removing unneeded code

Author: leem44

clustering.Rmd

@@ -439,7 +439,7 @@ There each row corresponds to an iteration,
 where the left column depicts the center update, 
 and the right column depicts the reassignment of data to clusters.
 
-(ref:10-toy-kmeans-iter) First four iterations of K-means clustering on the `penguin_data` example data set. Each pair of plots corresponds to an iteration. Within the pair, the left column depicts the center update, and the right column depicts the reassignment of data to clusters. Cluster centers are indicated by larger points that are outlined in black.
+(ref:10-toy-kmeans-iter) First four iterations of K-means clustering on the `penguin_data` example data set. Each pair of plots corresponds to an iteration. Within the pair, the first plot depicts the center update, and the second plot depicts the reassignment of data to clusters. Cluster centers are indicated by larger points that are outlined in black.
 
 ```{r 10-toy-kmeans-iter, echo = FALSE, warning = FALSE, fig.height = 4.5, fig.width = 8, fig.align = "center", fig.cap = "(ref:10-toy-kmeans-iter)"}
 list_plot_cntrs <- vector(mode = "list", length = 4)
@@ -611,7 +611,7 @@ plt_lbl
 
 Figure \@ref(fig:10-toy-kmeans-bad-iter) shows what the iterations of K-means would look like with the unlucky random initialization shown in Figure \@ref(fig:10-toy-kmeans-bad-init).
 
-(ref:10-toy-kmeans-bad-iter) First five iterations of K-means clustering on the `penguin_data` example data set with a poor random initialization. Each pair of plots corresponds to an iteration. Within the pair, the left column depicts the center update, and the right column depicts the reassignment of data to clusters. Cluster centers are indicated by larger points that are outlined in black.
+(ref:10-toy-kmeans-bad-iter) First five iterations of K-means clustering on the `penguin_data` example data set with a poor random initialization. Each pair of plots corresponds to an iteration. Within the pair, the first plot depicts the center update, and the second plot depicts the reassignment of data to clusters. Cluster centers are indicated by larger points that are outlined in black.
 
 ```{r 10-toy-kmeans-bad-iter, echo = FALSE, warning = FALSE, fig.height = 6.75, fig.width = 8, fig.align = "center", fig.cap = "(ref:10-toy-kmeans-bad-iter)"}
 list_plot_cntrs <- vector(mode = "list", length = 5)
@@ -689,13 +689,6 @@ iter_plot_list <- c(list_plot_cntrs[1], list_plot_lbls[1],
                     list_plot_cntrs[4], list_plot_lbls[4],
                     list_plot_cntrs[5], list_plot_lbls[5])
 
-# plot_grid(plotlist = iter_plot_list, 
-#           ncol = 4,
-#           rel_heights = c(1.10, 1, 1))
-
-ggarrange(plots = iter_plot_list, ncol =4, common.legend = TRUE)
-
-
 ggarrange(iter_plot_list[[1]] +
                theme(axis.text.x = element_blank(),
                      axis.ticks.x = element_blank(),