I need help accessing a value in a tibble by name

I need to use the value from count() by name and not by position due to the dynamic nature of the source data.

I am trying to estimate the labor cost to re-ip devices based on existing ip assignment state.

Example:
a device with a state of Active will be $40.00
a device with a state of ActiveReservation will be $100.00

For the first example below:
6,323 * $10
For the second example below:
9 * $10

I can get them by

temp_dhcp_count$quantity[1] * 10

however I cant guarantee that [1] is the position and always "Active", I need to be able to call it by name "Active"

My assumption was, if I could extract them to values I could:

> Active = 6323
> Active * 10
[1] 63230

vs

temp_dhcp_count$quantity[1] * 10

For example:

> temp_dhcp_count
# A tibble: 5 x 2
# Groups:   AddressState [5]
  AddressState        quantity
  <chr>                  <int>
1 Active                  6323
2 ActiveReservation       1222
3 Declined                  10
4 Expired                   12
5 InactiveReservation      287

> temp_dhcp_count$quantity[1]
[1] 6323

and

> temp_dhcp_count
# A tibble: 3 x 2
# Groups:   AddressState [3]
  AddressState        quantity
  <chr>                  <int>
1 Active                     9
2 ActiveReservation         46
3 InactiveReservation      642

> temp_dhcp_count$quantity[1]
[1] 9

I tried asking how to extract rows from a tibble as key value pairs and now I am trying to ask this way based on feedback.
How do you change the output of count from a tibble to Name Value pairs?

The source data is a tsv that I import and select based on subnet and count by state.

library(tidyverse)
library(ipaddress)
dhcp <- read_delim("dhcpmerge.tsv.txt", 
                   delim = "\t", escape_double = FALSE, 
                   trim_ws = TRUE)

dhcp <- distinct(dhcp)

network_in_review = "10.75.0.0/16"

temp_dhcp <- dhcp %>%
  select(IPAddress, AddressState, HostName) %>%
  filter(is_within(ip_address(IPAddress), ip_network(network_in_review)))

temp_dhcp %>% 
  group_by(AddressState) %>% 
  count(name = "quantity") -> temp_dhcp_count

temp_dhcp_count

>Solution :

You can create a named list. With the sample data

temp_dhcp_count <- read.table(text="
AddressState        quantity
Active                  6323
ActiveReservation       1222
Declined                  10
Expired                   12
InactiveReservation      287", header=TRUE)

You can create a named list of values to extract them by name

vals <- with(temp_dhcp_count, setNames(as.list(quantity), AddressState))
vals$Active
# [1] 6323
vals$Declined
# [1] 10

And if the vals$ part bothers you, you can use with() again

with(vals, {
   Active * 10 - Declined * 2
})
# [1] 63210