Update app.py

app.py

@@ -80,11 +80,11 @@ for uploaded_file in uploaded_files:
         
 
         st.subheader("Profile of candidate 1")
-        fig1 = px.treemap(entities, path=[px.Constant("all"), 'text', 'label'],
+        fig = px.treemap(entities, path=[px.Constant("all"), 'text', 'label'],
                 values='score', color='label')
-        fig1.update_layout(margin = dict(t=50, l=25, r=25, b=25))
-        a = st.plotly_chart(fig1, key = "tv")
-        a
+        fig.update_layout(margin = dict(t=50, l=25, r=25, b=25))
+        st.plotly_chart(fig, key = "tv")
+        
        
             
         
@@ -98,11 +98,11 @@ for uploaded_file in uploaded_files:
 
         
         st.subheader("Measuring similarity between keywords of candidate profile 1 and job description")
-        fig2 = px.imshow(cosine_sim_df, text_auto=True, labels=dict(x="Keyword similarity", y="Resumes", color="Productivity"),
+        fig = px.imshow(cosine_sim_df, text_auto=True, labels=dict(x="Keyword similarity", y="Resumes", color="Productivity"),
                         x=['Resume 1', 'Jon Description'],
                         y=['Resume 1', 'Job Description'])
-        b = st.plotly_chart(fig2, key = "bar")
-        b
+        st.plotly_chart(fig, key = "bar")
+        
 
         
         for i, similarity_score in enumerate(cosine_sim_matrix[0][1:]):
@@ -153,11 +153,11 @@ for uploaded_file in uploaded_files:
         
 
         
-        fig3 = px.treemap(entities, path=[px.Constant("all"), 'text', 'label'],
+        fig = px.treemap(entities, path=[px.Constant("all"), 'text', 'label'],
                 values='score', color='label')
-        fig3.update_layout(margin = dict(t=50, l=25, r=25, b=25))
-        c = st.plotly_chart(fig3, key = "iris")
-        c
+        fig.update_layout(margin = dict(t=50, l=25, r=25, b=25))
+        st.plotly_chart(fig, key = "iris")
+        
        
             
         
@@ -171,11 +171,11 @@ for uploaded_file in uploaded_files:
 
         
         
-        fig4 = px.imshow(cosine_sim_df, text_auto=True, labels=dict(x="Keyword similarity", y="Resumes", color="Productivity"),
+        fig = px.imshow(cosine_sim_df, text_auto=True, labels=dict(x="Keyword similarity", y="Resumes", color="Productivity"),
                         x=['Resume 2', 'Jon Description'],
                         y=['Resume 2', 'Job Description'])
-        d = st.plotly_chart(fig4, key = "radio")
-        d
+        st.plotly_chart(fig, key = "radio")
+        
 
         
         for i, similarity_score in enumerate(cosine_sim_matrix[0][1:]):