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Commit ae4ccb9b authored by wuyuming's avatar wuyuming
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20231023

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.idea/encodings.xml
View file @ ae4ccb9b
...@@ -19,9 +19,15 @@ ...@@ -19,9 +19,15 @@
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/2023涨停(000)股本N连单10%大于700w.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/2023涨停(000)股本N连单10%大于700w.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/2023涨停(000)股本N连单大于700w.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/2023涨停(000)股本N连单大于700w.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/300/2022-2023涨停(300)股本N连单大于700w.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/300/2022-2023涨停(300)股本N连单大于700w.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/300/2022-2023涨停(300)股本N连单大于700w振幅.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/300/2023涨停(000)股本N连单大于700w.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/300/2023涨停(000)股本N连单大于700w.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/600/2022涨停(600)股本N连单大于700w.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/600/2023涨停(600)股本N连单大于700w.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/688/2022-2023涨停(688)股本N连单大于700w.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/688/2022-2023涨停(688)股本N连单大于700w.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/688/2023涨停(688)股本N连单大于700w.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/688/2023涨停(688)股本N连单大于700w.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/数据修复/2022-2023涨停(000)股本N连单10%大于700w炸板率.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/数据修复/2022-2023涨停(000)股本N连单大于700w市值.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/数据修复/2022-2023涨停(000)股本N连单大于700w振幅.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/数据修复/2022涨停(000)股本N连单10%大于700w.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/数据修复/2022涨停(000)股本N连单10%大于700w.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/数据修复/2022涨停(000)股本N连单大于700w.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/10日未涨停回封/2022-202307/不复权/数据修复/2022涨停(000)股本N连单大于700w.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(小于1600W).csv" charset="GBK" />
...@@ -131,14 +137,9 @@ ...@@ -131,14 +137,9 @@
<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/2023-08-14-000.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/集合竞价数据/2023-08-23-000.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/集合竞价数据/2023-08-23-000.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-04-000.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-04-000.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-04-000.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-04-600.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-04-600.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-04-600.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-07炸板率.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-07炸板率.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-07炸板率.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-13炸板率.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-13炸板率.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-13炸板率.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-14炸板率.csv" charset="GBK" />
<file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-14炸板率.csv" charset="GBK" /> <file url="file://$PROJECT_DIR$/集合竞价数据/2023-09-14炸板率.csv" charset="GBK" />
</component> </component>
</project> </project>
\ No newline at end of file
10日未涨停回封/2022-202307/不复权/2023涨停(000)股本N连单b1-7%大于700w.csv 0 → 100644
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10日未涨停回封/2022-202307/不复权/300/2022-2023涨停(300)股本N连单大于700w市值.csv 0 → 100644
View file @ ae4ccb9b
This source diff could not be displayed because it is too large. You can view the blob instead.
10日未涨停回封/2022-202307/不复权/300/市值修复.py 0 → 100644
View file @ ae4ccb9b
import csv
import math
import os
import time
import numpy as np
import pandas as pd
root='/Users/yumingwu/Downloads/Stk_Day/'
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'])
data = pd.read_csv('./2022-2023涨停(300)股本N连单大于700w.csv',encoding='gbk')
data['日期']=pd.to_datetime(data['日期'])
with open('./2022-2023涨停(300)股本N连单大于700w市值'+'.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','昨日是否涨停','盈利','涨幅','流通市值','跟单明细','连单笔数','总金额','时间'])
for index,item in data.iterrows():
dataS = pd.read_csv(root + item['代码']+'.csv', encoding='gbk')
dataS['时间'] = pd.to_datetime(dataS['时间'])
data1 = dataS[dataS['时间'] < item['日期']]
item2 = data1.iloc[-1]
item3 = data1.iloc[-2]
code = item['代码'][2:8] + "." + item['代码'][0:2]
guben = guben1[guben1['代码'] == code]
guben = guben.sort_values('变更日期', ascending=False)
gubenitem1 = guben[guben['变更日期'] <= item['日期']]
if len(gubenitem1) == 0:
gubenitem1 = guben.iloc[-1]
else:
gubenitem1 = gubenitem1.iloc[0]
huanshou = item2['成交量(股)'] / gubenitem1['流通A股']
shizhi = gubenitem1['流通A股'] * item2['收盘价'] / 100000000.0
zhangting =0;
if item2['收盘价']/item3['收盘价']>1.198:
zhangting=1
writer.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'],
zhangting,
item['盈利'],
item['涨幅'],
shizhi,
item['跟单明细'],
item['连单笔数'],
item['总金额'],
item['时间']
])
10日未涨停回封/2022-202307/不复权/300/炸板率.py
View file @ ae4ccb9b
...@@ -8,7 +8,7 @@ import pandas as pd ...@@ -8,7 +8,7 @@ import pandas as pd
root='/Users/yumingwu/Downloads/Stk_Day_QFQ/' root='/Users/yumingwu/Downloads/Stk_Day_QFQ/'
path =os.listdir(root) path =os.listdir(root)
data = pd.read_csv('./2022-2023涨停(300)股本N连单大于700w.csv',encoding='gbk') data = pd.read_csv('./2022-2023涨停(300)股本N连单大于700w市值.csv',encoding='gbk')
file000 = open('./2022-2023涨停(300)股本N连单大于700w炸板率.csv','w',encoding='gbk',newline='') file000 = open('./2022-2023涨停(300)股本N连单大于700w炸板率.csv','w',encoding='gbk',newline='')
writer000 = csv.writer(file000) writer000 = csv.writer(file000)
...@@ -116,7 +116,7 @@ for index,item in data.iterrows(): ...@@ -116,7 +116,7 @@ for index,item in data.iterrows():
arr3 = arr3[len(arr3)-3:len(arr3)] arr3 = arr3[len(arr3)-3:len(arr3)]
rate3 = (arr3[0]+arr3[1]+arr3[2])/3 rate3 = (arr3[0]+arr3[1]+arr3[2])/3
zhangting = 0;
...@@ -134,7 +134,7 @@ for index,item in data.iterrows(): ...@@ -134,7 +134,7 @@ for index,item in data.iterrows():
item['换手率'], item['换手率'],
item['买入价格'], item['买入价格'],
item['卖出价格'], item['卖出价格'],
zhangting, item['昨日是否涨停'],
item['盈利'], item['盈利'],
item['涨幅'], item['涨幅'],
item['流通市值'], item['流通市值'],
......
10日未涨停回封/2022-202307/不复权/600/2023涨停(600)股本N连单大于700w.csv 0 → 100644
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This source diff could not be displayed because it is too large. You can view the blob instead.
10日未涨停回封/2022-202307/不复权/600/700wN连大单.py 0 → 100644
View file @ ae4ccb9b
import csv
import math
import os
import time
import numpy as np
import pandas as pd
root='/Volumes/Elements SE/逐笔202301-03/'
import datetime
data=pd.read_csv('./2022-2023涨停(600)股本.csv',encoding='gbk')
data['日期']=pd.to_datetime(data['日期'])
data = data.groupby('日期')
percent=0.01
name = pd.read_excel('/Users/yumingwu/Desktop/沪深A股.xlsx')
with open('./2023涨停(600)股本N连单10%大于700w'+'.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','跟单明细','连单笔数','总金额','时间'])
for day,dataR in data:
print(day)
if(day<pd.to_datetime('2023-01-01')):
continue
daystr= day.strftime("%Y-%m-%d")
for index,item in dataR.iterrows():
current_time = datetime.datetime.now()
print(item['代码'])
print("现在时间是: " + str(current_time))
# 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['Price']>=item['昨日收盘价']*1.09]
zhangtingjiaData = zhubiData[zhubiData['BuyOrderPrice'] >= zhangtingjia-0.03]
zhangtingjiaData=zhangtingjiaData[zhangtingjiaData['Type']=='B']
zhangtingjiaData=zhangtingjiaData.groupby('BuyOrderID')
zhangtingjiaData1=pd.DataFrame()
dicARR = {}
keyArr = []
for id, zhangtingjiaDataItem in zhangtingjiaData:
zhangtingjiaDataItem1 =zhubiData[zhubiData['BuyOrderID']==id].copy()
zhangtingjiaDataItem1 = zhangtingjiaDataItem1[zhangtingjiaDataItem1['BuyOrderPrice'] >= zhangtingjia-0.03]
amount = zhangtingjiaDataItem1['amount'].sum()
if amount<1000000:
continue
vol = zhangtingjiaDataItem1['Volume'].sum()
p0 = zhangtingjiaDataItem1.iloc[0]
p1 = zhangtingjiaDataItem1.iloc[-1]
time =p0['Time']
TranID1 = p0['TranID']
TranID2 = p1['TranID']
buyId = p0['BuyOrderID']
buyidData= {
'amount':amount,
'vol': vol,
'TranID1': TranID1,
'TranID2': TranID2,
'buyId':buyId,
'time':time
}
key =str(TranID1)
dicARR[key] = buyidData
keyArr.append(TranID1)
if len(dicARR)==0:
continue
keyArr.sort()
for trainIDIndex in np.arange(len(keyArr)):
key = keyArr[trainIDIndex]
subkeyArr = keyArr[trainIDIndex+1:len(keyArr)]
item_key = dicARR[str(key)]
vol = item_key['vol']
amount = item_key['amount']
TranID1 = item_key['TranID1']
TranID2 = item_key['TranID2']
buyId = item_key['buyId']
time = item_key['time']
preItem = item_key
itemArr = []
itemArr.append(item_key)
amountZ = amount
flag = False
for subkey in subkeyArr:
item1 = dicARR[str(subkey)]
vol_01 = item1['vol']
amount_01 = item1['amount']
TranID1_01 = item1['TranID1']
TranID2_01 = item1['TranID2']
if vol_01>vol*(1+percent):
break
if vol_01<vol*(1-percent):
break
if TranID1_01 !=preItem['TranID2']+1:
break
amountZ = amountZ+amount_01
itemArr.append(item1)
preItem = item1
liandan= []
for detailItem in itemArr:
info=str(detailItem['vol']) + ',' + str(int(detailItem['amount'])) + ',' + str(
detailItem['TranID1']) + ',' + str(detailItem['TranID2']) + ',' + str(
detailItem['buyId']) + ',' + str(detailItem['time'])
liandan.append(info)
info='--|--'.join(liandan)
if amountZ>=7000000:
flag =True
codename = item['代码'][2:8] + "." + item['代码'][0:2]
codename = name[name['股票代码'] == codename]
if len(codename) == 0:
codename = ''
else:
codename = codename.iloc[0]['股票简称']
writer.writerow(
[item['代码'],
codename,
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'],
info,
len(liandan),
amountZ,
item1['time']
])
break
if flag:
break
10日未涨停回封/2022-202307/不复权/600/市值修复.py 0 → 100644
View file @ ae4ccb9b
import csv
import math
import os
import time
import numpy as np
import pandas as pd
root='/Users/yumingwu/Downloads/Stk_Day/'
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'])
data = pd.read_csv('./2022涨停(600)股本N连单大于700w.csv',encoding='gbk')
data['日期']=pd.to_datetime(data['日期'])
with open('./2022-2023涨停(600)股本N连单大于700w市值'+'.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','昨日是否涨停','盈利','涨幅','流通市值','跟单明细','连单笔数','总金额','时间'])
for index,item in data.iterrows():
dataS = pd.read_csv(root + item['代码']+'.csv', encoding='gbk')
dataS['时间'] = pd.to_datetime(dataS['时间'])
data1 = dataS[dataS['时间'] < item['日期']]
item2 = data1.iloc[-1]
item3 = data1.iloc[-2]
code = item['代码'][2:8] + "." + item['代码'][0:2]
guben = guben1[guben1['代码'] == code]
guben = guben.sort_values('变更日期', ascending=False)
gubenitem1 = guben[guben['变更日期'] <= item['日期']]
if len(gubenitem1) == 0:
gubenitem1 = guben.iloc[-1]
else:
gubenitem1 = gubenitem1.iloc[0]
huanshou = item2['成交量(股)'] / gubenitem1['流通A股']
shizhi = gubenitem1['流通A股'] * item2['收盘价'] / 100000000.0
zhangting =0;
if item2['收盘价']/item3['收盘价']>1.098:
zhangting=1
writer.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'],
zhangting,
item['盈利'],
item['涨幅'],
shizhi,
item['跟单明细'],
item['连单笔数'],
item['总金额'],
item['时间']
])
10日未涨停回封/2022-202307/不复权/600/振幅.py 0 → 100644
View file @ ae4ccb9b
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('./2022-2023涨停(600)股本N连单大于700w炸板率.csv',encoding='gbk')
file000 = open('./2022-2023涨停(600)股本N连单大于700w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','开盘涨幅','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','昨日是否涨停','盈利','涨幅','流通市值','跟单明细','连单笔数','总金额','时间','炸板率','涨停次数','炸板次数','触板次数','炸板幅度','涨停次日溢价率','次日总溢价率','最近3次触板溢价','一年最高价跌幅','半年最高价跌幅','一日最高价跌幅','三日最高价跌幅','6日最高价跌幅','10日最高价跌幅','12日最高价跌幅','一个月最高价跌幅','3个月最高价跌幅','9个月最高价跌幅',
'1个月最低价涨幅','3个月最低价涨幅','半年最低价涨幅','9个月最低价涨幅','一年最低价涨幅','振幅','昨日振幅','10日涨幅'])
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]
codeData=codeData[len(codeData)-10:len(codeData)]
min = codeData0['收盘价']/(codeData['最低价'].min())-1
writer000.writerow(
[item['代码'],
item['名称'],
item['日期'],
item['昨日收盘价'],
item['开盘价'],
item['开盘涨幅'],
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['昨日是否涨停'],
item['盈利'],
item['涨幅'],
item['流通市值'],
item['跟单明细'],
item['连单笔数'],
item['总金额'],
item['时间'],
item['炸板率'],
item['涨停次数'],
item['炸板次数'],
item['触板次数'],
item['炸板幅度'],
item['涨停次日溢价率'],
item['次日总溢价率'],
item['最近3次触板溢价'],
item['一年最高价跌幅'],
item['半年最高价跌幅'],
item['一日最高价跌幅'],
item['三日最高价跌幅'],
item['6日最高价跌幅'],
item['10日最高价跌幅'],
item['12日最高价跌幅'],
item['一个月最高价跌幅'],
item['3个月最高价跌幅'],
item['9个月最高价跌幅'],
item['1个月最低价涨幅'],
item['3个月最低价涨幅'],
item['半年最低价涨幅'],
item['9个月最低价涨幅'],
item['一年最低价涨幅'],
(codeData0['最高价']-codeData0['最低价'])/codeData1['收盘价'],
(codeData0['最高价'] - codeData0['最低价']) / codeData0['收盘价'],
min
])
10日未涨停回封/2022-202307/不复权/600/炸板率.py 0 → 100644
View file @ ae4ccb9b
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('./2022-2023涨停(600)股本N连单大于700w市值.csv',encoding='gbk')
file000 = open('./2022-2023涨停(600)股本N连单大于700w炸板率.csv','w',encoding='gbk',newline='')
writer000 = csv.writer(file000)
zhangtingpercent = 1.098
writer000.writerow(
['代码','名称','日期', '昨日收盘价','开盘价','开盘涨幅','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','昨日是否涨停','盈利','涨幅','流通市值','跟单明细','连单笔数','总金额','时间','炸板率','涨停次数','炸板次数','触板次数','炸板幅度','涨停次日溢价率','次日总溢价率','最近3次触板溢价','一年最高价跌幅','半年最高价跌幅','一日最高价跌幅','三日最高价跌幅','6日最高价跌幅','10日最高价跌幅','12日最高价跌幅','一个月最高价跌幅','3个月最高价跌幅','9个月最高价跌幅',
'1个月最低价涨幅','3个月最低价涨幅','半年最低价涨幅','9个月最低价涨幅','一年最低价涨幅'])
for index,item in data.iterrows():
day = item['日期']
day =pd.to_datetime(day)
code= item['代码']+'.csv'
print(item['代码'])
if os.path.exists(root + code) == False:
continue
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]
if len(codeData)==0:
continue
day2 = day - pd.offsets.DateOffset(months=6)
day1_month = day - pd.offsets.DateOffset(months=1)
day3_month = day - pd.offsets.DateOffset(months=3)
day9_month = day - pd.offsets.DateOffset(months=9)
codeData_6_month = codeData[codeData['时间'] >= day2]
codeData_1_month = codeData[codeData['时间'] >= day1_month]
codeData_3_month = codeData[codeData['时间'] >= day3_month]
codeData_9_month = codeData[codeData['时间'] >= day9_month]
codeData1 = codeData[len(codeData)-1:len(codeData)]
codeData3= codeData[len(codeData) - 3:len(codeData)]
codeData6 = codeData[len(codeData) - 6:len(codeData)]
codeData9 = codeData[len(codeData) - 10:len(codeData)]
codeData12 = codeData[len(codeData) - 12:len(codeData)]
item_y=codeData.iloc[-1]
item_y2 = codeData.iloc[-1]
if item_y['收盘价'] / item_y2['收盘价'] > zhangtingpercent:
zhangting = 1
rate_year = item_y['收盘价']/codeData['最高价'].max()
rate_year_min = item_y['收盘价'] / codeData['最低价'].min()
rate_6_month = item_y['收盘价'] / codeData_6_month['最高价'].max()
rate_6_month_min = item_y['收盘价'] / codeData_6_month['最低价'].min()
rate_1_month = item_y['收盘价'] / codeData_1_month['最高价'].max()
rate_1_month_min = item_y['收盘价'] / codeData_1_month['最低价'].min()
rate_3_month = item_y['收盘价'] / codeData_3_month['最高价'].max()
rate_3_month_min = item_y['收盘价'] / codeData_3_month['最低价'].min()
rate_9_month = item_y['收盘价'] / codeData_9_month['最高价'].max()
rate_9_month_min = item_y['收盘价'] / codeData_9_month['最低价'].min()
rate_1 = item_y['收盘价'] / codeData1['最高价'].max()
rate_3= item_y['收盘价'] / codeData3['最高价'].max()
rate_6 = item_y['收盘价'] / codeData6['最高价'].max()
rate_9 = item_y['收盘价'] / codeData9['最高价'].max()
rate_12 = item_y['收盘价'] / codeData12['最高价'].max()
zhangtingTime=0
zhaBanTime=0
zhaBanTimefudu=0
zhangtingyijia=0
zhangtingyijiazong = 0
arr3 = []
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']>zhangtingpercent:
zhangtingyijiazong = zhangtingyijiazong + item2['开盘价'] / item1['最高价'] - 1.0014
arr3.append(item2['开盘价'] / item1['最高价'] - 1.0014)
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+(item2['开盘价']/item1['最高价']-1.0014)
rate =0
if zhangtingTime>0 or zhaBanTime>0:
rate = zhaBanTime/(zhangtingTime+zhaBanTime)
if zhaBanTime!=0:
zhaBanTimefudu=zhaBanTimefudu/zhaBanTime
if zhangtingTime!=0:
zhangtingyijia=zhangtingyijia/zhangtingTime
if (zhangtingTime +zhaBanTime)!= 0:
zhangtingyijiazong = zhangtingyijiazong / (zhangtingTime+zhaBanTime)
rate3=-100
if len(arr3)>=3:
arr3 = arr3[len(arr3)-3:len(arr3)]
rate3 = (arr3[0]+arr3[1]+arr3[2])/3
writer000.writerow(
[item['代码'],
item['名称'],
item['日期'],
item['昨日收盘价'],
item['开盘价'],
float(item['开盘价'])/float(item['昨日收盘价']),
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['昨日是否涨停'],
item['盈利'],
item['涨幅'],
item['流通市值'],
item['跟单明细'],
item['连单笔数'],
item['总金额'],
item['时间'],
rate,
zhangtingTime,
zhaBanTime,
zhangtingTime+zhaBanTime,
zhaBanTimefudu,
zhangtingyijia,
zhangtingyijiazong,
rate3,
rate_year,
rate_6_month,
rate_1,
rate_3,
rate_6,
rate_9,
rate_12,
rate_1_month,
rate_3_month,
rate_9_month,
rate_1_month_min,
rate_3_month_min,
rate_6_month_min,
rate_9_month_min,
rate_year_min
])
10日未涨停回封/2022-202307/不复权/700wN连大单.py
View file @ ae4ccb9b
...@@ -11,9 +11,10 @@ import datetime ...@@ -11,9 +11,10 @@ import datetime
data=pd.read_csv('./2022-2023涨停(000)股本.csv',encoding='gbk') data=pd.read_csv('./2022-2023涨停(000)股本.csv',encoding='gbk')
data['日期']=pd.to_datetime(data['日期']) data['日期']=pd.to_datetime(data['日期'])
data = data.groupby('日期') data = data.groupby('日期')
percent=0.01
name = pd.read_excel('/Users/yumingwu/Desktop/沪深A股.xlsx') name = pd.read_excel('/Users/yumingwu/Desktop/沪深A股.xlsx')
with open('./2023涨停(000)股本N连单10%大于700w'+'.csv','w',encoding='gbk',newline='') as csfile: with open('./2023涨停(000)股本N连单b1-7%大于700w'+'.csv','w',encoding='gbk',newline='') as csfile:
writer =csv.writer(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','跟单明细','连单笔数','总金额','时间']) 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','跟单明细','连单笔数','总金额','时间'])
for day,dataR in data: for day,dataR in data:
...@@ -77,7 +78,8 @@ with open('./2023涨停(000)股本N连单10%大于700w'+'.csv','w',encoding='gbk ...@@ -77,7 +78,8 @@ with open('./2023涨停(000)股本N连单10%大于700w'+'.csv','w',encoding='gbk
'TranID1': TranID1, 'TranID1': TranID1,
'TranID2': TranID2, 'TranID2': TranID2,
'buyId':buyId, 'buyId':buyId,
'time':time 'time':time,
'price': p0['Price']
} }
key =str(TranID1) key =str(TranID1)
...@@ -120,9 +122,9 @@ with open('./2023涨停(000)股本N连单10%大于700w'+'.csv','w',encoding='gbk ...@@ -120,9 +122,9 @@ with open('./2023涨停(000)股本N连单10%大于700w'+'.csv','w',encoding='gbk
TranID1_01 = item1['TranID1'] TranID1_01 = item1['TranID1']
TranID2_01 = item1['TranID2'] TranID2_01 = item1['TranID2']
if vol_01>vol*1.1: if vol_01>vol*(1+percent):
break break
if vol_01<vol*0.9: if vol_01<vol*(1-percent):
break break
if TranID1_01 !=preItem['TranID2']+1: if TranID1_01 !=preItem['TranID2']+1:
break break
...@@ -139,7 +141,7 @@ with open('./2023涨停(000)股本N连单10%大于700w'+'.csv','w',encoding='gbk ...@@ -139,7 +141,7 @@ with open('./2023涨停(000)股本N连单10%大于700w'+'.csv','w',encoding='gbk
info='--|--'.join(liandan) info='--|--'.join(liandan)
if amountZ>=7000000: if amountZ>=7000000 and item1['price']/item['昨日收盘价']>=1.07:
flag =True flag =True
codename = item['代码'][2:8] + "." + item['代码'][0:2] codename = item['代码'][2:8] + "." + item['代码'][0:2]
......
10日未涨停回封/2022-202307/不复权/数据修复/炸板率.py
View file @ ae4ccb9b
...@@ -8,9 +8,9 @@ import pandas as pd ...@@ -8,9 +8,9 @@ import pandas as pd
root='/Users/yumingwu/Downloads/Stk_Day_QFQ/' root='/Users/yumingwu/Downloads/Stk_Day_QFQ/'
path =os.listdir(root) path =os.listdir(root)
data = pd.read_csv('./2022涨停(000)股本N连单10%大于700w.csv',encoding='gbk') data = pd.read_csv('./2022涨停(000)股本N连单大于700w市值.csv',encoding='gbk')
file000 = open('./2022-2023涨停(000)股本N连单10%大于700w炸板率.csv','w',encoding='gbk',newline='') file000 = open('./2022-2023涨停(000)股本N连单大于700w炸板率.csv','w',encoding='gbk',newline='')
writer000 = csv.writer(file000) writer000 = csv.writer(file000)
writer000.writerow( writer000.writerow(
['代码','名称','日期', '昨日收盘价','开盘价','开盘涨幅','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','昨日是否涨停','盈利','涨幅','流通市值','跟单明细','连单笔数','总金额','时间','炸板率','涨停次数','炸板次数','触板次数','炸板幅度','涨停次日溢价率','次日总溢价率','最近3次触板溢价','一年最高价跌幅','半年最高价跌幅','一日最高价跌幅','三日最高价跌幅','6日最高价跌幅','10日最高价跌幅','12日最高价跌幅','一个月最高价跌幅','3个月最高价跌幅','9个月最高价跌幅', ['代码','名称','日期', '昨日收盘价','开盘价','开盘涨幅','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','昨日是否涨停','盈利','涨幅','流通市值','跟单明细','连单笔数','总金额','时间','炸板率','涨停次数','炸板次数','触板次数','炸板幅度','涨停次日溢价率','次日总溢价率','最近3次触板溢价','一年最高价跌幅','半年最高价跌幅','一日最高价跌幅','三日最高价跌幅','6日最高价跌幅','10日最高价跌幅','12日最高价跌幅','一个月最高价跌幅','3个月最高价跌幅','9个月最高价跌幅',
...@@ -115,7 +115,7 @@ for index,item in data.iterrows(): ...@@ -115,7 +115,7 @@ for index,item in data.iterrows():
arr3 = arr3[len(arr3)-3:len(arr3)] arr3 = arr3[len(arr3)-3:len(arr3)]
rate3 = (arr3[0]+arr3[1]+arr3[2])/3 rate3 = (arr3[0]+arr3[1]+arr3[2])/3
zhangting = 0;
...@@ -133,7 +133,7 @@ for index,item in data.iterrows(): ...@@ -133,7 +133,7 @@ for index,item in data.iterrows():
item['换手率'], item['换手率'],
item['买入价格'], item['买入价格'],
item['卖出价格'], item['卖出价格'],
zhangting, item['昨日是否涨停'],
item['盈利'], item['盈利'],
item['涨幅'], item['涨幅'],
item['流通市值'], item['流通市值'],
......
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