df_observed

src/streamlit_app.py

@@ -74,6 +74,8 @@ s3 = boto3.client(
 obj = s3.get_object(Bucket="mygeodechet", Key="df_dummies_2019.csv")
 df = pd.read_csv(obj['Body']).drop(columns=["Unnamed: 0"], errors="ignore")
 
+obj_obs = s3.get_object(Bucket="mygeodechet", Key="data_wip_v5.xlsx")
+observed_df = pd.read_excel(obj_obs['Body'])
 
 # # Chargement des données
 # df = pd.read_csv("https://mygeodechet.s3.eu-west-3.amazonaws.com/df_dummies_2019.csv").drop(columns=["Unnamed: 0"], errors="ignore")
@@ -190,11 +192,13 @@ with chart_col:
                 with open(path, "rb") as f:
                     model = pickle.load(f)
 
-                expected_cols = model.model.exog_names
-                if "const" in expected_cols and "const" not in input_df_complete.columns:
-                    input_df_complete["const"] = 1.0
+                # expected_cols = model.model.exog_names
+                # if "const" in expected_cols and "const" not in input_df_complete.columns:
+                #     input_df_complete["const"] = 1.0
+
+                # prediction = max(0, model.predict(input_df_complete[expected_cols]).iloc[0])
+                prediction = max(0, model.predict(input_df_complete).iloc[0])
 
-                prediction = max(0, model.predict(input_df_complete[expected_cols]).iloc[0])
                 valeurs_predites.append(prediction)
                 labels.append(typologie)