Adjust output table for certain date/code - r

Question

The code below works for almost all dates and codes that I choose from my df1 database, however only for the day 09/07, code FGE that doesn't. I would like to solve this problem, could you help me? If you need to, I can explain better what this code does.
library(dplyr)
library(tidyverse)
library(lubridate)
library(stringr)
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("2021-06-30","2021-06-30","2021-07-02","2021-07-07","2021-07-07","2021-07-09","2021-07-09","2021-07-09"),
Code = c("FDE","ABC","ABC","ABC","CDE","FGE","ABC","CDE"),
Week= c("Wednesday","Wednesday","Friday","Wednesday","Wednesday","Friday","Friday","Friday"),
DR1 = c(4,1,4,3,3,4,3,5),
DR01 = c(4,1,4,3,3,4,3,6), DR02= c(4,2,6,7,3,2,7,4),DR03= c(9,5,4,3,3,2,1,5),
DR04 = c(5,4,3,3,6,2,1,9),DR05 = c(5,4,5,3,6,2,1,9),
DR06 = c(2,4,3,3,5,6,7,8),DR07 = c(2,5,4,4,9,4,7,8),
DR08 = c(0,0,0,1,2,0,0,0),DR09 = c(0,0,0,0,0,0,0,0),DR010 = c(0,0,0,0,0,0,0,0),DR011 = c(4,0,0,0,0,0,0,0),
DR012 = c(0,0,0,3,0,0,0,5),DR013 = c(0,0,1,0,0,0,2,0),DR014 = c(0,0,0,0,0,2,0,0)),
class = "data.frame", row.names = c(NA, -8L))
dmda<-"2021-07-09"
CodeChosse<-"FGE"
x<-df1 %>% select(starts_with("DR0"))
x<-cbind(df1, setNames(df1$DR1 - x, paste0(names(x), "_PV")))
PV<-select(x, date2,Week, Code, DR1, ends_with("PV"))
med<-PV %>%
group_by(Code,Week) %>%
summarize(across(ends_with("PV"), median))
SPV<-df1%>%
inner_join(med, by = c('Code', 'Week')) %>%
mutate(across(matches("^DR0\\d+$"), ~.x +
get(paste0(cur_column(), '_PV')),
.names = '{col}_{col}_PV')) %>%
select(date1:Code, DR01_DR01_PV:last_col())
SPV<-data.frame(SPV)
mat1 <- df1 %>%
filter(date2 == dmda, Code == CodeChosse) %>%
select(starts_with("DR0")) %>%
pivot_longer(cols = everything()) %>%
arrange(desc(row_number())) %>%
mutate(cs = cumsum(value)) %>%
filter(cs == 0) %>%
pull(name)
(dropnames <- paste0(mat1,"_",mat1, "_PV"))
SPV %>%
filter(date2 == dmda, Code == CodeChosse) %>%
select(-dropnames)
> SPV %>%
+ filter(date2 == dmda, Code == CodeChosse) %>%
+ select(-dropnames)
Error: Can't subset columns that don't exist.
x Column `__PV` doesn't exist.
Run `rlang::last_error()` to see where the error occurred.
For others datas/codes it works, for example:
dmda<-"2021-06-30"
CodeChosse<-"FDE"
> SPV %>%
+ filter(date2 == dmda, Code == CodeChosse) %>%
+ select(-dropnames)
date1 date2 Code DR01_DR01_PV DR02_DR02_PV DR03_DR03_PV DR04_DR04_PV DR05_DR05_PV DR06_DR06_PV DR07_DR07_PV DR08_DR08_PV
1 2021-06-28 2021-06-30 FDE 4 4 4 4 4 4 4 4
DR09_DR09_PV DR010_DR010_PV DR011_DR011_PV
1 4 4 4
dmda<-"2021-07-02"
CodeChosse<-"ABC"
> SPV %>%
+ filter(date2 == dmda, Code == CodeChosse) %>%
+ select(-dropnames)
date1 date2 Code DR01_DR01_PV DR02_DR02_PV DR03_DR03_PV DR04_DR04_PV DR05_DR05_PV DR06_DR06_PV DR07_DR07_PV DR08_DR08_PV
1 2021-06-28 2021-07-02 ABC 4 3 5 4.5 5.5 1.5 2 3.5
DR09_DR09_PV DR010_DR010_PV DR011_DR011_PV DR012_DR012_PV DR013_DR013_PV
1 3.5 3.5 3.5 3.5 3
dmda<-"2021-07-07"
CodeChosse<-"CDE"
> SPV %>%
+ filter(date2 == dmda, Code == CodeChosse) %>%
+ select(-dropnames)
date1 date2 Code DR01_DR01_PV DR02_DR02_PV DR03_DR03_PV DR04_DR04_PV DR05_DR05_PV DR06_DR06_PV DR07_DR07_PV DR08_DR08_PV
1 2021-06-28 2021-07-07 CDE 3 3 3 3 3 3 3 3

Answer 1

The issue in this particular case is that mat1 has no values in it because the 1st row in df1 has non-zero value and filter(cs == 0) drops all the rows.
mat1
#character(0)
You may use any_of which will not give an error if the column does not exist.
library(dplyr)
SPV %>%
filter(date2 == dmda, Code == CodeChosse) %>%
select(-any_of(dropnames))