For loop combine with 2 if conditions. (only if).

Hi everyone,

I am doing a loop to make some graphs. The problem is that May 2014 is not in my data. Hence I decided to do an if into my loops. Actually, I do know the loops & the if are working, but partially. All my may & my 2014 data are just eliminated, which is not my aims but only may 2014. I already spent a day on it. I am pretty sure I am just making a bad mistake (since it's my first if in R). I would like do it only if the both are combine.

Mymonths <- month.name
Myyears <- unique(HQ$Year)

Myyears
[1] 2013 2014 2015 2016 2017 2018 2019

Mymonths
[1] "January" "February" "March" "April" "May" "June" "July" "August" "September" "October"
[11] "November" "December"

for (Y in Myyears) {
for (M in Mymonths) {
if(2014 != Y && "May" != M) {
print(Y)
print(M)
}
}
}
...
[1] "April"
[1] 2013
[1] "June"
[1] 2013
[1] "July"
[1] 2013
[1] "August"
[1] 2013
[1] "September"
[1] 2013
[1] "October"
[1] 2013
[1] "November"
[1] 2013
[1] "December"
[1] 2015
...

I already try all theses :

if(2014 != Y && "May" != M);

Myyears <- as.character(Myyears)
if("2014" != Y && "May" != M)

if(Y != 2014 && M != "May")

if(Y != 2014 & M != "May")

All of the aboe give the same results.

I know that one way I could solve it is by doing another if combine to an ifesle, but I think that would be bad coding.

for (Y in Myyears) {
for (M in Mymonths) {
if("2014" != Y) {
print(Y)
print(M)
} else {
if("May" != M){
print(Y)
print(M)
}
}
}
}

[1] "April"
[1] "2013"
[1] "May"
[1] "2013"
[1] "June"
[1] "2013"
[1] "July"
[1] "2013"
[1] "August"
[1] "2013"
[1] "September"
[1] "2013"
[1] "October"
[1] "2013"
[1] "November"
[1] "2013"
[1] "December"
[1] "2014"
[1] "January"
[1] "2014"

As we can see the both if are working, both, it's not the best way to write if, especially if I had like 4 conditions.

Have you tried formatting your data as a data.frame? Then let R handle the messy details like there are no rows for May 2014 when plotting or summarizing.

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Yes, actually this is just a easy way of underlining my problem.
That is my real graphs :

for (Y in Myyears) {
for (M in Mymonths) {
if(2014 != Y) {
x <- ggplot(D_H_M_Y[D_H_M_Y$Month == M & D_H_M_Y$Year == Y,], aes(x=Hour,group =1))+
geom_smooth(aes(y=Consumption), se = FALSE, color = ConsumptionColor, size = 1.1)+
geom_line(aes(y=WPcof),color = WindColor, size = 1.1)+
scale_y_continuous(
name = "Consumption",
sec.axis=sec_axis(~./cof, name="Wind Power"))+
facet_wrap(Year~Month~Day, nrow=4)+
theme(
axis.title.y = element_text(color = ConsumptionColor, size =13),
axis.title.y.right = element_text(color = WindColor, size =13),
panel.grid=element_blank(),
axis.text.x = element_text(angle = 90, hjust = 1))
} else {
if("May" != M){
x <- ggplot(D_H_M_Y[D_H_M_Y$Month == M & D_H_M_Y$Year == Y,], aes(x=Hour,group =1))+
geom_smooth(aes(y=Consumption), se = FALSE, color = ConsumptionColor, size = 1.1)+
geom_line(aes(y=WP
cof),color = WindColor, size = 1.1)+
scale_y_continuous(
name = "Consumption",
sec.axis=sec_axis(~./cof, name="Wind Power"))+
facet_wrap(Year~Month~Day, nrow=4)+
theme(
axis.title.y = element_text(color = ConsumptionColor, size =13),
axis.title.y.right = element_text(color = WindColor, size =13),
panel.grid=element_blank(),
axis.text.x = element_text(angle = 90, hjust = 1))
print(x)
}
}
}
}

The thing is that I want to look at each observation, like for each months at a give time.
So when I loop & I say when it's may 2014 (and may 2014 is not in the data), the data.frame don't seems to solve this problem. However, for agragate it worked well.