Dados disponíveis aqui Temperatura

dica: Control + Shift + M -> operador pipe

library('dplyr')

# ver os arquivos do diretório
list.files()
[1] "est_desc.nb.html" "est_desc.Rmd"     "est_desc.Rproj"   "temperatura.csv" 
# ler os dados
dados <- read.csv('temperatura.csv') 

dados
#agrupar
group_by(dados,ano,mes)  # tranforma o objeto data frame em objeto tibble

0 %>% cos() # operador pipe
[1] 1
dados <- read.csv('temperatura.csv') %>%
         group_by(ano,mes)   # ler e agrupar
dados
dados <- read.csv('temperatura.csv') %>%
         group_by(ano,mes)%>% 
         summarise(media=mean(t.ar, na.rm = TRUE), 
                   mediana=median(t.ar), 
                   desvpad=sd(t.ar),
                   maximo=max(t.ar), 
                   minimo= min(t.ar),
                   p.25=quantile(t.ar,probs = .25),
                   p.75=quantile(t.ar,probs = .75))
`summarise()` regrouping output by 'ano' (override with `.groups` argument)
dados
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