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Refactor code to use forward-pipe operator for better readability and consistency

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Arthur Danjou
2026-01-27 17:19:44 +01:00
parent 4697570bcc
commit 5d0c1d2b4e
6 changed files with 82 additions and 84 deletions
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10
M2/Data Visualisation/Project/NoticeTechnique.Rmd
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@@ -185,9 +185,9 @@ cor_mat <- cor(vars_candidates, use = "pairwise.complete.obs")
```
```{r}
cor_df <- as.data.frame(cor_mat) %>%
tibble::rownames_to_column(var = "Var1") %>%
pivot_longer(-Var1, names_to = "Var2", values_to = "r") %>%
cor_df <- as.data.frame(cor_mat) |>
tibble::rownames_to_column(var = "Var1") |>
pivot_longer(-Var1, names_to = "Var2", values_to = "r") |>
mutate(
Var1 = factor(Var1, levels = unique(Var1)),
Var2 = factor(Var2, levels = rev(unique(Var1)))
@@ -503,7 +503,9 @@ Bien que nous ayons appliqué une transformation logarithmique pour corriger l'a
Nous appliquons donc une standardisation (Z-score) : $z = \frac{x - \mu}{\sigma}$
```{r}
data_scaled <- tb_ready |> select(log_inc, log_mort) |> scale()
data_scaled <- tb_ready |>
select(log_inc, log_mort) |>
scale()
check_table <- data.frame(
Variable = c("Incidence (Log)", "Mortalité (Log)"),

16
M2/Data Visualisation/Project/app.R
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@@ -43,13 +43,11 @@ ui <- shinydashboard::dashboardPage(
tabName = "methodo",
icon = icon("info-circle")
),
menuItem(
"Vue d'Ensemble",
tabName = "dashboard",
icon = icon("dashboard")
),
menuItem("Données Brutes", tabName = "data", icon = icon("table")),
# Footer - Informations et crédits
@@ -66,7 +64,6 @@ ui <- shinydashboard::dashboardPage(
)
)
),
hr(),
# Filtre par Région
@@ -147,7 +144,6 @@ ui <- shinydashboard::dashboardPage(
plotlyOutput("cluster_scatter", height = "530px")
)
),
fluidRow(
# Plot des tendances
box(
@@ -190,7 +186,6 @@ ui <- shinydashboard::dashboardPage(
# Page 3 - Méthodologie
tabItem(
tabName = "methodo",
fluidRow(
# Indicateurs OMS
box(
@@ -307,7 +302,6 @@ ui <- shinydashboard::dashboardPage(
p("Dernière mise à jour du dataset : Octobre 2024.")
),
),
column(
width = 6,
box(
@@ -319,7 +313,6 @@ ui <- shinydashboard::dashboardPage(
p(
"Afin de synthétiser l'information et de faciliter la prise de décision, j'ai appliqué un algorithme d'apprentissage non supervisé (K-Means) pour regrouper les pays ayant des profils épidémiques similaires sous 4 clusters."
),
h4("Méthodologie"),
tags$ul(
tags$li(
@@ -335,7 +328,6 @@ ui <- shinydashboard::dashboardPage(
"Utilisation de `set.seed(123)` pour garantir la reproductibilité des résultats."
)
),
h4("Interprétation des 3 Groupes"),
# Tableau des Groupes
@@ -395,7 +387,6 @@ ui <- shinydashboard::dashboardPage(
status = "primary",
solidHeader = TRUE,
width = 12,
tags$p(
"Ce projet suit une approche Open Science.",
style = "font-style: italic;"
@@ -403,7 +394,6 @@ ui <- shinydashboard::dashboardPage(
tags$p(
"L'intégralité du code source (Rmd, App) ainsi que la notice technique (PDF) sont disponibles en libre accès sur le dépôt GitHub."
),
tags$a(
href = "https://go.arthurdanjou.fr/datavis-code",
target = "_blank",
@@ -524,7 +514,9 @@ server <- function(input, output, session) {
# KPI - Pire pays
output$kpi_worst_country <- shinydashboard::renderValueBox({
data <- filtered_data()
worst <- data |> arrange(desc(e_inc_100k)) |> slice(1)
worst <- data |>
arrange(desc(e_inc_100k)) |>
slice(1)
if (nrow(worst) > 0) {
valueBox(
@@ -743,7 +735,7 @@ server <- function(input, output, session) {
output$cluster_scatter <- plotly::renderPlotly({
data <- filtered_data()
sel_iso <- selected_country()
highlight_data <- data %>% filter(iso3 == sel_iso)
highlight_data <- data |> filter(iso3 == sel_iso)
p <- ggplot(data, aes(x = e_inc_100k, y = e_mort_exc_tbhiv_100k)) +
geom_point(

2
M2/Data Visualisation/Project/renv.lock
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@@ -2056,7 +2056,7 @@
"Type": "Package",
"Title": "A Forward-Pipe Operator for R",
"Authors@R": "c( person(\"Stefan Milton\", \"Bache\", , \"stefan@stefanbache.dk\", role = c(\"aut\", \"cph\"), comment = \"Original author and creator of magrittr\"), person(\"Hadley\", \"Wickham\", , \"hadley@posit.co\", role = \"aut\"), person(\"Lionel\", \"Henry\", , \"lionel@posit.co\", role = \"cre\"), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"), comment = c(ROR = \"03wc8by49\")) )",
"Description": "Provides a mechanism for chaining commands with a new forward-pipe operator, %>%. This operator will forward a value, or the result of an expression, into the next function call/expression. There is flexible support for the type of right-hand side expressions. For more information, see package vignette. To quote Rene Magritte, \"Ceci n'est pas un pipe.\"",
"Description": "Provides a mechanism for chaining commands with a new forward-pipe operator, |>. This operator will forward a value, or the result of an expression, into the next function call/expression. There is flexible support for the type of right-hand side expressions. For more information, see package vignette. To quote Rene Magritte, \"Ceci n'est pas un pipe.\"",
"License": "MIT + file LICENSE",
"URL": "https://magrittr.tidyverse.org, https://github.com/tidyverse/magrittr",
"BugReports": "https://github.com/tidyverse/magrittr/issues",