如何在生成的表中插入新列

Question

您能帮我在生成的表中插入Category列吗?这样我就可以清楚地知道每一天和每一个类别的价格。

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

df1 <- structure(
list(date1= c("2021-06-28","2021-06-28","2021-06-28","2021-06-28"),
date2 = c("2021-06-30","2021-06-30","2021-07-01","2021-07-01"),
Category = c("FDE","ABC","FDE","ABC"),
Week= c("Wednesday","Wednesday","Friday","Friday"),
DR1 = c(4,1,6,3),
DR01 = c(4,1,4,3), DR02= c(4,2,6,2),DR03= c(9,5,4,7),
DR04 = c(5,4,3,2),DR05 = c(5,4,5,4),
DR06 = c(2,4,3,2),DR07 = c(2,5,4,4),
DR08 = c(3,4,5,4),DR09 = c(2,3,4,4)),
class = "data.frame", row.names = c(NA, -4L))

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: 4 x 2
dates       coef
<chr>      <dbl>
1 30/06/2021  7.89
2 30/06/2021  7.89
3 01/07/2021  7.95
4 01/07/2021  7.95

在本例中，它看起来像这样:

dates       Category  coef
<chr>                 <dbl>
1 30/06/2021    FDE     7.89
2 30/06/2021    ABC     7.89
3 01/07/2021    FDE     7.95
4 01/07/2021    ABC     7.95

Answer 1

您可以将bind_cols()用于包含Category列的数据集

##Select the Category column as a subset
categories <- subset(df1, date2 > date1, select =  Category)
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[[1]], coef = coef(mod)[2])

}) %>% bind_cols(categories)  %>% #add the categories to the tibble
mutate(dates = format(ymd(dates), "%d/%m/%Y"))