Nesta atividade 3, trabalharemos com o conjunto de dados sobre o preço da cesta básica mensal no peíodo de 2016 a 2018, para a capital Campo Grande.
rm(list=ls())
setwd("C:/Users/admin/Dropbox/UFGD/2019_02_Disciplinas/Topicos_Estatistica_R/3_Aula/Dados_Aula_03")
cesta <- readxl::read_xlsx("cesta_basica_campo_grande.xlsx")
Data | Ano | Mes | Preco |
---|---|---|---|
2016-01-01 | 2016 | 1 | 412.61 |
2016-02-01 | 2016 | 2 | 387.87 |
2016-03-01 | 2016 | 3 | 394.04 |
2016-04-01 | 2016 | 4 | 402.89 |
2016-05-01 | 2016 | 5 | 401.63 |
2016-06-01 | 2016 | 6 | 428.73 |
2016-07-01 | 2016 | 7 | 430.37 |
2016-08-01 | 2016 | 8 | 440.86 |
2016-09-01 | 2016 | 9 | 432.27 |
2016-10-01 | 2016 | 10 | 436.51 |
2016-11-01 | 2016 | 11 | 425.78 |
2016-12-01 | 2016 | 12 | 408.06 |
2017-01-01 | 2017 | 1 | 393.25 |
2017-02-01 | 2017 | 2 | 385.38 |
2017-03-01 | 2017 | 3 | 391.95 |
2017-04-01 | 2017 | 4 | 402.19 |
2017-05-01 | 2017 | 5 | 395.11 |
2017-06-01 | 2017 | 6 | 386.68 |
2017-07-01 | 2017 | 7 | 382.17 |
2017-08-01 | 2017 | 8 | 355.09 |
2017-09-01 | 2017 | 9 | 359.24 |
2017-10-01 | 2017 | 10 | 368.83 |
2017-11-01 | 2017 | 11 | 364.33 |
2017-12-01 | 2017 | 12 | 366.26 |
2018-01-01 | 2018 | 1 | 384.26 |
2018-02-01 | 2018 | 2 | 372.79 |
2018-03-01 | 2018 | 3 | 382.47 |
2018-04-01 | 2018 | 4 | 378.40 |
2018-05-01 | 2018 | 5 | 398.14 |
2018-06-01 | 2018 | 6 | 380.18 |
2018-07-01 | 2018 | 7 | 370.59 |
2018-08-01 | 2018 | 8 | 364.66 |
2018-09-01 | 2018 | 9 | 383.77 |
2018-10-01 | 2018 | 10 | 396.80 |
2018-11-01 | 2018 | 11 | 420.80 |
2018-12-01 | 2018 | 12 | 422.88 |
Dica: Ao utilizar o ggplot2, no eixo x, coloque o
Ano como factor:
x = factor(Ano)
require(ggplot2)
## Carregando pacotes exigidos: ggplot2
ggplot(cesta, aes(x = factor(Ano), y = Preco)) +
geom_boxplot() +
scale_x_discrete("Ano", labels = c("2016", "2017", "2018"))
mean(cesta$Preco)
## [1] 394.6622
sd(cesta$Preco)
## [1] 23.45746
(sd(cesta$Preco)/mean(cesta$Preco))*100
## [1] 5.943681
library(e1071)
skewness(cesta$Preco)
## [1] 0.3208858
aggregate(Preco~Ano, data=cesta, FUN=mean)
## Ano Preco
## 1 2016 416.8017
## 2 2017 379.2067
## 3 2018 387.9783
aggregate(Preco~Ano, data=cesta, FUN=sd)
## Ano Preco
## 1 2016 17.80276
## 2 2017 15.72603
## 3 2018 18.50722
quantile(cesta$Preco, c(0.30, 0.90))
## 30% 90%
## 382.32 429.55