Diretrizes gerais:

  1. Baixe o arquivo .Rmd e abra no RStudio.

Arquivo

install.packages(tidyverse) install.packages(tinytex) install.packages(knitr) install.packages(flexdashboard) install.packages(xaringan) install.packages(xaringanthemer)

  1. Chame as bibliotecas dos pacotes instalados
  library("tidyverse")
## Warning: package 'tidyverse' was built under R version 4.1.2
## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --
## v ggplot2 3.3.5     v purrr   0.3.4
## v tibble  3.1.3     v dplyr   1.0.7
## v tidyr   1.1.3     v stringr 1.4.0
## v readr   2.0.1     v forcats 0.5.1
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()
  library("tinytex")
## Warning: package 'tinytex' was built under R version 4.1.2
  library("knitr")
  library("flexdashboard")
## Warning: package 'flexdashboard' was built under R version 4.1.2
  library("xaringan")
## Warning: package 'xaringan' was built under R version 4.1.2
  library("xaringanthemer")

  1. Corrija os problemas de códigos nos respectivos chunks.

  2. Rode o arquivo .Rmd por meio do ícone knitr

  3. Salve o .Rmd e submeta-o por meio da tarefa no Sigaa.

Dica: As barras que delimitam o endereçamento do arquivo no seu computador, quando exibidas no explorer do Windows, são invertidas (). O R trabalha com barras normais (/) para endereçamento.

Preparação para o exercício:

Carregue o data frame mtcars

data(mtcars)

Encontre o erro em todos os códigos abaixo, corrija-os e rode o script:

Q1)

head(mtcars)
##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

Q2)

str(mtcars)
## 'data.frame':    32 obs. of  11 variables:
##  $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
##  $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
##  $ disp: num  160 160 108 258 360 ...
##  $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
##  $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
##  $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
##  $ qsec: num  16.5 17 18.6 19.4 17 ...
##  $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
##  $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
##  $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
##  $ carb: num  4 4 1 1 2 1 4 2 2 4 ...

Q3)

dim(mtcars)
## [1] 32 11

Q4)

names(mtcars)
##  [1] "mpg"  "cyl"  "disp" "hp"   "drat" "wt"   "qsec" "vs"   "am"   "gear"
## [11] "carb"

Q5)

head(mtcars, 7)
##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1
## Duster 360        14.3   8  360 245 3.21 3.570 15.84  0  0    3    4

Q6)

v1 <- c("pato", "cachorro", "minhoca", "lagarto")

Q7)

v2 <- c("1", "2", "3", "4")
v1[5] <- c("gaivota")

Q8)

v1 <- c("pato", "cachorro", "minhoca", "lagarto")

Q9)

v3 <- c(33, 31, 40, 25, 27, 40)

Q10)

v1 <- c("pato", "cachorro", "minhoca", "lagarto")

Q11)

v1 <- c("pato", "cachorro", "minhoca", "lagarto")

Q12)

v3 <- c(33, 31, 40, 25, 27, 40)

Q13)

v1 <- c("pato", "cachorro", "minhoca", "lagarto", NA, "")
v3 <- c(33, 31, 40, 25, 27, 40)
myData <- data.frame(v1, v3)

Q14)

v1 <- c("pato", "cachorro", "minhoca", "lagarto")
v4 <- c(33, 31, 40, 25)
myData2 <- data.frame(v1,v4)
names(myData2) <- c("animal", "idade")

Q15)

ls()
## [1] "mtcars"  "myData"  "myData2" "v1"      "v2"      "v3"      "v4"

Q16)

v1 <- c("pato", "cachorro", "minhoca", "lagarto")
sum(v4)
## [1] 129