Adding Variable Values & County Names using County_ChoroplethR

Question

I've created a country choroplethR to display data and works fine, what I want to do, is add County Names, and a Variable additional Data (Number of Employees) in additional to the Fill on salary data for the choroplethR. Is this possible? The County raw data in the code block isn't hard coded of course it is read into R as a csv but didn't know how else to share.

library(leaflet)
library(ggplot2)
library(ggmap)
library(choroplethr)
library(choroplethrMaps)
library(sp)
library(raster)
library(rgdal)
library(tidyverse)
library(devtools)
library(knitr)
library(dplyr)
library(tmap)
library(tmaptools)
library(sf)
library(RColorBrewer)
library(rio)
library(plyr)

{CNTY   Total_Employees value   region
Arkansas    4   543040.33   5001
Bradley 1   102738.51   5011
Calhoun 1   67475.2 5013
Cleveland   6   481505.92   5025
Drew    1   129700.27   5043
Faulkner    6   707548.2    5045
Garland 4   540568  5051
Grant   45  4525191.89  5053
Hempstead   1   99804.53    5057
Jefferson   313 21032269.84 5069
Lincoln 2   130407.44   5079
Lonoke  11  1213848.15  5085
Miller  2   260067.3    5091
Pope    1   150617.18   5115
Pulaski 229 33095240.96 5119
Saline  45  5975793.76  5125
Washington  1   130187.05   5143
Ashley  0   0   5003
Baxter  0   0   5005
Benton  0   0   5007
Boone   0   0   5009
Carroll 0   0   5015
Chicot  0   0   5017
Clark   0   0   5019
Clay    0   0   5021
Cleburne    0   0   5023
Columbia    0   0   5027
Conway  0   0   5029
Craighead   0   0   5031
Crawford    0   0   5033
Crittenden  0   0   5035
Cross   0   0   5037
Dallas  0   0   5039
Desha   0   0   5041
Franklin    0   0   5047
Fulton  0   0   5049
Greene  0   0   5055
Hot Spring  0   0   5059
Howard  0   0   5061
Independence    0   0   5063
Izard   0   0   5065
Jackson 0   0   5067
Johnson 0   0   5071
Lafayette   0   0   5073
Lawrence    0   0   5075
Lee 0   0   5077
Little River    0   0   5081
Logan   0   0   5083
Madison 0   0   5087
Marion  0   0   5089
Mississippi 0   0   5093
Monroe  0   0   5095
Montgomery  0   0   5097
Nevada  0   0   5099
Newton  0   0   5101
Ouachita    0   0   5103
Perry   0   0   5105
Phillips    0   0   5107
Pike    0   0   5109
Poinsett    0   0   5111
Polk    0   0   5113
Prairie 0   0   5117
Randolph    0   0   5121
St Francis  0   0   5123
Scott   0   0   5127
Searcy  0   0   5129
Sebastian   0   0   5131
Sevier  0   0   5133
Sharp   0   0   5135
Stone   0   0   5137
Union   0   0   5139
Van Buren   0   0   5141
White   0   0   5145
Woodruff    0   0   5147
Yell    0   0   5149}

AR_Cnty <- read.csv("C:/AR_CntyData.csv", header =TRUE, sep = ',')
AR_Cnty1 <- AR_Cnty[,c(3:4)]

AR_Map <- county_choropleth(AR_Cnty1, 
                   title = "Economic Impact 2022 by County",
                   state_zoom = "arkansas",
                   num_colors = 9) 


AR_Map