#Ler os arquivos das planilhas Excel.

library(readxl)

vendas <- read_excel("Vendas2024.xlsx")

salario_base <- read_excel("Salario_base2024.xlsx")

venda_mes <- vendas  %>%
  group_by(ano ,mes) %>%
  summarise(venda_mensal = sum(venda_diaria)) %>%
  arrange(ano, mes)
## `summarise()` has grouped output by 'ano'. You can override using the `.groups`
## argument.

Graficos

plot(venda_mes$venda_mensal)

vendas_mes_ts <- ts(venda_mes$venda_mensal, start = c(2018,1), frequency = 12)
plot(vendas_mes_ts)

decomp_vendas_mes <- decompose(vendas_mes_ts, type = 'additive')
plot(decomp_vendas_mes)

forecast(vendas_mes_ts , 6, 90)
##          Point Forecast    Lo 90    Hi 90
## Apr 2024       592128.1 508364.8 675891.4
## May 2024       677756.0 563531.7 791980.3
## Jun 2024       626941.9 488818.4 765065.3
## Jul 2024       546903.3 388445.2 705361.4
## Aug 2024       546792.1 370327.1 723257.0
## Sep 2024       543842.9 351045.7 736640.1
plot(forecast(vendas_mes_ts , 6, 90))