Working across two dataframes: Apply or for-loop? - r

Question

I have two dataframes and one function. The function is supposed to take the variables start_month & end_month, select for each row the values in the second dataframe in the month-column, calculate the rate_of_change between each start_month and end_month variable in a given year. Finally calculate the mean(rate_of_change) and place it into the first dataframe as a new variable in the vector average_ratio.
So far I've created a code that calculates the average ratio, but I can't manage to put it into a for loop or an apply function so that the loop runs through the whole first data frame. I have two ideas, but they don't work so far.
structure(Total) # Df containing total combinations of all existing month starting in September
.
i | start_month | end_month | average_ratio (expected output)
1 | 9 | 10 | -23
2 | 9 | 11 | 13
3 | 9 | 12 | -4
4 | 9 | 1 |
5 | 9 | 2 | # ... with 61 more rows
and
structure(Cologne)
# A tibble: 3,000 x 4
year month price town (rate of change)
<dbl> <dbl> <dbl> <chr>
1 1531 7 7575 Cologne
2 1531 8 588 Cologne
3 1531 9 615 Cologne
4 1531 10 69 Cologne -88%
5 1531 11 712 Cologne
6 1531 12 590 Cologne
7 1532 1 72 Cologne
8 1532 2 675 Cologne
9 1532 3 6933 Cologne
10 1532 4 54 Cologne
11 1532 5 425 Cologne
12 1532 6 12 Cologne
13 1532 7 323 Cologne
14 1532 8 32 Cologne
15 1532 9 58 Cologne
16 1532 10 84 Cologne 42%
# ... with 2,990 more rows
# rate of change function
rateofchange <- function(x,y) {
((x-y)/y)*100
}
# avg_ratio function
avg_ratio <- function(x,y,z) {
dt.frame <- filter(x, month==y | month==z)
pre_p <- lag(dt.frame$price, 1)
dt.frame <- cbind(dt.frame, pre_p)
for (i in 1:nrow(dt.frame)) {
dt.frame$roc <- rateofchange(dt.frame$price,dt.frame$pre_p)
}
result <- mean(dt.frame$roc,na.rm=TRUE)
return(result)
}
May_Aug <- avg_ratio(Cologne, 5,7)
################ works until here ################
# Now, Idea 1
Total <- Total %>%
mutate(Total, ratio = avg_ratio(Cologne,Total$start_mth,Total$end_mth)
)
Warning messages:
1: In month == y :
longer object length is not a multiple of shorter object length
2: In month == z :
longer object length is not a multiple of shorter object length
# and Idea 2
ratio <- c()
Total_new <- for(i in 1:nrow(Total)) {
ratio [i] <- c(ratio, avg_ratio(Cologne,Total$start_mth[i],Total$end_mth[i]))
return(cbind(Total,ratio))
}
> dput(Cologne[1:20,])
structure(list(year = c(1531, 1531, 1531, 1531, 1531, 1531, 1532,
1532, 1532, 1532, 1532, 1532, 1532, 1532, 1532, 1532, 1532, 1532,
1533, 1533), month = c(7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6,
7, 8, 9, 10, 11, 12, 1, 2), price = c(7575, 588, 615, 69, 712,
72, 72, 675, 6933, 70, 656, 66, 62, 48, 48, 462, 45, 45, 456,
46), town = c("Cologne", "Cologne", "Cologne", "Cologne", "Cologne",
"Cologne", "Cologne", "Cologne", "Cologne", "Cologne", "Cologne",
"Cologne", "Cologne", "Cologne", "Cologne", "Cologne", "Cologne",
"Cologne", "Cologne", "Cologne")), spec = structure(list(cols = list(
Jahr = structure(list(), class = c("collector_double", "collector"
)), Monat = structure(list(), class = c("collector_double",
"collector")), cologne_wheat_monthly = structure(list(), class = c("collector_number",
"collector"))), default = structure(list(), class = c("collector_guess",
"collector")), skip = 1), class = "col_spec"), row.names = c(NA,
20L), class = c("tbl_df", "tbl", "data.frame"))
> dput(Total) structure(list(start_mth = c(9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 6, 6, 7), end_mth = c(10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 12, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 2, 3, 4, 5, 6, 7, 8, 3, 4, 5, 6, 7, 8, 4, 5, 6, 7, 8, 5, 6, 7, 8, 6, 7, 8, 7, 8, 8)), class = "data.frame", row.names = c(NA, -66L))

Answer 1

You can do:
Total$average_ratio <- mapply(avg_ratio, y = Total$start_mth, z = Total$end_mth, MoreArgs = list(x = cologne))
Your function is not vectorized, that's why this doesn't work:
Total <- Total %>%
mutate(ratio = avg_ratio(cologne, start_mth, end_mth))
The mapply() function iterates (or vectorizes) through the arguments provided, you don't want to iterate over cologne however, that's why you pass it inside MoreArgs = , so it gets taken as it is.