fixed keyword block

app.py

@@ -70,10 +70,15 @@ for i in np.unique(dat['cluster']):
     keywords_df.append(TR_keywords[0:10])
     
 keywords_df = pd.DataFrame(keywords_df)
-keywords_df.columns = ['keyword1', 'keyword2', 'keyword3', 'keyword4', 'keyword5']
+keywords_df['cluster'] = np.unique(dimr['cluster'])
+keywords_df.columns = ['keyword1', 'keyword2', 'keyword3', 'keyword4', 'keyword5', 'cluster']
+
+# Get the keyword data into the dataframe
+dat = dat.merge(keywords_df) # This messes up the index, so we need to reset it
+dat = dat.reset_index(drop = True)
 
 # Merge the data together
-dat = pd.concat([md.reset_index(), dimr.reset_index(), keywords_df.reset_index()], axis = 1)
+dat = pd.concat([md.reset_index(), dimr.reset_index()], axis = 1)
 
 # handle duplicate index columns
 dat = dat.loc[:,~dat.columns.duplicated()]