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Refactor code for improved readability and consistency across R Markdown files

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- Updated comments and code formatting in `3-td_ggplot2 - enonce.Rmd` for clarity.
- Enhanced code structure in `4-td_graphiques - enonce.Rmd` by organizing options and library calls.
- Replaced pipe operator `%>%` with `|>` in `Code_Lec3.Rmd` for consistency with modern R syntax.
- Cleaned up commented-out code and ensured consistent spacing in ggplot calls.
This commit is contained in:
Arthur Danjou
2025-11-06 09:26:58 +01:00
parent 8f5f2b417c
commit 03bf0a4db2
10 changed files with 764 additions and 588 deletions
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20
M1/General Linear Models/TP2-bis/TP2.Rmd
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@@ -1,5 +1,5 @@
```{r}
setwd('/Users/arthurdanjou/Workspace/studies/M1/General Linear Models/TP2-bis')
setwd("/Users/arthurdanjou/Workspace/studies/M1/General Linear Models/TP2-bis")
library(tidyverse)
library(GGally)
@@ -10,9 +10,9 @@ library(qqplotr)
options(scipen = 999, digits = 5)
```
```{r}
data <- read.csv('data02.csv', sep = ',', header = TRUE, dec = ".")
data %>%
mutate(type = factor(type, levels = c("maths", "english", "final"), labels = c("maths", "english", "final"))) %>%
data <- read.csv("data02.csv", sep = ",", header = TRUE, dec = ".")
data |>
mutate(type = factor(type, levels = c("maths", "english", "final"), labels = c("maths", "english", "final"))) |>
ggplot(aes(x = note)) +
facet_wrap(vars(type), scales = "free_x") +
geom_histogram(binwidth = 4, color = "black", fill = "grey80") +
@@ -21,8 +21,8 @@ data %>%
```
```{r}
data_wide <- pivot_wider(data, names_from = type, values_from = note)
data_wide %>%
select(-id) %>%
data_wide |>
select(-id) |>
ggpairs() + theme_bw(14)
```
```{r}
@@ -67,12 +67,12 @@ linearHypothesis(model, "maths - english = 0")
# Submodel testing
```{r}
data_predict <- predict(model, newdata = expand.grid(maths = seq(70, 90, 2), english = c(75, 85)), interval = "confidence") %>%
as_tibble() %>%
data_predict <- predict(model, newdata = expand.grid(maths = seq(70, 90, 2), english = c(75, 85)), interval = "confidence") |>
as_tibble() |>
bind_cols(expand.grid(maths = seq(70, 90, 2), english = c(75, 85)))
data_predict %>%
mutate(english = as.factor(english)) %>%
data_predict |>
mutate(english = as.factor(english)) |>
ggplot(aes(x = maths, y = fit, color = english, fill = english, label = round(fit, 1))) +
geom_ribbon(aes(ymin = lwr, ymax = upr), alpha = 0.2, show.legend = FALSE) +
geom_point(size = 2) +