Update apps/sdg_pd.py

apps/sdg_pd.py

@@ -7,6 +7,15 @@ import os
 
 def app():
     st.title("SDG Embedding Visualisation")
+    with st.expander("ℹ️ - About this app", expanded=True):
+
+        st.write(
+            """     
+            Information cartography - Get your word/phrase/sentence/paragraph embedded and visualized.
+            The (English) sentence-transformers model "all-MiniLM-L6-v2" maps sentences & paragraphs to a 384 dimensional dense vector space This is normally used for tasks like clustering or semantic search, but in this case, we use it to place your text to a 3D map. Before plotting, the dimension needs to be reduced to three so we can actually plot it, but preserve as much information as possible. For this, we use a technology called umap.
+            
+            On this page, you find thousands of text excerpts that were labelled by the community volunteers with respect to Sustainable Development Goals, a project by OSDG.ai,  embedded as described. Ready to explore.
+            """)
     
     with st.spinner("👑 load data"):
           df_osdg = pd.read_csv("sdg_umap.csv", sep = "|")