Update app.py

app.py

@@ -151,39 +151,60 @@ def show_sentiment(selected_companies=None, aggregation="Day", selected_year="Al
 
     return df_grouped.tail(30), fig
 
-# --- GRADIO INTERFACE ---
+import gradio as gr
+
+# Markdown descrittivo adattato al tuo dashboard
+description_text = """
+### How This Dashboard Works
+
+This dashboard allows you to explore the sentiment of news articles related to major tech companies (Apple, Tesla, Microsoft, Meta, Alphabet) and compare it with their stock prices. 
+
+- **Multiple companies per news**: Some news articles mention more than one company. Each news item is associated with the relevant companies in the dataset, allowing you to analyze sentiment per company.
+- **Dataset structure**: The dataset includes a company column and is organized so that each row corresponds to a news item for a specific company. This ensures accurate aggregation of sentiment scores while avoiding duplicate rows.
+- **Sentiment aggregation**: You can select a time aggregation level (Month or Year) to see how sentiment evolves over time.
+- **NASDAQ comparison**: Selecting "NASDAQ" shows the general market sentiment alongside the company-specific sentiment.
+- **Visual insights**: The top-left graph shows the average sentiment score and the corresponding closing price of the selected company. Similar trends are often observed between sentiment and stock performance.
+- **Multiple companies and years**: You can filter by company and year to focus on specific periods, or leave as "All" for a broader overview.
+
+#### Example Graph
+
+![Example graph](https://upload.wikimedia.org/wikipedia/commons/4/45/Plot_example.png)
+"""
+
+# Lista di aziende e anni
 companies = sorted(df['Company'].unique().tolist()) + ["NASDAQ"]
 years = sorted(df['Year'].dropna().unique().tolist())
 
-demo = gr.Interface(
-    fn=show_sentiment,
-    inputs=[
-        gr.Dropdown(
-            choices=companies,
-            value=None,
-            label="Select Companies (NASDAQ compares with general sentiment)",
-            multiselect=False
-        ),
-        gr.Radio(
-            choices=["Month", "Year"],
-            value="Month",
-            label="Aggregation Level"
-        ),
-        gr.Dropdown(
-            choices=["All"] + years,
-            value=2022,
-            label="Select Year"
-        )
-    ],
-    outputs=[
-        gr.Dataframe(label="Sentiment Table", type="pandas"),
-        gr.Plot(label="Sentiment Trend"),
-    ],
-    title="Dynamic Sentiment Dashboard",
-    description="Shows sentiment scores aggregated by month or year. NASDAQ compares with general sentiment if selected."
+# Interfaccia a colonne
+with gr.Blocks() as demo:
+    gr.Markdown("# Dynamic Sentiment Dashboard")
+
+    with gr.Row():
+        # Colonna a sinistra: Markdown
+        with gr.Column(scale=1):
+            gr.Markdown(description_text)
+
+        # Colonna a destra: Input
+        with gr.Column(scale=2):
+            dropdown_companies = gr.Dropdown(
+                choices=companies,
+                value=None,
+                label="Select Companies (NASDAQ compares with general sentiment)",
+                multiselect=False
+            )
 
-    
-)
+            radio_aggregation = gr.Radio(
+                choices=["Month", "Year"],
+                value="Month",
+                label="Aggregation Level"
+            )
 
-demo.launch()
+            dropdown_year = gr.Dropdown(
+                choices=["All"] + years,
+                value=2022,
+                label="Select Year"
+            )
 
+    # Output sotto le colonne
+    gr.Dataframe(label="Sentiment Table", type="pandas")
+    gr.Plot(label="Sentiment Trend")