def get_st_classified():
"""
获取风险警示板股票
Return
--------
DataFrame
code :股票代码
name :股票名称
"""
df = fd.get_stock_basics()
df.reset_index(inplace=True)
df = df[ct.FOR_CLASSIFY_COLS]
df = df.ix[df.name.str.contains('ST')]
df = df.sort_values('code').reset_index(drop=True)
return df
def get_area_classified():
"""
获取地域分类数据
Return
--------
DataFrame
code :股票代码
name :股票名称
area :地域名称
"""
df = fd.get_stock_basics()
df = df[['name', 'area']]
df.reset_index(inplace=True)
df = df.sort_values('area').reset_index(drop=True)
return df
def get_sme_classified():
"""
获取中小板股票
Return
--------
DataFrame
code :股票代码
name :股票名称
"""
df = fd.get_stock_basics()
df.reset_index(inplace=True)
df = df[ct.FOR_CLASSIFY_COLS]
df = df.ix[df.code.str[0:3] == '002']
df = df.sort_values('code').reset_index(drop=True)
return df
def bar2h5(market='', date='', freq='D', asset='E', filepath=''):
cons = get_apis()
stks = get_stock_basics()
fname = "%s%s%sbar%s.h5" % (filepath, market, date, freq)
store = pd.HDFStore(fname, "a")
if market in ['SH', 'SZ']:
if market == 'SH':
stks = stks.ix[stks.index.str[0] == '6', :]
elif market == 'SZ':
stks = stks.ix[stks.index.str[0] != '6', :]
else:
stks = ''
market = 1 if market == 'SH' else 0
for stk in stks.index:
symbol = '%s.SH' % stk
if 'min' in freq:
df = bar(stk,
conn=cons,
start_date=date,
end_date=date,
freq=freq,
market=market,
asset=asset)
df['Time'] = df.index
df['Time'] = df['Time'].apply(get_dt_time)
df.index = df['Time']
df.drop(['code', 'Time'], axis=1, inplace=True)
df.rename(columns={'open': 'OPEN'}, inplace=True)
df.rename(columns={'close': 'CLOSE'}, inplace=True)
df.rename(columns={'low': 'LOW'}, inplace=True)
df.rename(columns={'high': 'HIGH'}, inplace=True)
df.rename(columns={'vol': 'VOLUME'}, inplace=True)
df.rename(columns={'amount': 'TURNOVER'}, inplace=True)
df.loc[:, 'HIGH'] = df.loc[:, 'HIGH'].astype("int64")
df.loc[:, 'LOW'] = df.loc[:, 'LOW'].astype("int64")
df.loc[:, 'OPEN'] = df.loc[:, 'OPEN'].astype("int64")
df.loc[:, 'CLOSE'] = df.loc[:, 'CLOSE'].astype("int64")
df.loc[:, 'VOLUME'] = df.loc[:, 'VOLUME'].astype("int64")
df.loc[:, 'TURNOVER'] = df.loc[:, 'TURNOVER'].astype("int64")
df.loc[:, 'OPEN'] *= 10000
df.loc[:, 'CLOSE'] *= 10000
df.loc[:, 'HIGH'] *= 10000
df.loc[:, 'LOW'] *= 10000
df.loc[:, 'ASKPRICE1'] = 0
df.loc[:, 'ASKPRICE2'] = 0
df.loc[:, 'ASKPRICE3'] = 0
df.loc[:, 'ASKPRICE4'] = 0
df.loc[:, 'ASKPRICE5'] = 0
df.loc[:, 'ASKPRICE6'] = 0
df.loc[:, 'ASKPRICE7'] = 0
df.loc[:, 'ASKPRICE8'] = 0
df.loc[:, 'ASKPRICE9'] = 0
df.loc[:, 'ASKPRICE10'] = 0
df.loc[:, 'BIDPRICE1'] = 0
df.loc[:, 'BIDPRICE2'] = 0
df.loc[:, 'BIDPRICE3'] = 0
df.loc[:, 'BIDPRICE4'] = 0
df.loc[:, 'BIDPRICE5'] = 0
df.loc[:, 'BIDPRICE6'] = 0
df.loc[:, 'BIDPRICE7'] = 0
df.loc[:, 'BIDPRICE8'] = 0
df.loc[:, 'BIDPRICE9'] = 0
df.loc[:, 'BIDPRICE10'] = 0
df.loc[:, 'ASKVOL1'] = 0
df.loc[:, 'ASKVOL2'] = 0
df.loc[:, 'ASKVOL3'] = 0
df.loc[:, 'ASKVOL4'] = 0
df.loc[:, 'ASKVOL5'] = 0
df.loc[:, 'ASKVOL6'] = 0
df.loc[:, 'ASKVOL7'] = 0
df.loc[:, 'ASKVOL8'] = 0
df.loc[:, 'ASKVOL9'] = 0
df.loc[:, 'ASKVOL10'] = 0
df.loc[:, 'BIDVOL1'] = 0
df.loc[:, 'BIDVOL2'] = 0
df.loc[:, 'BIDVOL3'] = 0
df.loc[:, 'BIDVOL4'] = 0
df.loc[:, 'BIDVOL5'] = 0
df.loc[:, 'BIDVOL6'] = 0
df.loc[:, 'BIDVOL7'] = 0
df.loc[:, 'BIDVOL8'] = 0
df.loc[:, 'BIDVOL9'] = 0
df.loc[:, 'BIDVOL10'] = 0
df.loc[:, 'VWAP'] = 0.0
df.loc[:, 'VOL30'] = 0.0
df.loc[:, 'TOTAL_VOLUME'] = 0.0
df.loc[:, 'TOTAL_TURNOVER'] = 0.0
df.loc[:, 'INTEREST'] = 0.0
print(df)
# if market == 1 and stk[0] == '6':
# df = bar(stk, conn=cons, start_date=date, end_date=date, freq=freq, market=market, asset=asset)
store[symbol] = df
store.close()
close_apis(cons)