. +1 IssueDate MMDDYY10.; ExpireDate = IssueDate + (365.25*3); ExpireQuarter = QTR(ExpireDate...); if IssueDate > '01JAN2003'D then NewCard = 'yes'; cards; A....Kaminaka 29may2001 01-24-2003 ; proc print data=date; Format IssueDate MMDDYY10.; Format birthday YYMMDD10
就业职称 employmentLength 就业年限（年） homeOwnership 借款人在登记时提供的房屋所有权状况 annualIncome 年收入 verificationStatus 验证状态 issueDate...'] = pd.to_datetime(data_train['issueDate'],format='%Y-%m-%d') startdate = datetime.datetime.strptime...).dt.days #转化成时间格式 data_test_a['issueDate'] = pd.to_datetime(data_train['issueDate'],format='%Y-%m-%d...', 'earliesCreditLine'] category_fea：对象型类别特征需要进行预处理，其中'issueDate'为时间格式特征。...#转化成时间格式 for data in [data_train, data_test_a]: data['issueDate'] = pd.to_datetime(data['issueDate
特征转换 为了进一步探究issueDate和earliesCreditLine这两个时间ID的时间久远性是否会对我们的预测产生影响，另外增加了两个变量，分别是interval_issueDate和Interval_earliesCreditLine...,都是用2020减去issueDate和earliesCreditLine的年份得到的。...决策树 使用二分支和三分支决策树进行分析，结果显示影响贷款违约的重要因素有homeOwnership、ficoRangeHigh、dti、grade、term、issueDate等。...对于贷款发放年份issueDate，相较于2017年6月之后发放的贷款，2013年6月之前发放的贷款违约风险显著更大，贷款发放年份在2013.6-2015.6年的违约风险稍低，在2015.6-2017.6
formsAuthTicket = GetFormsAuthTicket(protectedText); var name = formsAuthTicket.Name; DateTime issueDate...= formsAuthTicket.IssueDate; DateTime expiration = formsAuthTicket.Expiration; var...Microsoft.AspNetCore.Http.Authentication.AuthenticationProperties { IssuedUtc = issueDate...FormsAuthTicket public class FormsAuthTicket { public DateTime Expiration { get; set; } public DateTime IssueDate...formsAuthTicket = FormsAuthentication.Decrypt(cookie); return Ok(new { formsAuthTicket.Name, formsAuthTicket.IssueDate
债券标的为170005，我的python代码如下： 1 import QuantLib as ql 2 3 faceAmount = 100.0 4 redemption = 100.0 5 issueDate...flatTermStructure) 32 bondEngin = ql.DiscountingBondEngine(discountingTermStructure) 33 34 schedule = ql.Schedule(issueDate...ql.Following, 48 redemption, 49 issueDate
特征转换为了进一步探究issueDate和earliesCreditLine这两个时间ID的时间久远性是否会对我们的预测产生影响，另外增加了两个变量，分别是interval_issueDate和Interval_earliesCreditLine...,都是用2020减去issueDate和earliesCreditLine的年份得到的。...决策树使用二分支和三分支决策树进行分析，结果显示影响贷款违约的重要因素有homeOwnership、ficoRangeHigh、dti、grade、term、issueDate等。...对于贷款发放年份issueDate，相较于2017年6月之后发放的贷款，2013年6月之前发放的贷款违约风险显著更大，贷款发放年份在2013.6-2015.6年的违约风险稍低，在2015.6-2017.6
Created token for fayson: HDFS_DELEGATION_TOKEN owner=fayson@CLOUDERA.COM, renewer=yarn, realUser=, issueDate...Ident: (token for fayson: HDFS_DELEGATION_TOKEN owner=fayson@CLOUDERA.COM, renewer=yarn, realUser=, issueDate...Ident: (token for fayson: HDFS_DELEGATION_TOKEN owner=fayson@CLOUDERA.COM, renewer=yarn, realUser=, issueDate
employmentTitle', 'employmentLength', 'homeOwnership', 'annualIncome', 'verificationStatus', 'issueDate...png 非数值类别型变量分析 category_fea ['grade', 'subGrade', 'employmentLength', 'issueDate', 'earliesCreditLine...png 2.3.6 时间格式数据处理及查看 #转化成时间格式 issueDateDT特征表示数据日期离数据集中日期最早的日期（2007-06-01）的天数 data_train['issueDate'...] = pd.to_datetime(data_train['issueDate'],format='%Y-%m-%d') startdate = datetime.datetime.strptime(...).dt.days #转化成时间格式 data_test_a['issueDate'] = pd.to_datetime(data_train['issueDate'],format='%Y-%m-%d
0 dtype: int64 #查看类别特征 category_fea ['grade', 'subGrade', 'employmentLength', 'issueDate...', 'earliesCreditLine'] category_fea：对象型类别特征需要进行预处理，其中['issueDate']为时间格式特征。...时间格式处理 #转化成时间格式 for data in [data_train, data_test_a]: data['issueDate'] = pd.to_datetime(data['issueDate...= datetime.datetime.strptime('2007-06-01', '%Y-%m-%d') #构造时间特征 data['issueDateDT'] = data['issueDate...output_81_1.png features = [f for f in data_train.columns if f not in ['id','issueDate','isDefault']
exit 1 fi local hour_now=$(date '+%H') local issuedate=$(date '+%Y-%m-%d') if [ ${hour_now...=$(date -v+1d '+%Y-%m-%d') else issuedate=$(date '+%Y-%m-%d' -d "+1 days")...else issuedate=$(date '+%Y-%m-%d' -d "+${expire} days")...fi # issue new permit request echo "new permit will start from ${issuedate}" local issuereq...=$(date "-v+${expire}d" '+%Y-%m-%d') else issuedate=$(date '+%Y-%m-%d' -d "+${expire} days") fi
Table(name = "T_ID_CARD") public class IdCard { private Long id; private String idNumber; private Date issueDate...Column(name = "ISSUE_DATE") @Temporal(TemporalType.TIMESTAMP) public Date getIssueDate() { return issueDate...; } public void setIssueDate(Date issueDate) { this.issueDate = issueDate; } } @Temporal告诉JPA如何将其序列化保存到数据库中
T_ID_CARD") public class IdCard { private Long id; private String idNumber; private Date issueDate..."ISSUE_DATE") @Temporal(TemporalType.TIMESTAMP) public Date getIssueDate() { return issueDate...; } public void setIssueDate(Date issueDate) { this.issueDate = issueDate; } } Tips
employmentLength 就业年限（年） - homeOwnership 借款人在登记时提供的房屋所有权状况 - annualIncome 年收入 - verificationStatus 验证状态 - issueDate...employmentTitle', 'employmentLength', 'homeOwnership', 'annualIncome', 'verificationStatus', 'issueDate...3.5.2 时间特征分析 #转化成时间格式 data_train['issueDate'] = pd.to_datetime(data_train['issueDate'],format='%Y-%m-...startdate = datetime.datetime.strptime('2007-06-01', '%Y-%m-%d') data_train['issueDateDT'] = data_train['issueDate...'].apply(lambda x: x-startdate).dt.days 将数据集时间特征转化为时间格式后，可以看到整个数据集最早的issueDate是2007-06-01，所以将整个数据集的issueDate
SOURCEPRODUCTQUANTITY, COMPONENTID, VENDORLOTID, VENDORNAME, ISSUEDATE
IssueDate, ExpiryTime and Status can be empty on writes. type License struct { Status...omitempty"` UID string `json:"uid"` Type string `json:"type"` IssueDate...string `json:"uid"` Type OperatorLicenseType `json:"type"` IssueDate
-- 销售订单编号 --> 2018-09-01 <!
好在只是调试，可以直接硬编码日期为一个合法值： # mac date performs differs with other unix.. if [ ${IS_MAC} -eq 1 ]; then issuedate...=$(date "-v+${expire}d" '+%Y-%m-%d') else issuedate=$(date '+%Y-%m-%d' -d "+${expire} days") fi...issuedate="2023-03-04" 然后就成功了！
company_name'] = job_item["company_name"] # 发布时间 items['Releasetime'] = job_item['issuedate
jobArea=000000&jobArea3=&landmark=&metro=&salary=&workYear=°ree=&companyType=&companySize=&jobType=&issueDate...workYear': '', 'degree': '', 'companyType': '', 'companySize': '', 'jobType': '', 'issueDate
TokenID = {ownerID, renewerID, issueDate, maxDate, sequenceNumber} TokenAuthenticator = HMAC-SHA1(masterKey
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