I am going to start with an example:

```
tibble::tribble(
~Date, ~Material, ~Quantity,
"2020-01-01", "nails", 10L,
"2020-01-01", "nails", 100L,
"2020-02-02", "nails", 50L,
"2020-02-02", "nails", 70L,
"2020-01-01", "hammer", 20L,
"2020-01-01", "hammer", 80L,
"2020-02-02", "hammer", 20L,
"2020-02-02", "hammer", 50L
)
```

This is the example data set. The original data set is way longer with 100+ items and dates.

- First I subset data for one day
- Sum all item quantity in that day
- Divide each item quantity with the sum(from previous step), lets call the result weight
- multiply each items quantity with the corresponding weight and sum the results for each item.
- Divide result from step 4 with the sum of all weights.
- Repeat for all days.

The result from the example should be:

- First all items in day 2020-01-01
- 10 + 100 + 20 + 80 = 210
- 10/210 = 0.048, 100/210 = 0.48, 20/210 = 0.095, 80/210 = 0.38
- 10 * 0.048 + 100 * 0.48 + 20 * 0.095 + 80 * 0.38 = 0.48 + 48 + 1.9 + 30.4 = 80.78
- 80.78/(0.048 + 0.48 + 0.095 + 0.38) = 80.78/1.003 = 80.54
- And the same process for 2020-02-02

I though that maybe its doable with a for loop, this is how far I got and now I am stuck:

```
inv <- read.csv("Book1.csv")
inv$Date <- as.Date(inv$Date)
n <- unique(inv$Date)
item <- vector()
length(n)
for (i in 1:length(n)){
day <- subset(inv, subset = (Date == n[i]))
day_total <- sum(day$Quantity)
m <- unique(day$Material)
for (j in 1:length(m)){
material <- subset(day, subset = (Material == m[j]))
material_total <- sum(material$Quantity)
material_weight <- material_total/day_total
item[j] <- material_total/day_total
}
}
```

If you have any suggestion it will be greatly appreciated