Update index.py

index.py

@@ -47,38 +47,35 @@ df['FinBERT_label'].replace({
 counts = df.groupby(['date', 'Topic', 'domain_folder_name', 'FinBERT_label']).size().reset_index(name='count')
 counts['count'] = counts['count'].astype('float64')
 counts['rolling_mean_counts'] = counts['count'].rolling(window=30, min_periods=2).mean()
+
 df_pos = counts[[x in ['positive'] for x in counts.FinBERT_label]]
 df_neu = counts[[x in ['neutral'] for x in counts.FinBERT_label]]
 df_neg = counts[[x in ['negative'] for x in counts.FinBERT_label]]
 
 
 
-app.layout = dbc.Container(
-[   dbc.Row([ # row 1
-    dbc.Col([html.H1('Evolução temporal de sentimento em títulos de notícias')],
-    className="text-center mt-3 mb-1")
-]
-),
+app.layout = dbc.Container([   
+    dbc.Row([ # row 1
+        dbc.Col([html.H1('Evolução temporal de sentimento em títulos de notícias')],
+        className="text-center mt-3 mb-1")]),
+    
     dbc.Row([ # row 2
-        dbc.Label("Selecione um período (mm/dd/aaaa):", className="fw-bold")
-]),
+        dbc.Label("Selecione um período (mm/dd/aaaa):", className="fw-bold")]),
 
-dbc.Row([ # row 3
+    dbc.Row([ # row 3
         dcc.DatePickerRange(
             id='date-range',
             min_date_allowed=df['date'].min().date(),
             max_date_allowed=df['date'].max().date(),
             initial_visible_month=df['date'].min().date(),
             start_date=df['date'].min().date(),
-            end_date=df['date'].max().date()
-        )
-]),
+            end_date=df['date'].max().date())]),
 
     dbc.Row([ # row 4
         dbc.Label("Escolha um tópico:", className="fw-bold")
-]),
+    ]),
 
-dbc.Row([ # row 5
+    dbc.Row([ # row 5
         dbc.Col(
             dcc.Dropdown(
                 id="topic-selector",
@@ -91,17 +88,16 @@ dbc.Row([ # row 5
 
         )
 ]),
+    
+    dbc.Row([ # row 6
+            dbc.Col(dcc.Graph(id='line-graph-1'))
+    ]),
 
-dbc.Row([ # row 6
-        dbc.Col(dcc.Graph(id='line-graph-1'),
-                )
-]),
-
- dbc.Row([ # row 7
-        dbc.Label("Escolha um site de notícias:", className="fw-bold")
-]),
+    dbc.Row([ # row 7
+            dbc.Label("Escolha um site de notícias:", className="fw-bold")
+    ]),
 
-dbc.Row([ # row 8
+    dbc.Row([ # row 8
         dbc.Col(
             dcc.Dropdown(
                 id="domain-selector",
@@ -115,20 +111,20 @@ dbc.Row([ # row 8
         )
 ]),
 
-dbc.Row([ # row 9
-        dbc.Col(dcc.Graph(id='line-graph-2'),
-                )
-]),
-
-dbc.Row([ # row 10
-        dbc.Col(dcc.Graph(id='line-graph-3'),
-                )
-]),
+    dbc.Row([ # row 9
+            dbc.Col(dcc.Graph(id='line-graph-2'),
+                    )
+    ]),
 
-dbc.Row([ # row 11
-        dbc.Col(dcc.Graph(id='line-graph-4'),
-                )
-])
+    dbc.Row([ # row 10
+            dbc.Col(dcc.Graph(id='line-graph-3'),
+                    )
+    ]),
+    
+    dbc.Row([ # row 11
+            dbc.Col(dcc.Graph(id='line-graph-4'),
+                    )
+    ])
 
 ])
 
@@ -143,13 +139,11 @@ dbc.Row([ # row 11
     Input('date-range', 'start_date'),
     Input('date-range', 'end_date')
 )
-# callback function
 def update_output(selected_topic, selected_domain, start_date, end_date):
     # filter dataframes based on updated data range
     mask_1 = ((df["Topic"] == selected_topic) & (df['date'] >= start_date) & (df['date'] <= end_date))
     df_filtered = df.loc[mask_1]
 
-
     #create line graphs based on filtered dataframes
     line_fig_1 = px.line(df_filtered, x="date", y="normalised results",
                      color='Veículos de notícias', title="O gráfico mostra a evolução temporal de sentimento dos títulos de notícias. Numa escala de -1 (negativo) a 1 (positivo), sendo 0 (neutro).")