diff --git a/student_reports.html b/student_reports.html deleted file mode 100644 index 7be6ab14778873bc5bd41183ce97e52d6ee38eae..0000000000000000000000000000000000000000 --- a/student_reports.html +++ /dev/null @@ -1,483 +0,0 @@ - - - - -
- - - - - - - - - -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
-