R - Iterate through a Data Frame using for Loop - r

Question

I am trying to generate the below series (see attached image) based on the logic given below. I was able create the series for one product and store (code given below). i am having trouble when i try to generalize this for multiple product store combinations. Could you please advise if there is an easier way to do this.
Logic
a given
b lag of d by 4
c initial c for first week thereafter (c previous row + b current - a current)
d initial d - c current
my code
library(dplyr)
df = structure(list(
Product = c(11078931, 11078931, 11078931, 11078931, 11078931,
11078931, 12021216, 12021216, 12021216, 12021216,
12021216, 12021216, 10932270, 10932270, 10932270,
10932270, 10932270),
STORE = c(90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 547, 547,
547, 547, 547),
WEEK = c(201627, 201628, 201629, 201630, 201631, 201632, 201627, 201628,
201629, 201630, 201631, 201632, 201627, 201628, 201629, 201630,
201631),
WEEK_SEQ = c(914, 915, 916, 917, 918, 919, 914, 915, 916, 917, 918, 919,
914, 915, 916, 917, 918),
a = c(9.161, 9.087, 8.772, 8.698, 7.985, 6.985, 0.945, 0.734, 0.629, 0.599,
0.55, 0.583, 5.789, 5.694, 5.488, 5.47, 5.659),
initial_d = c(179, 179, 179, 179, 179, 179, 18, 18, 18, 18, 18, 18, 37, 37,
37, 37, 37),
Initial_c = c(62, 0, 0, 0, 0, 0, 33, 0, 0, 0, 0, 0, 59, 0, 0, 0, 0)
),
.Names = c("Product", "STORE", "WEEK", "WEEK_SEQ", "a", "initial_d",
"Initial_c"),
class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -17L))
# filter to extract one product and store
# df = df %>% filter(Product == 11078931) %>% filter(STORE == 90)
df$b = 0
df$c = 0
df$d = NA
c_init = 62
d_init = 179
df$d <- d_init
df$c[1] <- c_init
RQ <- function(df,...){
for(i in seq_along(df$WEEK_SEQ)){
if(i>4){
df[i, "b"] = round(df[i-4,"d"], digits = 0)# Calculate b with the lag
}
if(i>1){
df[i, "c"] = round(df[i-1, "c"] + df[i, "b"] - df[i, "a"], digits = 0) # calc c
}
df[i, "d"] <- round(d_init - df[i, "c"], digits = 0) # calc d
if(df[i, "d"] < 0) {
df[i, "d"] <- 0 # reset negative d values
}
}
return(df)
}
df = df %>% group_by(SKU_CD, STORE_CD) %>% RQ(df)
Expected output series
could you please advice what is wrong in my code. this code works fine for one product and store combination. but for multiple product and store it doesn't. thanks for your time and input!

Answer 1

Consider base R's by which subsets the input dataframe by each combination of factor types to return a list of the subsetted dataframes. Then, run a do.call(rbind, ...) to row bind the list into one final dataframe.
RQ_dfs <- by(df, df[c("Product", "STORE")], FUN=RQ)
finaldf <- do.call(rbind, RQ_dfs)
While I cannot achieve your outputted series screenshot with posted data, the filtered commented out pairing does show up finaldf:
# # A tibble: 17 × 10
# Product STORE WEEK WEEK_SEQ a initial_d Initial_c b c d
# * <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 11078931 90 201627 914 9.161 179 62 0 62 117
# 2 11078931 90 201628 915 9.087 179 0 0 53 126
# 3 11078931 90 201629 916 8.772 179 0 0 44 135
# 4 11078931 90 201630 917 8.698 179 0 0 35 144
# 5 11078931 90 201631 918 7.985 179 0 117 144 35
# 6 11078931 90 201632 919 6.985 179 0 126 263 0
# 7 12021216 90 201627 914 0.945 18 33 0 0 179
# 8 12021216 90 201628 915 0.734 18 0 0 -1 180
# 9 12021216 90 201629 916 0.629 18 0 0 -2 181
# 10 12021216 90 201630 917 0.599 18 0 0 -3 182
# 11 12021216 90 201631 918 0.550 18 0 179 175 4
# 12 12021216 90 201632 919 0.583 18 0 180 354 0
# 13 10932270 547 201627 914 5.789 37 59 0 0 179
# 14 10932270 547 201628 915 5.694 37 0 0 -6 185
# 15 10932270 547 201629 916 5.488 37 0 0 -11 190
# 16 10932270 547 201630 917 5.470 37 0 0 -16 195
# 17 10932270 547 201631 918 5.659 37 0 179 157 22