Selections based on vector elements - r

Question

Im extremely new, sorry ahead of time. I have two vectors, one a character vector of account names (30) and the other a character vector of product names(30). Lastly, I have a dataframe with three columns account names, product names and revenue but this list goes way beyond the 30 of either.
Ultimately I need a 30x30 dataframe rows as products from the product name vector, columns as account names from the account name vector and the values as the revenue associated with the account in the column and the product in the row.
I think I need a nested loop function? but I dont know how to use that to populate the dataframe appropriately.
account<-c("a","b",etc)
product<-c("prod_a","prod_b", etc)
for(i in 1:length(account)){
for(i in 1:length(product)){
.....
}
}
Honestly Im just very lost haha

Answer 1

I think I know what you're trying to do here. I suspect there is a good reason you want this 30x30 cross-table type of structure, but I would also like to take the opportunity to encourage "tidy" data for analysis purposes. That link can be summarized by these three main criteria for data to be considered "tidy":
Each variable forms a column.
Each observation forms a row.
Each type of observational unit forms a table.
That said, below is my attempt to interpret and demonstrate what I think you're trying to accomplish.
library(tidyr)
# set up some fake data to better explain
account_vec <- paste0(letters, 1:26)
product_vec <- paste0(as.character(101:126), LETTERS)
revenue_vec <- rnorm(26*26)
# permutating accounts and products to set up our fake data
df <- expand.grid(account_vec, product_vec)
names(df) <- c("accounts", "products")
df$revenue <- revenue_vec
# if this is what your data looks like currently, I would consider this fairly "tidy"
# now let's pretend there's some data we need to filter out
df <- rbind(df,
data.frame(
accounts = paste0("bad_account", 1:3),
products = paste0("bad_product", 1:3),
revenue = rnorm(3)
)
)
# filter to just what is included in our "accounts" and "products" vectors
df <- df[df$accounts %in% account_vec, ]
df <- df[df$products %in% product_vec, ]
# spread out the products so they occupy the column values
df2 <- df %>% tidyr::spread(key="products", value="revenue")
# if you aren't familiar with the "%>%" pipe operator, the above
# line of code is equivalent to this one below:
# df2 <- tidyr::spread(df, key="products", value="revenue")
# now we have accounts as rows, products as columns, and revenues at the intersection
# we can go one step further by making the accounts our row names if we want
row.names(df2) <- df2$accounts
df2$accounts <- NULL
# now the accounts are in the row name and not in a column on their own