Update app.py

app.py

@@ -144,7 +144,7 @@ data['score'] = (data['score_sanitaire'] + data['score_foyer']) / 2
 # In[6]:
 
 
-#data['score responsabilité'] = data['score_sanitaire'] - data['score_foyer']
+data['score responsabilité'] = data['score_sanitaire'] - data['score_foyer']
 
 
 # In[7]:
@@ -397,80 +397,3 @@ st.plotly_chart(fig)
 
 
 #gdf_merged_q.to_csv('merged_q.csv', index=False)
-
-
-# In[ ]:
-
-
-
-
-
-# # Scores de propreté - par régions
-
-# In[78]:
-
-
-#id_regions
-
-
-# In[79]:
-
-
-regions_id = list(id_regions.keys())
-scores = list()
-
-
-# In[80]:
-
-
-rm = {}
-for q in regions_id:
-  print(q)
-  rm[q] = moyenne_par_communaute(data, q)
-
-#rm
-
-
-# In[81]:
-
-
-regions = [id_regions[i] for i in regions_id]
-scores = list(rm.values())
-
-
-# In[82]:
-
-
-region_df = pd.DataFrame({
-    'region_id': regions_id,
-    'region': regions,
-    'scores': scores
-})
-
-
-
-# In[ ]:
-
-
-
-
-
-# # Score de responsabilité - par quartiers (Préfectures)
-
-# In[93]:
-
-
-qm = {}
-for q in quartiers:
-    qm[q] = moyenne_par_quartier(data, quartier_id[q], scoring="score responsabilité")
-
-
-
-# In[ ]:
-
-
-# In[ ]:
-
-
-
-