somar colunar e ordenar por estado

[Ronnie]

ano	regiao	sg_estado	id_cbo	renda_mensal_total	total_empregos	total_estabelecimentos
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

Prezados estou começando agora estudar R e preciso da seguinte ajuda, como eu faço para Somar a coluna renda_mensal_total e ordenar por sg_estado.

agradeço a ajuda de todos

[jcblum]

Hi @Ronnie! Welcome!

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

[EconomiCurtis]

The tidyverse packate dplyr has a number of tools for exactly this kind of thing,

Here's the Data Wrangling cheatsheet in Portuguese, many more located here: https://www.rstudio.com/resources/cheatsheets/

For example;

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>

^{Created on 2018-11-19 by the reprex package (v0.2.1)}