['date']=='2014-05-06','high'].values[0]) ''' ''' df = ts.get_realtime_quotes(['600848', '000980', '000981']) #一次过返回3个数据 print(df) ''' # bar 函数 # conn = ts.get_apis() # df =ts.bar('000022',conn,start_date='2000-01-01',adj='qfq') # print(df) # print(df.dtypes) df = ts.get_today_all() print(df) exit() filename = datetime.datetime.now().strftime('%Y-%m-%d') + '.xls' df.to_excel(filename) forecast_filename = '2017-12.xls' forecast_df = ts.forecast_data(2017, 4) print(forecast_df) forecast_df.to_excel(forecast_filename) ts.stock_pledged()
def get_all_stock_pledged(self): return tu.stock_pledged().sort_values(['p_ratio'], ascending=False)