apps/sdg_pd.py

import plotly.express as px
import streamlit as st
from sentence_transformers import SentenceTransformer
import umap.umap_ as umap
import pandas as pd
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 = "|")
                       
          #labels = [_lab_dict[lab] for lab in df_osdg['label'] ]
          keys = list(df_osdg['keys'])
          #docs = list(df_osdg['text'])
          
          agree = st.checkbox('add labels')
    
          if agree:
              with st.spinner("👑 create visualisation"):  
                  fig = px.scatter_3d(
                      df_osdg, x='coord_x', y='coord_y', z='coord_z',
                      color='labels',
                      opacity = .5,    hover_data=[keys])
                  fig.update_scenes(xaxis_visible=False, yaxis_visible=False,zaxis_visible=False )
                  fig.update_traces(marker_size=4)
                  st.plotly_chart(fig)
          else:
              with st.spinner("👑 create visualisation"):  
                  fig = px.scatter_3d(
                      df_osdg, x='coord_x', y='coord_y', z='coord_z',  
                      opacity = .5,    hover_data=[keys])
                  fig.update_scenes(xaxis_visible=False, yaxis_visible=False,zaxis_visible=False )
                  fig.update_traces(marker_size=4)
                  st.plotly_chart(fig)