Average by group for 'n' number of rows per group - R

I have a dataframe with three columns; entity, date, value.

First I must order the ‘value’ based on ‘Descending order of ‘DATE” per entity.

Then,the requirement is to get 2 types of averages per entity based on the user defined number of rows. For example, if user enters 3 and 6; it means that ‘give me the average of first 3 values and then average of next 6 values‘ per entity.

for the given dataset, result would be a data frame as:

    Entity    Avg3 Avg6
        A     110   65 
        B     220  130

I can use ‘aggregate‘ function to get ‘mean‘ by entity but I am not able to extract specific rows data per entity.
Also, ordering the dataframe based on entity and then ‘date’ seems to not work.

#order data based on date (tried adding entity here but it does not work)
df_new <- df[rev(order(as.Date(df$Date)))),]

here is the dput:

structure(list(Wells = c("A", "A", "A", "A", "A", "A", "A", "A", 
"A", "A", "A", "A", "B", "B", "B", "B", "B", "B", "B", "B", "B", 
"B", "B", "B"), Date = structure(c(1577836800, 1577923200, 1578009600, 
1578096000, 1578182400, 1578268800, 1578355200, 1578441600, 1578528000, 
1578614400, 1578700800, 1578787200, 1577836800, 1577923200, 1578009600, 
1578096000, 1578182400, 1578268800, 1578355200, 1578441600, 1578528000, 
1578614400, 1578700800, 1578787200), class = c("POSIXct", "POSIXt"
), tzone = "UTC"), Index = c(10, 20, 30, 40, 50, 60, 70, 80, 
90, 100, 110, 120, 20, 40, 60, 80, 100, 120, 140, 160, 180, 200, 
220, 240)), row.names = c(NA, -24L), class = c("tbl_df", "tbl", 
"data.frame"))

library(dplyr)
library(stringr)
n1 <- 3
n2 <- 6
df %>%
    arrange(Wells, desc(Date)) %>% 
    group_by(Wells) %>%
    slice_head(n = n1 + n2) %>%
    summarise(!! str_c('Avg', n1) := mean(head(Index, n1)), 
              !! str_c('Avg', n2)  := mean(tail(Index, n2)), .groups = 'drop')

# A tibble: 2 x 3
#  Wells  Avg3  Avg6
#  <chr> <dbl> <dbl>
#1 A       110    65
#2 B       220   130

df1 <- df[order(df$Wells, -as.numeric(df$Date)),]
out <- do.call(data.frame, aggregate(Index ~ Wells, 
       subset(df1, ave(seq_along(Wells), 
         Wells, FUN = seq_along) <= (n1 + n2)), FUN = function(x)
        c(Avg3 = mean(head(x, n1)), Avg6 = mean(tail(x, n2)))))

library(dplyr)
n <- c(3, 6)

df %>%
  arrange(Wells, desc(Date)) %>%
  group_by(Wells) %>%
  group_by(grp = findInterval(row_number(), cumsum(n), left.open = TRUE), .add = TRUE) %>%
  #For older dplyr version use add = TRUE
  #group_by(grp = findInterval(row_number(), cumsum(n), left.open = TRUE), add = TRUE) %>%
  summarise(Index = mean(Index)) %>%
  slice(seq_along(n)) %>%
  mutate(grp = paste0('avg', n)) %>%
  tidyr::pivot_wider(names_from = grp, values_from = Index)

#  Wells  avg3  avg6
#  <chr> <dbl> <dbl>
#1 A       110    65
#2 B       220   130