首页 > 解决方案 > 用R中的宽限日和月偿还计算

问题描述

首先,很抱歉再次发布相同的问题。

我想将宽限期添加到固定利息计算方法的还款表中,以便可以在宽限期内收到利息金额。

dataframe1:这是正常情况。

uid     emi_date    amt interest    tenure  emi      Rep_seq    status  balance
KII-453 01/01/2020  100 2%          12      10.33333    1          1    113.67
KII-453 01/02/2020  100 2%          12      10.33333    2          1    103.3367
KII-453 01/03/2020  100 2%          12      10.33333    3          1    93.00333
KII-453 01/04/2020  100 2%          12      10.33333    4          0    82.67
KII-453 01/05/2020  100 2%          12      10.33333    5          0    72.33667
KII-453 01/06/2020  100 2%          12      10.33333    6          0    62.00333
KII-453 01/07/2020  100 2%          12      10.33333    7          0    51.67
KII-453 01/08/2020  100 2%          12      10.33333    8          0    41.33667
KII-453 01/09/2020  100 2%          12      10.33333    9          0    31.00333
KII-453 01/10/2020  100 2%          12      10.33333    10         0    20.67
KII-453 01/11/2020  100 2%          12      10.33333    11         0    10.33667
KII-453 01/12/2020  100 2%          12      10.33333    12         0    0.003333

从dataframe1,我试图提供x从最后一个日期开始的接下来几个月的宽限期status = 1(在dataframe 1中,这是emi_date = '01/03/2020'

余额计算:

所需的结果应如下所示:

uid     emi_date    amt interest    tenure  emi       rep_seq   status  balance
KII-453 01/01/2020  100   2%          12    10.33333    1         1     113.67
KII-453 01/02/2020  100   2%          12    10.33333    2         2     103.3367
KII-453 01/03/2020  100   2%          12    10.33333    3         3     93.00333
KII-453 01/04/2020  100   2%          12    0           4         0     95.00333
KII-453 01/05/2020  100   2%          12    0           5         0     97.04333
KII-453 01/06/2020  100   2%          12    10.33333    6         0     86.71
KII-453 01/07/2020  100   2%          12    10.33333    7         0     76.37667
KII-453 01/08/2020  100   2%          12    10.33333    8         0     66.04333
KII-453 01/09/2020  100   2%          12    10.33333    9         0     55.71
KII-453 01/10/2020  100   2%          12    10.33333    10        0     45.37667
KII-453 01/11/2020  100   2%          12    10.33333    11        0     35.04333
KII-453 01/12/2020  100   2%          12    10.33333    12        0     24.71
KII-453 01/01/2021  100   2%          12    10.33333    13        0     14.37667
KII-453 01/02/2021  100   2%          12    10.33333    14        0     4.043333
KII-453 01/03/2021  100   2%          12    4.043333    15        0     0

余额计算 (row1) = 124 - 10.333 =113.67, row2 及以后直到状态 (1) = 余额 row1(113.67)-emi(10.333)

要添加宽限期,我们将接下来的两个月emi设为 0。这两个月的余额计算将是01/04/2020= amt(100)*interest(2%) + 之前的余额 (93.00333) 和01/05/2020= (amt(100)*interest (2%))+(amt(100)*利息(2%))*2%+ 之前的余额 (95.00333)

剩余余额计算将保持原样(例如,以前的余额 - emi)直到余额 < emi,如果余额 < emi,我们会将 emi 中的余额结转到下个月,并在该月保持余额 0。

PS - 使用的兴趣方法是平坦的,为了减少我正在尝试构建的逻辑,如果 SO 也可以帮助我,这将是有帮助的。

出于示例目的,我已经为一个uid真实的数据框创建了数据框,我在数据框中有约 10000 个唯一的 uid。

输入输出:

   dataframe1<- structure(list(uid = c("KII-62", "KII-62", "KII-62", 
"KII-62", "KII-62", "KII-62", "KII-62", 
"KII-62", "KII-62", "KII-62", "KII-62", 
"KII-62", "KII-62", "KII-62", "KII-62", 
"KII-62", "KII-62", "KII-62", "KII-62", 
"KII-62", "KII-62", "KII-62", "KII-62", 
"KII-62", "KII-63", "KII-63", "KII-63", 
"KII-63", "KII-63", "KII-63", "KII-63", 
"KII-63", "KII-63", "KII-63", "KII-63", 
"KII-63"), emi_date = c("05/12/2019", "05/01/2020", "05/02/2020", 
"05/03/2020", "05/04/2020", "05/05/2020", "05/06/2020", "05/07/2020", 
"05/08/2020", "05/09/2020", "05/10/2020", "05/11/2020", "05/12/2020", 
"05/01/2021", "05/02/2021", "05/03/2021", "05/04/2021", "05/05/2021", 
"05/06/2021", "05/07/2021", "05/08/2021", "05/09/2021", "05/10/2021", 
"05/11/2021", "05/12/2019", "05/01/2020", "05/02/2020", "05/03/2020", 
"05/04/2020", "05/05/2020", "05/06/2020", "05/07/2020", "05/08/2020", 
"05/09/2020", "05/10/2020", "05/11/2020"), amt = c(470000, 470000, 
470000, 470000, 470000, 470000, 470000, 470000, 470000, 470000, 
470000, 470000, 470000, 470000, 470000, 470000, 470000, 470000, 
470000, 470000, 470000, 470000, 470000, 470000, 220000, 220000, 
220000, 220000, 220000, 220000, 220000, 220000, 220000, 220000, 
220000, 220000), interest = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2), tenure = c(24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 12, 12, 
12, 12, 12, 12, 12, 12, 12, 12, 12, 12), emi = c(28983.33, 28983.33, 
28983.33, 28983.33, 28983.33, 28983.33, 28983.33, 28983.33, 28983.33, 
28983.33, 28983.33, 28983.33, 28983.33, 28983.33, 28983.33, 28983.33, 
28983.33, 28983.33, 28983.33, 28983.33, 28983.33, 28983.33, 28983.33, 
28983.33, 22733.33, 22733.33, 22733.33, 22733.33, 22733.33, 22733.33, 
22733.33, 22733.33, 22733.33, 22733.33, 22733.33, 22733.33), 
    Rep_seq = c("1", "2", "3", "4", "5", "6", "7", "8", "9", 
    "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", 
    "20", "21", "22", "23", "24", "1", "2", "3", "4", "5", "6", 
    "7", "8", "9", "10", "11", "12"), status = c(1L, 1L, 1L, 
    1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L), balance = c(450416.666666667, 430833.333333333, 
    411250, 391666.666666667, 372083.333333333, 352500, 332916.666666667, 
    313333.333333333, 293750, 274166.666666667, 254583.333333333, 
    235000, 215416.666666667, 195833.333333333, 176250, 156666.666666667, 
    137083.333333333, 117500, 97916.6666666667, 78333.3333333333, 
    58750, 39166.6666666667, 19583.3333333333, 8e-28, 201666.666666667, 
    183333.333333333, 165000, 146666.666666667, 128333.333333333, 
    110000, 91666.6666666667, 73333.3333333333, 55000, 36666.6666666667, 
    18333.3333333333, 4e-28)), .Names = c("uid", "emi_date", 
"amt", "interest", "tenure", "emi", "Rep_seq", "status", "balance"
), class = "data.frame", row.names = c(NA, 36L))

uid = KII-62 的第 1 行余额将是 (amt * interest * tenure)+amt,对于 uid = KII-63 的第 1 行余额将重复同样的操作

第 1 行余额 (KII-62):(4,70,000*0.02*24)+4,70,000 = 6,96,500

感谢 SO,下面是我用于计算的代码,但在 2-3 个月结束时得到一个负值,请帮助解决问题。

library(tidyverse)
library (lubridate) # for dmy()
startingbalance <- 124
period <- "1 month"
dataframe1 %>% 
  mutate(index = seq(1,nrow(.))) %>%
  mutate(emi_date = dmy(emi_date)) %>%
  mutate(emi = case_when(status - lag(status) < 0 ~ 0, status - lag(status,2L) < 0 ~ 0, TRUE ~ emi)) %>%
  mutate(balance = case_when(index == 1 ~ startingbalance - emi,
                                index > 1 & emi > 0 & status == 1 ~ lag(balance) - emi,
                                index > 1 & emi == 0 & lag(status) == 1 & lag(status,2L) == 1 ~ lag(balance) + (amt * (as.integer(gsub("%","",interest))) / 100),
                                index > 1 & emi == 0 & lag(status) == 0 & lag(status,2L) == 1 ~ lag(balance,2L) + 2 * (amt * (as.integer(gsub("%","",interest))) / 100),
                                TRUE ~ NaN)) %>%
  select(-index) %>%
  do(add_row(., uid = .$uid[nrow(.)],emi_date = .$emi_date[nrow(.)] + period(period), amt = .$amt[nrow(.)],interest = .$interest[nrow(.)],tenure = .$tenure[nrow(.)],emi = .$emi[nrow(.)],status = .$status[nrow(.)],Rep_seq = .$Rep_seq[nrow(.)] + 1,balance = NaN)) %>% 
  do(add_row(., uid = .$uid[nrow(.)],emi_date = .$emi_date[nrow(.)] + period(period), amt = .$amt[nrow(.)],interest = .$interest[nrow(.)],tenure = .$tenure[nrow(.)],emi = .$emi[nrow(.)],status = .$status[nrow(.)],Rep_seq = .$Rep_seq[nrow(.)] + 1,balance = NaN)) %>%
  do(add_row(., uid = .$uid[nrow(.)],emi_date = .$emi_date[nrow(.)] + period(period), amt = .$amt[nrow(.)],interest = .$interest[nrow(.)],tenure = .$tenure[nrow(.)],emi = .$emi[nrow(.)],status = .$status[nrow(.)],Rep_seq = .$Rep_seq[nrow(.)] + 1,balance = NaN)) %>%
  mutate(balance =  {ind <- which(is.nan(balance)); for(i in ind){balance[i] <- balance[i-1] - emi[i]}; balance}) %>%
  mutate(emi = case_when(balance < 0 ~ lag(balance), TRUE ~ emi),
         balance = case_when(balance < 0 ~ 0, TRUE ~ balance))

标签: rdataframeggplot2dplyr

解决方案


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