问题描述
对于我的硕士学位，我必须检查现有数据集上的不同填充方法。因此，我必须添加不同长度的人工间隙（1h，5h ..），以便可以用不同的方法填充它们。有简单的功能吗？
这是数据框的示例：
class ApplePay: NSObject {
var applePayItem: PKPaymentSummaryItem?
var baseVC: UIViewController?
let payNetworks = [PKPaymentNetwork.masterCard,.visa,.amex,.discover]
init(forItem: Product) {
applePayItem = PKPaymentSummaryItem.init(label: forItem.name ?? "",amount: NSDecimalNumber(value: forItem.price ?? 0))
}
func initiatePayment(complete: @escaping (Bool) -> Void) {
if PKPaymentAuthorizationViewController.canMakePayments(usingNetworks: payNetworks) {
let request = PKPaymentRequest()
request.currencyCode = "USD"
request.countryCode = "US"
request.merchantIdentifier = <*identifier from my development account*>
request.merchantCapabilities = PKMerchantCapability.capability3DS
request.supportednetworks = payNetworks
request.paymentSummaryItems = [applePayItem!]
guard let paymentVC = PKPaymentAuthorizationViewController(paymentRequest: request) else {
return
}
baseVC = UIApplication.shared.keyWindow?.rootViewController?.children.last
baseVC?.present(paymentVC,animated: true,completion: nil)
paymentVC.delegate = self
complete(true)
} else {
complete(false)
CaAssembly.resolve(CaAlertProtocol.self)!.showAlert(CaConstant.alertTitles.addCardApplePay,dismiss: {})
}
}
func paymentAuthorizationControllerDidFinish(_ controller: PKPaymentAuthorizationController) {
controller.dismiss {
}
func paymentAuthorizationViewControllerDidFinish(_ controller: PKPaymentAuthorizationViewController) {
controller.dismiss(animated: true,completion: nil)
}
}
extension ApplePay: PKPaymentAuthorizationViewControllerDelegate,PKPaymentAuthorizationControllerDelegate {
@available(iOS 11.0,*)
func paymentAuthorizationViewController(_ controller:
PKPaymentAuthorizationViewController,didAuthorizePayment payment: PKPayment,handler completion: @escaping
(PKPaymentAuthorizationResult) -> Void) {
print(“PKPaymentAuthorizationViewController didAuthorizePayment” )
}
}
解决方法
如果我正确理解了您的问题，则可能的解决方法是：
set.seed(4) # make it reproducable
del <- sort(sample(1:nrow(df),4,replace=FALSE)) # get 4 random indexex from the total number of rows and sort them
del2 <- del[diff(del) !=1] # delete those values that have a difference of 1 (meaning "connected")
df[del2,c(2:5)] <- NA # set column 2 to 5 NA for the indices we calculated above
DateTime `Dd 1-1` `Dd 1-3` `Dd 1-5` luecken
<dttm> <dbl> <dbl> <dbl> <dbl>
1 2015-01-01 01:00:00 0.0186 0.0243 0.0213 0.0186
2 2015-01-01 02:00:00 0.0243 0.0349 0.0284 0.0243
3 2015-01-01 03:00:00 NA NA NA NA
4 2015-01-01 04:00:00 0.000967 0.00136 0.0143 0.000967
5 2015-01-01 05:00:00 0.0119 0.0221 0.0276 0.0119
6 2015-01-01 06:00:00 0.0496 0.0601 0.0329 0.0496
7 2015-01-01 07:00:00 0.0201 0.0462 0.0495 0.0201
8 2015-01-01 08:00:00 0.0307 0.0172 0.0173 0.0307
9 2015-01-01 09:00:00 NA NA NA NA
10 2015-01-01 10:00:00 0.0192 0.0227 0.0177 0.0192
请明确一点：清理连接间隙的步骤并不完全正确，因为随机数为1-4会掉2、3和4，但是在大数据上，如果您选择与整个数据集相比，我们不打算放弃很多值
现在介绍如何创建更大的差距（我将使用3h，因为您的示例数据只有10行）
set.seed(4)
del <- sort(sample(1:nrow(df),3,replace=FALSE))
del2 <- del[diff(del) > 3] #set difference to more than maximum size of gap wanted
del3 <- c(del2,del2 + 1,del2 + 2) # build vector with +1 and +2 to get indices conecting conecting to the onces you have
del4 <- del3[del3 <= nrow(df)] # make sure it is not out of bound (max index should be 10 even if gap starts at line 10
df[del4,c(2:5)] <- NA
DateTime `Dd 1-1` `Dd 1-3` `Dd 1-5` luecken
<dttm> <dbl> <dbl> <dbl> <dbl>
1 2015-01-01 01:00:00 0.0186 0.0243 0.0213 0.0186
2 2015-01-01 02:00:00 0.0243 0.0349 0.0284 0.0243
3 2015-01-01 03:00:00 NA NA NA NA
4 2015-01-01 04:00:00 NA NA NA NA
5 2015-01-01 05:00:00 NA NA NA NA
6 2015-01-01 06:00:00 0.0496 0.0601 0.0329 0.0496
7 2015-01-01 07:00:00 0.0201 0.0462 0.0495 0.0201
8 2015-01-01 08:00:00 0.0307 0.0172 0.0173 0.0307
9 2015-01-01 09:00:00 NA NA NA NA
10 2015-01-01 10:00:00 NA NA NA NA