diff --git a/p2/quest/biber_pca_affil.png b/p2/quest/biber_pca_affil.png
new file mode 100644
index 0000000..4a553dd
Binary files /dev/null and b/p2/quest/biber_pca_affil.png differ
diff --git a/p2/quest/neurobiber-pca.log b/p2/quest/neurobiber-pca.log
index 7bfae6c..ccddd4c 100644
--- a/p2/quest/neurobiber-pca.log
+++ b/p2/quest/neurobiber-pca.log
@@ -1,5 +1,5 @@
-starting the job at: Tue Sep  2 15:53:08 CDT 2025
+starting the job at: Tue Sep  2 16:02:22 CDT 2025
 setting up the environment
 running the neurobiber labeling script
 job finished, cleaning up
-job pau at: Tue Sep  2 15:53:21 CDT 2025
+job pau at: Tue Sep  2 16:02:32 CDT 2025
diff --git a/p2/quest/python_scripts/neurobiber_PCA.py b/p2/quest/python_scripts/neurobiber_PCA.py
index 06cde33..57cc2c7 100644
--- a/p2/quest/python_scripts/neurobiber_PCA.py
+++ b/p2/quest/python_scripts/neurobiber_PCA.py
@@ -5,6 +5,7 @@ import pandas as pd
 import numpy as np
 import pandas as pd 
 import matplotlib.pyplot as plt
+import seaborn as sns
 
 
 def format_df_data(df):
@@ -33,3 +34,20 @@ if __name__ == "__main__":
     plt.colorbar()
 
     plt.savefig("090225_biber_pca_plot.png", dpi=300) 
+    
+    plot_df = pd.DataFrame({
+        "PC1": biber_vecs_pca[:, 0],
+        "PC2": biber_vecs_pca[:, 1],
+        "AuthorWMFAffil": biber_vec_df["AuthorWMFAffil"].astype(str)
+    })
+    plt.figure(figsize=(8,6))
+    sns.scatterplot(
+        data=plot_df, x="PC1", y="PC2", hue="AuthorWMFAffil",
+        palette="tab10", s=40, alpha=0.7, edgecolor=None
+    )
+    plt.xlabel('component 1')
+    plt.ylabel('component 2')
+    plt.legend(title='AuthorWMFAffil', bbox_to_anchor=(1.05, 1), loc=2)
+    plt.tight_layout()
+    plt.savefig("biber_pca_affil.png", dpi=300)
+    plt.show()