A small note: this is an English language forum, so you're more likely to get answers if you can post your questions in that language.
One good place to start learning about how to do this sort of thing is the Data Transformation chapter of the free book R for Data Science: https://r4ds.had.co.nz/transform.html
To give more specific advice, you'll need to explain exactly what sort of calculations you are trying to do here. It sounds like you want to summarize the table, calculating a sum of renda_mensal_total for certain groups. What variables do you want to group by? sg_estado, or something else?
Showing some code you have tried will be very helpful, even if the code doesn't work. Reading this FAQ will help you ask questions here in a way that gets you better, faster answers: FAQ: Tips for writing R-related questions
library(readr)
library(dplyr)
# had to edit your table allow it to be loaded by readr's read_delim:
object <- "ano|regiao|sg_estado|id_cbo|renda_mensal_total|total_empregos|total_estabelecimentos|na
2014|Norte|AC|1112|206042.68|75|8|
2014|Norte|AC|1113|1921101.84|77|2|
2014|Norte|AC|1114|6304959.54|924|82|
2014|Norte|AC|1115|66968|12|4|
2014|Norte|AC|1141|37657.53|4|1|
2014|Norte|AC|1142|1448|1|1|
2014|Norte|AC|1144|19014.49|10|4|
2014|Norte|AC|1210|388895.93|49|37|
2014|Norte|AC|1221|4440.02|2|2|
2014|Norte|AM|3115|514245.27|141|53|
2014|Norte|AM|3116|28076.24|14|4|
2014|Norte|AM|3117|114739.85|115|80|
2014|Norte|AM|3121|4947031.61|1073|231|
2014|Norte|AM|3122|1736391.28|933|30|
2014|Norte|AM|3123|556787.42|235|69|
2014|Norte|AM|3131|8453901.03|1576|445|"
data_frame <- read_delim(object, delim = '|')
data_frame <- data_frame %>%
mutate(
income_mensal_total = total_empregos / 100 # you'd need correct logic here
) %>%
arrange(sg_estado)
data_frame
#> # A tibble: 16 x 9
#> ano regiao sg_estado id_cbo renda_mensal_total total_empregos
#> <int> <chr> <chr> <int> <dbl> <int>
#> 1 2014 Norte AC 1112 206043. 75
#> 2 2014 Norte AC 1113 1921102. 77
#> 3 2014 Norte AC 1114 6304960. 924
#> 4 2014 Norte AC 1115 66968 12
#> 5 2014 Norte AC 1141 37658. 4
#> 6 2014 Norte AC 1142 1448 1
#> 7 2014 Norte AC 1144 19014. 10
#> 8 2014 Norte AC 1210 388896. 49
#> 9 2014 Norte AC 1221 4440. 2
#> 10 2014 Norte AM 3115 514245. 141
#> 11 2014 Norte AM 3116 28076. 14
#> 12 2014 Norte AM 3117 114740. 115
#> 13 2014 Norte AM 3121 4947032. 1073
#> 14 2014 Norte AM 3122 1736391. 933
#> 15 2014 Norte AM 3123 556787. 235
#> 16 2014 Norte AM 3131 8453901. 1576
#> # ... with 3 more variables: total_estabelecimentos <int>, na <chr>,
#> # income_mensal_total <dbl>