I'm having a little problem when generating the graph for the day 03/07, category ABC. Note that the two graphs I can generate normally, but the last graph not. This happens because I have values equal to zero for this date/category, so when it comes to datas, it's was NA. However, I would like to generate a graph when this situation occurs, with a point at 0 and a red line at 0, similar to the other images. I believe that to solve this it must be some small adjustment, but I couldn't do it. I appreciate any help!
Executable code below:
library(dplyr)
library(tidyr)
library(lubridate)
df1 <- structure(
list(date1= c("2021-06-28","2021-06-28","2021-06-28"),
date2 = c("2021-07-01","2021-07-02","2021-07-03"),
Category = c("BCE","ABC","ABC"),
Week= c("Wednesday","Thursday","Friday"),
DR1 = c(11,5,0),
DR01 = c(10,4,0), DR02= c(2,4,0),DR03= c(0,5,0),
DR04 = c(2,4,0),DR05 = c(1,6,0)),
class = "data.frame", row.names = c(NA, -3L))
f1 <- function(dmda, CategoryChosse) {
x<-df1 %>% select(starts_with("DR0"))
x<-cbind(df1, setNames(df1$DR1 - x, paste0(names(x), "_PV")))
PV<-select(x, date2,Week, Category, DR1, ends_with("PV"))
med<-PV %>%
group_by(Category,Week) %>%
summarize(across(ends_with("PV"), median))
SPV<-df1%>%
inner_join(med, by = c('Category', 'Week')) %>%
mutate(across(matches("^DR0\\d+$"), ~.x +
get(paste0(cur_column(), '_PV')),
.names = '{col}_{col}_PV')) %>%
select(date1:Category, DR01_DR01_PV:last_col())
SPV<-data.frame(SPV)
mat1 <- df1 %>%
filter(date2 == dmda, Category == CategoryChosse) %>%
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 <- SPV %>%
filter(date2 == dmda, Category == CategoryChosse) %>%
select(-any_of(dropnames))
if(length(grep("DR0", names(SPV))) == 0) {
SPV[head(mat1, 20)] <- NA_real_
}
datas <-SPV %>%
filter(date2 == ymd(dmda)) %>%
group_by(Category) %>%
summarize(across(starts_with("DR0"), sum)) %>%
pivot_longer(cols= -Category, names_pattern = "DR0(.+)", values_to = "val") %>%
mutate(name = readr::parse_number(name))
colnames(datas)[-1]<-c("Days","Numbers")
datas <- datas %>%
group_by(Category) %>%
slice((as.Date(dmda) - min(as.Date(df1$date1) [
df1$Category == first(Category)])):max(Days)+1) %>%
ungroup
m<-df1 %>%
group_by(Category,Week) %>%
summarize(across(starts_with("DR1"), mean))
m<-subset(m, Week == df1$Week[match(ymd(dmda), ymd(df1$date2))] & Category == CategoryChosse)$DR1
maxrange <- range(0, datas$Numbers, na.rm = TRUE)
maxrange[2] <- max(datas$Numbers)+ 20
max<-max(datas$Days, na.rm = TRUE)+1
plot(Numbers ~ Days, xlim= c(0,max), ylim= c(0,maxrange[2]),
xaxs='i',data = datas,main = paste0(dmda, "-", CategoryChosse))
if (nrow(datas)<=2){
abline(h=m,lwd=2)
points(0, m, col = "red", pch = 19, cex = 2, xpd = TRUE)
text(.1,m+ .5, round(m,1), cex=1.1,pos=4,offset =1,col="black")}
}
f1("2021-07-01", "BCE")
f1("2021-07-02", "ABC")
f1("2021-07-03", "ABC")
Error in plot.window(...) : need finite 'xlim' values”
In addition: Warning messages:
1: In max(datas$Numbers) : no non-missing arguments to max; returning -Inf
2: In max(datas$Days, na.rm = TRUE) :
