将新数据插入表中

Question

我想对以下问题有所帮助：请注意，此代码从我选择的日期生成一个系数，在这种情况下，对于 03/07 (dmda)，它给出的系数等于 15.55。在这种情况下，我想生成一个新表，其中有一列带有日期，另一列带有与这些日期对应的系数。对于列日期，仅考虑 date1 (28/06) 中考虑的日期之后的 date2 日期，在这种情况下，日期为：01/07、02/07 和 03/07。

所以表格将如下所示：

谢谢！

library(dplyr)
library(tidyverse)
library(lubridate)

df1 <- structure(
  list(date1 = c("2021-06-28","2021-06-28","2021-06-28","2021-06-28","2021-06-28",
                 "2021-06-28","2021-06-28","2021-06-28"),
       date2 = c("2021-04-02","2021-04-03","2021-04-08","2021-04-09","2021-04-10","2021-07-01","2021-07-02","2021-07-03"),
       Week= c("Friday","Saturday","Thursday","Friday","Saturday","Thursday","Friday","Monday"),
       DR01 = c(14,11,14,13,13,14,13,16), DR02= c(14,12,16,17,13,12,17,14),DR03= c(19,15,14,13,13,12,11,15),
       DR04 = c(15,14,13,13,16,12,11,19),DR05 = c(15,14,15,13,16,12,11,19),
       DR06 = c(21,14,13,13,15,16,17,18),DR07 = c(12,15,14,14,19,14,17,18)),
  class = "data.frame", row.names = c(NA, -8L))

dmda<-"2021-07-03"

datas<-df1 %>%
  filter(date2 == ymd(dmda)) %>%
  summarize(across(starts_with("DR"), sum)) %>%
  pivot_longer(everything(), names_pattern = "DR(.+)", values_to = "val") %>%
  mutate(name = as.numeric(name))
colnames(datas)<-c("Days","Numbers")

mod <- nls(Numbers ~ b1*Days^2+b2,start = list(b1 = 47,b2 = 0), data = datas)
coef(mod)[2]
> coef(mod)[2]
      b2 
15.55011 

Answer 1

我们可以subset 'date2' 大于 date1' 的数据，将 'date2' 列提取为向量。使用map（来自purrr）循环日期，在循环内进行转换，构建nls 并在tibble 中提取coefficient，然后使用_dfr 折叠@987654328 @给单个tibble

library(purrr)
library(dplyr)
dates <- subset(df1, date2 > date1, select = date2)$date2
map_dfr(dates, ~ {
 
   datas <- df1 %>%
  filter(date2 == ymd(.x)) %>%
  summarize(across(starts_with("DR"), sum)) %>%
  pivot_longer(everything(), names_pattern = "DR(.+)", values_to = "val") %>%
  mutate(name = as.numeric(name))
colnames(datas)<-c("Days","Numbers")
mod <- nls(Numbers ~ b1*Days^2+b2,start = list(b1 = 47,b2 = 0), data = datas)
  tibble(dates = .x, coef = coef(mod)[2])
   }) %>%
   mutate(dates = format(ymd(dates), "%d/%m/%Y"))
# A tibble: 3 × 2
  dates       coef
  <chr>      <dbl>
1 01/07/2021  12.2
2 02/07/2021  12.4
3 03/07/2021  15.6