Create app.py

app.py

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+import pandas as pd
+import plotly.express as px
+from datasets import load_dataset
+import gradio as gr
+
+# --- LOAD YOUR DATASET ---
+df = pd.DataFrame(load_dataset("SelmaNajih001/NewsSentiment")["train"])
+df['Date'] = pd.to_datetime(df['Date'], errors='coerce').dt.normalize()
+
+
+# --- GRADIO FUNCTION ---
+def show_sentiment(selected_companies):
+    if selected_companies:  # filtraggio per aziende selezionate
+        df_filtered = df[df['Company'].isin(selected_companies)]
+        df_grouped = (
+            df_filtered.groupby(['Date', 'Company'])['Score']
+            .sum()
+            .reset_index()
+        )
+        fig = px.line(
+            df_grouped, x="Date", y="Score", color="Company",
+            title="Daily Sentiment Score by Company"
+        )
+    else:  # aggregato generale
+        df_grouped = (
+            df.groupby('Date')['Score']
+            .sum()
+            .reset_index()
+        )
+        fig = px.line(
+            df_grouped, x="Date", y="Score",
+            title="General Daily Sentiment Score"
+        )
+
+    return df_grouped.tail(30), fig  # ultime 30 righe per leggibilità
+
+# --- GRADIO INTERFACE ---
+companies = sorted(df['Company'].unique().tolist())
+
+demo = gr.Interface(
+    fn=show_sentiment,
+    inputs=[
+        gr.Dropdown(
+            choices=companies,
+            value=None,
+            label="Select Companies (leave empty for general sentiment)",
+            multiselect=True
+        )
+    ],
+    outputs=[
+        gr.Dataframe(label="Daily Sentiment", type="pandas"),
+        gr.Plot(label="Sentiment Trend"),
+    ],
+    title="Daily Sentiment Dashboard",
+    description="Shows daily sentiment scores (positive = +score, negative = -score, neutral = 0)."
+)
+
+demo.launch()