Update app.py

app.py

@@ -2,6 +2,7 @@ import streamlit as st
 import pandas as pd
 import transformers
 import re
+import zipfile
 import postt
 from postt import postcor
 from transformers import  pipeline, TokenClassificationPipeline, BertForTokenClassification , AutoTokenizer , TextClassificationPipeline , AutoModelForSequenceClassification
@@ -241,6 +242,45 @@ if submit and len(x) != 0:
   edccanbis = postcor(edccanbis)
   
   
+  
+  edccann = []
+  edchorm = []
+  edcrecep = []
+  hormrecep = []
+  hormcan = []
+  
+  for e in edccanbis:
+    if e[-1]== ["B-EDC","B-CANCER"]:
+      edccann += [[e[0],e[1],e[2]]
+    elif e[-1]== ["B-EDC","B-HORMONE"]:
+      edchorm += [[e[0],e[1],e[2]]
+    elif e[-1]== ["B-EDC","B-RECEPTOR"]:
+      edcrecep += [[e[0],e[1],e[2]]
+    elif e[-1]== ["B-HORMONE","B-RECEPTOR"]:
+      hormrecep += [[e[0],e[1],e[2]]
+    elif e[-1]== ["B-HORMONE","B-CANCER"]:
+      hormcan += [[e[0],e[1],e[2]]
+  
+  
+  edcrecepdf  = pd.DataFrame(edcrecep, columns=["EDC", "RECEPTOR", "RELATION"])
+  edccanndf = pd.DataFrame(edccann, columns= ["EDC", "CANCER", "RELATION"] )
+  edchormdf = pd.DataFrame(edchorm , columns = ["EDC", "HORMONE", "RELATION"])
+  hormrecepdf = pd.DataFrame(hormrecep, columns = ["HORMONE", "RECEPTOR", "RELATION"])
+  hormcandf = pd.DataFrame(hormcan, columns = ["HORMONE", "CANCER", "RELATION"])
+  
+  edccancsv = edccanndf.to_csv('edccan.csv') 
+  edcrecepcsv = edcrecepdf.to_csv('edcrecep.csv')
+  edchormcsv = edchormdf.to_csv('edchorm.csv')
+  hormcancsv = hormcandf.to_csv('hormcan.csv')
+  hormrecepcsv = hormrecepdf.to_csv('hormrecep.csv')
+  
+  with zipfile.ZipFile("allcsvs.zip", "w") as zipf:
+    zipf.write(edccancsv)
+    zipf.write(edcrecepcsv)
+    zipf.write(edchormcsv)
+    zipf.write(hormcancsv)
+    zipf.write(hormrecepcsv)
+  
   for e in edccanbis:
     edccan += [[e[3],e[0]+" ["+e[-1][0][2:]+"]", e[1]+" ["+e[-1][1][2:]+"]",e[2]]]
    
@@ -250,11 +290,18 @@ if submit and len(x) != 0:
   st.table(edccandf)
   csv = edccandf.to_csv(index=False).encode('utf-8')
   st.download_button(
-       label="Download data as CSV",
+       label="Download all data as CSV",
        data=csv,
        file_name='Relation_triples.csv',
        mime='text/csv',
    )
+   st.download_button(
+       "Download in different CSVs",
+       zipf,
+       file_name='TriplesCSVs.zip',
+       
+   )
+