20230907

.idea/encodings.xml

@@ -2,6 +2,11 @@
 <project version="4">
   <component name="Encoding">
     <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/202201-202307月-10日未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B小于1600w炸板率.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/2022未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/2022未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B炸板率.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/2023未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B(振幅).csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/2023未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B-1.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/2023未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B炸板率.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/10日未涨停回封/2023-1-7月-10日未涨停首笔大单大于700w-b1-8%type第一个为B(小于1600W).csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/10日未涨停回封/2023-1-7月-10日未涨停首笔大单大于700w-b1-8%type第一个为B.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/10日未涨停回封/2023-1-7月-10日未涨停首笔大单大于700w-b1-8%type第一个为B炸板率.csv" charset="GBK" />
@@ -10,20 +15,35 @@
     <file url="file://$PROJECT_DIR$/10日未涨停回封/2023-1-7月10未涨停回封板首笔大单大于500w-b1-8%type第一个为B.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/10日未涨停回封/低价股/2022-10日未涨停(000)股本低价股首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/10日未涨停回封/低价股/2022-10日未涨停(000)股本低价股首笔大单大于700w-b1-8%type第一个为B炸板率.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/10日未涨停回封/低价股/2022-10日未涨停(000)股本低价股首笔大单大于9900手-b1-8%type第一个为B炸板率(振幅).csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/10日未涨停回封/低价股/2022-10日未涨停(000)股本低价股首笔大单大于9900手-b1-8%type第一个为B炸板率.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/10日未涨停回封/低价股/2023-1-7月-10日未涨停低价股大于9900手-b1-8%type第一个为B.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/10日未涨停回封/低价股/2023-1-7月-10日未涨停低价股大于9900手-b1-8%type第一个为B炸板率(振幅).csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/10日未涨停回封/流通股本/A股列表.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/10日未涨停回封/股本/2023-1-7月-10日未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B炸板率.csv" charset="GBK" />
-    <file url="file://$PROJECT_DIR$/2023-08-14-000.csv" charset="GBK" />
-    <file url="file://$PROJECT_DIR$/2023-08-23-000.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/2023-08-25-000.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/2023-08-25炸板率.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/2023-08-29-000-7.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/2023-09-01炸板率.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/2023-09-04-000.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/2023-09-04-600.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/2023-09-07炸板率.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/2板新高/2023-000-45日未涨停2板.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/300-600/300-600.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/300/2022-10日未涨停(300)首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/300/2022-10日未涨停(300)首笔大单大于700w-b1-8%type第一个为B炸板率.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/300/2022涨停(300)首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/300/2023-1-7月-10日未涨停(300)首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/300/2023涨停(300)股本首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/300/2023涨停(300)股本首笔大单大于700w-b1-8%type第一个为B炸板率.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/45日首板触板小于2次/2023-1-7月-45日未涨停.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/45日首板触板小于2次/2023-1-7月-45日未涨停1.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/45日首板触板小于2次/2023-1-7月-45日未涨停首笔大单大于700w-b1-8%type第一个为B.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/600打板/2022涨停(600)股本首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/600打板/2023-1-7月-10日未涨停600首笔大单大于700w-b1-8%type第一个为B-1.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/600打板/2023-1-7月-10日未涨停600首笔大单大于700w-b1-8%type第一个为B.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/600打板/2023未涨停(600)股本.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/600打板/2023涨停(600)股本首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/N字反包/2022/2022反包7距板收盘价跌幅大于5%首笔大单大于700w-b1-8%type第一个为B.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/N字反包/2022/2022反包7距板收盘价跌幅大于5%首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/N字反包/2022/2022反包7距板收盘价跌幅大于5%首笔大单大于700w-b1-8%type第一个为B炸板率.csv" charset="GBK" />
@@ -92,5 +112,7 @@
     <file url="file://$PROJECT_DIR$/集合竞价数据/2023-08-08炸板率.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/集合竞价数据/2023-08-11炸板率.csv" charset="GBK" />
     <file url="file://$PROJECT_DIR$/集合竞价数据/2023-08-13-000-7.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/集合竞价数据/2023-08-14-000.csv" charset="GBK" />
+    <file url="file://$PROJECT_DIR$/集合竞价数据/2023-08-23-000.csv" charset="GBK" />
   </component>
 </project>
\ No newline at end of file

000黑名单.csv

@@ -7,3 +7,6 @@ SZ002406
 SZ002712
 SZ002945
 SH600152
+SZ002902
+SZ002009
+SZ000666

10日未涨停回封/2022-202307/700大单.py

+import csv
+import math
+import os
+import time
+
+import numpy as np
+import pandas as pd
+root='/Volumes/Elements SE/逐笔202301-03/'
+
+
+data=pd.read_csv('./2023未涨停(000)股本.csv',encoding='gbk')
+data['日期']=pd.to_datetime(data['日期'])
+data = data.groupby('日期')
+
+name = pd.read_excel('/Users/yumingwu/Desktop/沪深A股.xlsx')
+with open('./2023未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B-1'+'.csv','w',encoding='gbk',newline='') as csfile:
+    writer =csv.writer(csfile)
+    writer.writerow(['代码','名称','日期', '昨日收盘价','开盘价','最低价','最高价涨幅','成交量','成交额','换手率','买入价格','卖出价格','盈利','涨幅','流通市值','涨停trainID','涨停BuyOrderID','涨停vol','涨停amount','大单ID','时间'])
+    for day,dataR in data:
+
+        print(day)
+        if(day>=pd.to_datetime('2023-07-19')):
+            continue
+        daystr= day.strftime("%Y-%m-%d")
+
+        for index,item in dataR.iterrows():
+
+            # if item['代码']!='SZ002851':
+            #     continue
+            if os.path.exists(root + daystr + '/' + item['代码'][2:8] + '.csv') == False:
+                print(root + daystr + '/' + item['代码'][2:8] + '.csv')
+                continue
+
+            zhubiData= pd.read_csv(root+daystr+'/'+item['代码'][2:8]+'.csv')
+            zhubiData=zhubiData[zhubiData['Time']>'09:25:00']
+            zhubiData['amount']=zhubiData['Volume']*zhubiData['BuyOrderPrice']
+            zhangtingjia=zhubiData['BuyOrderPrice'].max()
+            maxPrice= zhubiData['Price'].max()
+            maxPriceItem = zhubiData[zhubiData['Price']>=maxPrice]
+            maxPriceItem=maxPriceItem.iloc[0]
+
+            zhangtingdata = zhubiData[zhubiData['BuyOrderID']==maxPriceItem['BuyOrderID']]
+
+            # stockNum = 7000000 / (zhangtingjia-0.01)
+            # zhubiData = zhubiData[zhubiData['BuyOrderVolume'] > stockNum]
+
+            zhangtingjiaData=zhubiData[zhubiData['BuyOrderPrice']>=zhangtingjia-0.01]
+            zhangtingjiaData=zhangtingjiaData.groupby('BuyOrderID')
+            zhangtingjiaData1=pd.DataFrame()
+            for id, zhangtingjiaDataItem in zhangtingjiaData:
+                amount = zhangtingjiaDataItem['amount'].sum()
+                if(amount<7000000):
+                    continue
+                p0 = zhangtingjiaDataItem.iloc[0]
+                TranID = p0['TranID']
+                zhangtingjiaDataItem['ID']=TranID
+                zhangtingjiaData1=zhangtingjiaData1.append(zhangtingjiaDataItem)
+            if len(zhangtingjiaData1)==0:
+                continue
+
+            zhangtingjiaData =zhangtingjiaData1.groupby('ID')
+            for id ,zhangtingjiaDataItem in zhangtingjiaData:
+                amount = zhangtingjiaDataItem['amount'].sum()
+                p0=zhangtingjiaDataItem.iloc[0]
+
+                type = p0['Type']
+                time1 =p0['Time']
+                # zhangtingjiaDataItemS = zhangtingjiaDataItem[zhangtingjiaDataItem['Type']=='S']
+                # zhangtingjiaDataItemSLength = len(zhangtingjiaDataItemS)
+                # p0 = zhangtingjiaDataItem.iloc[-1]
+                p0=p0['Price']
+
+                num = math.floor(2000000 / item['买入价格'] / 100) * 100
+                codename = item['代码'][2:8]+"."+item['代码'][0:2]
+
+                codename = name[name['股票代码']==codename]
+                codename =codename.iloc[0]
+                if (amount >= 7000000 and p0/item['昨日收盘价']>1.08 and type == 'B'):
+                    writer.writerow(
+                        [item['代码'],
+                         codename['股票简称'],
+                         item['日期'],
+                         item['昨日收盘价'],
+                         item['开盘价'],
+                         item['最低价'],
+                         item['最高价涨幅'],
+                         item['成交量'],
+                         item['成交额'],
+                         item['换手率'],
+                         item['买入价格'],
+                         item['卖出价格'],
+                         num * (item['卖出价格'] - item['买入价格']) - item['买入价格'] * num * 0.0002 - item[
+                             '卖出价格'] * num * 0.0012,
+
+                         item['涨幅'],
+                         item['流通市值'],
+                         maxPriceItem['TranID'],
+                         maxPriceItem['BuyOrderID'],
+                         zhangtingdata['Volume'].sum(),
+                         amount,
+                         id,
+
+                        time1,
+
+
+                         ])
+                    break
+
+
+
+
+

10日未涨停回封/2022-202307/main涨停-0.py

+import csv
+import math
+import os
+import time
+
+import numpy as np
+import pandas as pd
+root='/Users/yumingwu/Downloads/Stk_Day_QFQ/'
+path =os.listdir(root)
+path.sort()
+
+
+
+guben1 = pd.read_csv('../../600打板/流通股本.csv',encoding='utf-8')
+guben1['变更日期']=pd.to_datetime(guben1['变更日期'])
+with open('./2023未涨停(000)股本'+'.csv','w',encoding='gbk',newline='') as csfile:
+    writer =csv.writer(csfile)
+    writer.writerow(['代码','日期','昨日收盘价','开盘价','最低价','最高价涨幅','成交量','成交额','换手率','买入价格','卖出价格','盈利','涨幅','10日涨幅','流通市值'])
+
+    for spath in path:
+        # 过滤000
+        if spath.find("SZ0") == -1:
+            continue
+
+        print(spath)
+        dataS = pd.read_csv(root + spath, encoding='gbk')
+        dataS['时间'] = pd.to_datetime(dataS['时间'])
+        data1=dataS[dataS['时间']>=pd.to_datetime('20230101')]
+        # data1 = data1[data1['时间'] < pd.to_datetime('20230101')]
+        code = spath[2:8] + "." + spath[0:2]
+
+        guben = guben1[guben1['代码']==code]
+        guben =guben.sort_values('变更日期',ascending=False)
+        for indexitemn in np.arange(len(data1)):
+            if indexitemn==len(data1)-1:
+                continue
+            itemn=data1.iloc[indexitemn]
+
+            itemn1 = data1.iloc[indexitemn+1]
+            data=dataS[dataS['时间']<itemn['时间']]
+
+
+            if len(data)<5:
+                continue
+            item = data.iloc[-1]
+
+            if itemn['最高价'] / item['收盘价'] <= 1.08:
+                continue
+            zhangting = 0
+
+
+            if zhangting == 0:
+
+
+                data10 = data.iloc[len(data) - 10 - 1:len(data)]
+                minprice = data10['开盘价'].min()
+                zhangfu = item['收盘价'] / minprice
+                # if zhangfu >= 1.15:
+                #     continue
+
+
+                gubenitem = guben.iloc[0]
+                gubenitem1 = guben[guben['变更日期']<=item['时间']]
+                if len(gubenitem1)==0:
+                    gubenitem1 = guben.iloc[-1]
+                else:
+                    gubenitem1=gubenitem1.iloc[0]
+
+
+                huanshou=item['成交量(股)'] / gubenitem1['流通A股']
+
+
+                shizhi = gubenitem['流通A股'] * item['收盘价'] / 100000000.0
+                # if shizhi > 200:
+                #     continue
+                num1 = math.floor(2000000 / itemn['最高价'] / 100) * 100
+                writer.writerow([itemn['代码'],
+                                 itemn['时间'],
+                                 item['收盘价'],
+                                 itemn['开盘价'],
+                                 itemn['最低价'],
+                                 itemn['最高价']/item['收盘价']-1,
+                                 item['成交量(股)'],
+                                 item['成交额(元)'],
+                                 huanshou,
+                                 itemn['最高价'],
+                                 itemn1['开盘价'],
+                                 num1 * (itemn1['开盘价'] -itemn['最高价']) - itemn['最高价'] * num1 * 0.0002 -
+                                 itemn1['开盘价'] * num1 * 0.0012,
+                                 itemn1['开盘价'] / itemn['最高价']-1-0.0014,
+                                 zhangfu,
+                                 shizhi,
+
+                                 ])
+

10日未涨停回封/2022-202307/炸板率.py → 10日未涨停回封/2022-202307/反包.py

@@ -7,76 +7,51 @@ import numpy as np
 import pandas as pd
 root='/Users/yumingwu/Downloads/Stk_Day_QFQ/'
 path =os.listdir(root)
-data1 = pd.read_csv('./2022-1-6月-10日未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B小于1600w炸板率.csv',encoding='gbk')
-data2 = pd.read_csv('./2022-7-12月-10日未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B小于1600w炸板率.csv',encoding='gbk')
 
-data = pd.read_csv('../股本/2023-1-7月-10日未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B小于1600w炸板率.csv',encoding='gbk')
+data = pd.read_csv('./2022未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv',encoding='utf-8')
 
-file000 = open('./202201-202307月-10日未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B小于1600w炸板率.csv','w',encoding='gbk',newline='')
+file000 = open('./2022未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B炸板率(振幅)反包10.csv','w',encoding='gbk',newline='')
 writer000 = csv.writer(file000)
 writer000.writerow(
     ['代码', '名称', '日期', '昨日收盘价', '开盘价', '最低价', '最高价涨幅', '成交量', '成交额', '换手率', '买入价格',
      '卖出价格', '盈利', '涨幅', '流通市值', '涨停trainID', '涨停BuyOrderID', '涨停vol', '涨停amount','大单ID',
-     '时间','炸板率','涨停次数','炸板次数','炸板幅度','第二天溢价率'])
-for index,item in data1.iterrows():
-    writer000.writerow(
-        [item['代码'],
-         item['名称'],
-         item['日期'],
-         item['昨日收盘价'],
-         item['开盘价'],
-         item['最低价'],
-         item['最高价涨幅'],
-         item['成交量'],
-         item['成交额'],
-         item['换手率'],
-         item['买入价格'],
-         item['卖出价格'],
-         item['盈利'],
-         item['涨幅'],
-         item['流通市值'],
-         item['涨停trainID'],
-         item['涨停BuyOrderID'],
-         item['涨停vol'],
-         item['涨停amount'],
-         item['大单ID'],
-         item['时间'],
-         item['炸板率'],
-         item['涨停次数'],
-         item['炸板次数'],
-         item['炸板幅度'],
-         item['第二天溢价率']
-         ])
-for index,item in data2.iterrows():
-    writer000.writerow(
-        [item['代码'],
-         item['名称'],
-         item['日期'],
-         item['昨日收盘价'],
-         item['开盘价'],
-         item['最低价'],
-         item['最高价涨幅'],
-         item['成交量'],
-         item['成交额'],
-         item['换手率'],
-         item['买入价格'],
-         item['卖出价格'],
-         item['盈利'],
-         item['涨幅'],
-         item['流通市值'],
-         item['涨停trainID'],
-         item['涨停BuyOrderID'],
-         item['涨停vol'],
-         item['涨停amount'],
-         item['大单ID'],
-         item['时间'],
-         item['炸板率'],
-         item['涨停次数'],
-         item['炸板次数'],
-         item['炸板幅度'],
-         item['第二天溢价率']
-         ])
+     '时间','炸板率','涨停次数','炸板次数','炸板幅度','第二天溢价率','振幅','昨日振幅','昨日跌幅','10日涨幅','十日是否有涨停','十日最高价跌幅','十日涨停价跌幅'])
 for index,item in data.iterrows():
+    day = item['日期']
+    day =pd.to_datetime(day)
+    code= item['代码']+'.csv'
+
+    codeData=pd.read_csv(root+code,encoding='gbk')
+    codeData['时间'] = pd.to_datetime(codeData['时间'])
+    codeData =codeData[codeData['时间']<day]
+    codeData0=codeData.iloc[-1]
+    codeData1 = codeData.iloc[-2]
+    if len(codeData)<10:
+        continue
+    codeData=codeData[len(codeData)-10:len(codeData)]
+    codeData7 = codeData[len(codeData) - 7:len(codeData)]
+    min = codeData0['收盘价']/(codeData['最低价'].min())-1
+    max = codeData0['收盘价']/(codeData['最高价'].max())-1
+    data =codeData7
+    zhangtingItem=0
+    zhangting=0
+    for i in np.arange(len(data)):
+        if i > 0:
+            item0 = data.iloc[i - 1]
+            item1 = data.iloc[i]
+
+            if item1['收盘价'] / item0['收盘价'] > 1.08:
+                n = len(data) - i + 1
+                zhangting = zhangting + 1
+                zhangtingItem = item1
+
+        # if flag:
+        #     continue
+    zhangtingFlag=0
+    zhangtingrate = -1
+    if zhangting >0:
+        zhangtingFlag=1
+        zhangtingrate=codeData0['收盘价'] / zhangtingItem['最高价']- 1
     writer000.writerow(
         [item['代码'],
          item['名称'],
@@ -103,5 +78,13 @@ for index,item in data.iterrows():
          item['涨停次数'],
          item['炸板次数'],
          item['炸板幅度'],
-         item['第二天溢价率']
+         item['第二天溢价率'],
+         (codeData0['最高价']-codeData0['最低价'])/codeData1['收盘价'],
+         (codeData0['最高价'] - codeData0['最低价']) / codeData0['收盘价'],
+         codeData0['收盘价']/codeData1['收盘价']-1,
+         min,
+         zhangtingFlag,
+         max,
+         zhangtingrate
+
          ])

10日未涨停回封/2022-202307/振幅.py

@@ -8,9 +8,9 @@ import pandas as pd
 root='/Users/yumingwu/Downloads/Stk_Day_QFQ/'
 path =os.listdir(root)
 
-data = pd.read_csv('./202201-202307月-10日未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B炸板率.csv',encoding='utf-8')
+data = pd.read_csv('./2023未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B炸板率.csv',encoding='gbk')
 
-file000 = open('./202201-202307月-10日未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv','w',encoding='gbk',newline='')
+file000 = open('./2023未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B(振幅).csv','w',encoding='gbk',newline='')
 writer000 = csv.writer(file000)
 writer000.writerow(
     ['代码', '名称', '日期', '昨日收盘价', '开盘价', '最低价', '最高价涨幅', '成交量', '成交额', '换手率', '买入价格',

10日未涨停回封/2022-202307/炸板率1.py

+import csv
+import os
+import time
+from _decimal import Decimal
+
+import numpy as np
+import pandas as pd
+root='/Users/yumingwu/Downloads/Stk_Day_QFQ/'
+path =os.listdir(root)
+
+data = pd.read_csv('./2023未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B-1.csv',encoding='gbk')
+
+file000 = open('./2023未涨停(000)股本首笔大单大于700w-b1-8%type第一个为B炸板率.csv','w',encoding='gbk',newline='')
+writer000 = csv.writer(file000)
+writer000.writerow(
+    ['代码', '名称', '日期', '昨日收盘价', '开盘价', '最低价', '最高价涨幅', '成交量', '成交额', '换手率', '买入价格',
+     '卖出价格', '盈利', '涨幅', '流通市值', '涨停trainID', '涨停BuyOrderID', '涨停vol', '涨停amount', '大单ID',
+     '时间','炸板率','涨停次数','炸板次数','炸板幅度','第二天溢价率'])
+for index,item in data.iterrows():
+    day = item['日期']
+    day =pd.to_datetime(day)
+    code= item['代码']+'.csv'
+
+    codeData=pd.read_csv(root+code,encoding='gbk')
+    codeData['时间'] = pd.to_datetime(codeData['时间'])
+    codeData =codeData[codeData['时间']<day]
+    day1=day-pd.offsets.DateOffset(years=1)
+    codeData = codeData[codeData['时间'] >= day1]
+
+
+    zhangtingTime=0
+    zhaBanTime=0
+    zhaBanTimefudu=0
+    zhangtingyijia=0
+    for i in np.arange(len(codeData)):
+        if i==0:
+            continue
+        if i==len(codeData)-1:
+            continue
+        item0 = codeData.iloc[i-1]
+        item1 = codeData.iloc[i]
+        item2 = codeData.iloc[i+1]
+        if item1['最高价']/item0['收盘价']>1.098:
+            if item1['最高价']==item1['收盘价']:
+                zhangtingTime=zhangtingTime+1
+                zhangtingyijia=zhangtingyijia+item2['开盘价']/item1['最高价']-1.0014
+            else:
+                zhaBanTime=zhaBanTime+1
+                zhaBanTimefudu=zhaBanTimefudu+(item1['收盘价']/item1['最高价']-1)
+
+    rate =0
+    if zhangtingTime>0 or zhaBanTime>0:
+        rate = zhaBanTime/(zhangtingTime+zhaBanTime)
+
+
+    if zhaBanTime!=0:
+        zhaBanTimefudu=zhaBanTimefudu/zhaBanTime
+    if zhangtingTime!=0:
+        zhangtingyijia=zhangtingyijia/zhangtingTime
+
+    writer000.writerow(
+        [item['代码'],
+         item['名称'],
+         item['日期'],
+         item['昨日收盘价'],
+         item['开盘价'],
+         item['最低价'],
+         item['最高价涨幅'],
+         item['成交量'],
+         item['成交额'],
+         item['换手率'],
+         item['买入价格'],
+         item['卖出价格'],
+         item['盈利'],
+         item['涨幅'],
+         item['流通市值'],
+         item['涨停trainID'],
+         item['涨停BuyOrderID'],
+         item['涨停vol'],
+         item['涨停amount'],
+         item['大单ID'],
+         item['时间'],
+         rate,
+         zhangtingTime,
+         zhaBanTime,
+         zhaBanTimefudu,
+         zhangtingyijia
+         ])

10日未涨停回封/2022-202307/炸板率前3.py

@@ -22,8 +22,8 @@ data = data[data['流通市值']<200]
 data = data[data['振幅']<0.045]
 # data = data[data['涨停amount']<19000000]
 data = data[data['炸板次数']>0]
-
-data = data[data['10日涨幅']<0.2]
+data = data[data['开盘涨幅']<1.05]
+# data = data[data['10日涨幅']<0.2]
 # data = data[data['10日涨幅']>0.02]
 # data=data[data['流通市值']<200]
 
@@ -46,6 +46,8 @@ with open('./202201-202307月-10日未涨停(000)股本首笔大单大于700w-b1
         for index ,item in dataR.iterrows():
             if item['涨停次数']==1 and item['炸板次数']==1 and item['第二天溢价率']<-0.0014:
                 continue
+            if item['涨停次数']>1 and item['第二天溢价率']<0:
+                continue
             writer.writerow(
                 [item['代码'],
                  item['名称'],

10日未涨停回封/低价股/振幅.py

@@ -8,9 +8,9 @@ import pandas as pd
 root='/Users/yumingwu/Downloads/Stk_Day_QFQ/'
 path =os.listdir(root)
 
-data = pd.read_csv('./2022-10日未涨停(000)股本低价股首笔大单大于700w-b1-8%type第一个为B炸板率.csv',encoding='gbk')
+data = pd.read_csv('./2023-1-7月-10日未涨停低价股大于9900手-b1-8%type第一个为B炸板率.csv',encoding='gbk')
 
-file000 = open('./2022-10日未涨停(000)股本低价股首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv','w',encoding='gbk',newline='')
+file000 = open('./2023-1-7月-10日未涨停低价股大于9900手-b1-8%type第一个为B炸板率(振幅).csv','w',encoding='gbk',newline='')
 writer000 = csv.writer(file000)
 writer000.writerow(
     ['代码', '名称', '日期', '昨日收盘价', '开盘价', '最低价', '最高价涨幅', '成交量', '成交额', '换手率', '买入价格',

10日未涨停回封/低价股/炸板率.py

@@ -8,13 +8,13 @@ import pandas as pd
 root='/Users/yumingwu/Downloads/Stk_Day_QFQ/'
 path =os.listdir(root)
 
-data = pd.read_csv('./2022-10日未涨停(000)股本低价股首笔大单大于700w-b1-8%type第一个为B炸板率.csv',encoding='gbk')
+data = pd.read_csv('./2023-1-7月-10日未涨停低价股大于9900手-b1-8%type第一个为B.csv',encoding='gbk')
 
-file000 = open('./2023-1-7月-10日未涨停2单大于700w-b1-8%type第一个为B炸板率.csv','w',encoding='gbk',newline='')
+file000 = open('./2023-1-7月-10日未涨停低价股大于9900手-b1-8%type第一个为B炸板率.csv','w',encoding='gbk',newline='')
 writer000 = csv.writer(file000)
 writer000.writerow(
     ['代码', '名称', '日期', '昨日收盘价', '开盘价', '最低价', '最高价涨幅', '成交量', '成交额', '换手率', '买入价格',
-     '卖出价格', '盈利', '涨幅', '流通市值', '涨停trainID', '涨停BuyOrderID', '涨停vol', '涨停amount',
+     '卖出价格', '盈利', '涨幅', '流通市值', '涨停trainID', '涨停BuyOrderID', '涨停vol', '涨停Volume','大单ID',
      '时间','炸板率','涨停次数','炸板次数','炸板幅度','第二天溢价率'])
 for index,item in data.iterrows():
     day = item['日期']
@@ -77,7 +77,8 @@ for index,item in data.iterrows():
          item['涨停trainID'],
          item['涨停BuyOrderID'],
          item['涨停vol'],
-         item['涨停amount'],
+         item['涨停Volume'],
+         item['大单ID'],
          item['时间'],
          rate,
          zhangtingTime,

300/振幅.py

@@ -8,9 +8,9 @@ import pandas as pd
 root='/Users/yumingwu/Downloads/Stk_Day_QFQ/'
 path =os.listdir(root)
 
-data = pd.read_csv('./2023-1-7月-10日未涨停(300)首笔大单大于700w-b1-8%type第一个为B炸板率.csv',encoding='gbk')
+data = pd.read_csv('./2023涨停(300)股本首笔大单大于700w-b1-8%type第一个为B炸板率.csv',encoding='gbk')
 
-file000 = open('./2023-1-7月-10日未涨停(300)首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv','w',encoding='gbk',newline='')
+file000 = open('./2023涨停(300)股本首笔大单大于700w-b1-8%type第一个为B炸板率(振幅).csv','w',encoding='gbk',newline='')
 writer000 = csv.writer(file000)
 writer000.writerow(
     ['代码', '名称', '日期', '昨日收盘价', '开盘价', '最低价', '最高价涨幅', '成交量', '成交额', '换手率', '买入价格',
@@ -26,6 +26,10 @@ for index,item in data.iterrows():
     codeData =codeData[codeData['时间']<day]
     codeData0=codeData.iloc[-1]
     codeData1 = codeData.iloc[-2]
+    if len(codeData)<10:
+        continue
+
+
     codeData=codeData[len(codeData)-10:len(codeData)]
     min = codeData0['收盘价']/(codeData['最低价'].min())-1
     writer000.writerow(

财报/main.py

+# https://datacenter-web.eastmoney.com/api/data/v1/get?callback=jQuery11230983850769812807_1693456017259&sortColumns=UPDATE_DATE%2CSECURITY_CODE&sortTypes=-1%2C-1&pageSize=50&pageNumber=1&reportName=RPT_LICO_FN_CPD&columns=ALL&filter=(REPORTDATE%3D%272023-06-30%27)
+
+import requests
+url = 'https://datacenter-web.eastmoney.com/api/data/v1/get?callback=jQuery11230983850769812807_1693456017259&sortColumns=UPDATE_DATE%2CSECURITY_CODE&sortTypes=-1%2C-1&pageSize=50&pageNumber=1&reportName=RPT_LICO_FN_CPD&columns=ALL&filter=(REPORTDATE%3D%272023-06-30%27)'
+
+r = requests.get(url)
+#print(r.text)
+print(r.content)
\ No newline at end of file