New metric Count as compared to other variables in the ELP.

# ========================================================= # 13. Relabel axes with indexed variable names # ========================================================= # --------------------------------------------------------- # 1. Create ordered variable index # --------------------------------------------------------- var_names <- colnames(cor_mat) var_index_df <- data.frame( variable = var_names, index = seq_along(var_names), y_label = paste0(var_names, " (", seq_along(var_names), ")"), x_label = paste0("(", seq_along(var_names), ")"), stringsAsFactors = FALSE ) # --------------------------------------------------------- # 2. Merge labels into plotting data # --------------------------------------------------------- heat_sig_df_labeled <- heat_sig_df %>% dplyr::left_join(var_index_df, by = c("Var1" = "variable")) %>% dplyr::rename( Var1_index = index, Var1_label = y_label ) %>% dplyr::left_join(var_index_df, by = c("Var2" = "variable")) %>% dplyr::rename( Var2_index = index, Var2_label = x_label ) # --------------------------------------------------------- # 3. Convert to ordered factors using index # --------------------------------------------------------- heat_sig_df_labeled <- heat_sig_df_labeled %>% dplyr::mutate( Var1_label = factor(Var1_label, levels = var_index_df$y_label), Var2_label = factor(Var2_label, levels = var_index_df$x_label) ) # --------------------------------------------------------- # 4. Plot with new labels # --------------------------------------------------------- p_sig_labeled <- ggplot(heat_sig_df_labeled, aes(x = Var2_label, y = Var1_label, fill = r)) + geom_tile(color = "white") + geom_text(aes(label = sprintf("%.2f", r)), size = 3) + scale_fill_gradient2( low = "blue", mid = "white", high = "red", midpoint = 0, limits = c(-1, 1), name = "r" ) + theme_minimal(base_size = 12) + theme( axis.text.x = element_text(angle = 0, hjust = 0.5), axis.text.y = element_text(size = 9), panel.grid = element_blank() ) + labs( title = "Significant Correlations Only (p < .05)", x = "Variable Index", y = "Variables" ) + coord_fixed() # --------------------------------------------------------- # 5. Save # --------------------------------------------------------- ggsave( filename = "Derived_Measures_Correlation_Heatmap_SIGNIFICANT_ONLY_LABELED.png", plot = p_sig_labeled, width = 14, height = 12, dpi = 300 ) # Display print(p_sig_labeled)