Add a first section called Data input, in which you will load the rWSBIM1207 package, use the interroA.csv() function to get the name of a csv file containing test results for a set of students, and read these data into R using read_csv. Display the few first observations and write a short sentence explaining the data.
## install.packages("BiocManager")
## install.packages("remotes")
## BiocManager::install("UCLouvain-CBIO/rWSBIM1207")
library(rWSBIM1207)
##
## This is 'rWSBIM1207' version 0.1.9
interroA.csv()
## [1] "/usr/local/lib/R/site-library/rWSBIM1207/extdata/interroA.csv"
library("tidyverse")
## ── Attaching packages ─────────── tidyverse 1.3.0 ──
## ✓ ggplot2 3.3.0 ✓ purrr 0.3.3
## ✓ tibble 2.1.3 ✓ dplyr 0.8.5
## ✓ tidyr 1.0.2 ✓ stringr 1.4.0
## ✓ readr 1.3.1 ✓ forcats 0.5.0
## ── Conflicts ────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
x <- read_csv(interroA.csv())
## Parsed with column specification:
## cols(
## id = col_character(),
## height = col_double(),
## gender = col_character(),
## X = col_double(),
## interro1 = col_double(),
## interro2 = col_double(),
## interro3 = col_double(),
## interro4 = col_double()
## )
ou
x <- interroA.csv() %>%
read_csv()
## Parsed with column specification:
## cols(
## id = col_character(),
## height = col_double(),
## gender = col_character(),
## X = col_double(),
## interro1 = col_double(),
## interro2 = col_double(),
## interro3 = col_double(),
## interro4 = col_double()
## )
Affichage
x
## # A tibble: 100 x 8
## id height gender X interro1 interro2 interro3 interro4
## <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 A74890 168 M 1.43 16 18 7 10
## 2 A85494 167 M 1.05 15 18 13 NA
## 3 A51820 166 M 0.435 4 10 NA 7
## 4 A98669 164 M 0.715 15 15 18 13
## 5 A75521 171 M 0.917 18 10 17 NA
## 6 A96704 178 F -2.66 11 20 14 17
## 7 A23214 155 M 1.11 12 2 8 14
## 8 A31124 177 M -0.485 19 4 8 20
## 9 A80471 187 F 0.231 19 16 16 8
## 10 A21783 195 F -0.295 13 11 8 20
## # … with 90 more rows