一些更正的东西

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#是否长上影，绝对长度和相对长度都有要求
df1['K_l_up_flag'] = np.where((df1['shiti_up']>50) & (df1['shiti_up_len']>3),1,0)
#是否长下影
df1['K_l_low_flag'] = np.where((df1['shiti_low']>50) & (df1['shiti_low_len']>3),1,0)
#是否上下影都长
df1['K_l_lu_flag'] = np.where((df1['shiti_low']>35) & (df1['shiti_up']>35) & (df1['zhenfu']>5) ,1,0)

#长上影和长下影的十字星，是否上线都长的十字星
df1['K_shizi_l_up'] = np.where((df1['K_bianxian_flag']==1) &  (df1['K_l_up_flag']==1),1,0)
df1['K_shizi_l_low'] = np.where((df1['K_bianxian_flag']==1) &  (df1['K_l_low_flag']==1),1,0)
df1['K_shizi_l_low'] = np.where((df1['K_bianxian_flag']==1) &  (df1['K_l_lu_flag']==1),1,0)

df1['panping'] = np.where((df1['pan_nei_14count']>9) & (df1['d21_d0_count']<10)  & (df1['d21_d0_count']>1 & (abs(df1['ma21xielv'])<0.12)) ,1,0)

#长箱体突破
df['xttp'] = np.where((df1['panping']==1) & (df1['close']>df1['c_up_12per'])  & (df1['close']>df1['close'].shift(2)) & (df1['close']>df1['close'].shift(3),1,0)
 

#盘升，后一日比前一日的收盘价高，15个里面有多个这样的，且最后一日的比较高，14日的斜率为正，比10个以上都高，盘跌类似
#中间无大跌，无大涨，不超过1次
df1['hdq_flag'] = np.where(df1['high']>df1['high'].shift(1),1,0)
df1['qdh_flag'] = np.where(df1['low']<df1['low'].shift(1),1,0)
df1['hdq_flag_count15'] =  ta.SUM(df1['hdq_flag'], timeperiod=15)
df1['qdh_flag_count15'] =  ta.SUM(df1['qdh_flag'], timeperiod=15)
df1['pansheng_flag'] = np.where((df1['hdq_flag_count15']>9) & (df1['d21_d0_count']>9) & (df1['close']>df1['close'].shift(14)) ,1,0)
df1['pandie_flag'] = np.where((df1['qdh_flag_count15']>9) & (df1['d21_d0_count']<5) & (df1['close']<df1['close'].shift(14)) ,1,0)

#df1 = df1.drop(['c_up_12per',],axis=1)