Practical_a: library section

M1_biosciences_dimension_reduction/Practical_a.Rmd

@@ -63,7 +63,7 @@ One of the most widely used tools in big data analysis is the principal componen
 
 ## Loading the libraries
 
-```{r echo=F, message=F}
+```{r echo=T, message=F}
 library(tidyverse) # to manipule data and make plot
 library(factoextra) # manipulate pca results
 library(palmerpenguins) # we load the data
@@ -75,7 +75,7 @@ We are going to work on the famous Palmer penguins dataset. This dataset is an i
 
 The  `palmerpenguins` data contains size measurements for three penguin species observed on three islands in the Palmer Archipelago, Antarctica.
 
-![./img/lter_penguins.png](./img/lter_penguins.png)
+![img/lter_penguins.png](img/lter_penguins.png)
 
 The `palmerpenguins` library load the `penguins` dataset into your R environment. If you are not familiar with `tibble`, you just have to know that they are equivalent to `data.frame`.
 
@@ -123,7 +123,7 @@ If you are not familiar with the `%>%` operator or pipe in R: It takes the outpu
 
 For the sake of this practical, we are going to focus on the continuous variables in the data `bill_length_mm`, `bill_depth_mm`, `flipper_length_mm` and `body_mass_g`.
 
-![./img/culmen_depth.png](./img/culmen_depth.png)
+![img/culmen_depth.png](img/culmen_depth.png)
 
 The function `pairs` renders scatter plots of each possible pairs of variables