Update app.py

app.py

@@ -649,23 +649,30 @@ with gr.Blocks(theme='gradio/soft',js=js_func) as demo:
     with gr.Tab("Fed data analysis"):
         gr.Markdown("## Sentiment Analysis Overview")
         # Display DataFrame
+        apply_btn = gr.Button("Apply", scale=0)
         df = pd.read_csv("data/2008_2024_minutes.csv", header = 0)
         df['Total_paragraphs']=df['Total_paragraphs']-df['Neutral']
         df['Positive_ratio'] = df['Positive'] / df['Total_paragraphs']*100
         df['Negative_ratio'] = df['Negative'] / df['Total_paragraphs']*100
+        df['Date'] = pd.to_datetime(df['Date']) 
+        with gr.Row():
+            start = gr.DateTime(df['Date'].min(), label="Start")
+            end = gr.DateTime(df['Date'].max(), label="End")
+            apply_btn = gr.Button("Apply", scale=0)
+            reset_btn = gr.Button("Reset", scale=0)
         # data_table = gr.DataFrame(value=df[['Date', 'Positive_ratio', 'Negative_ratio', 'Total_paragraphs']], label="Sentiment Data", height=500)
-        df['Date'] = pd.to_datetime(df['Date'])  # Ensure 'Date' is a datetime object
         # Pivot the DataFrame
-        melted_df = df.melt(id_vars='Date', value_vars=['Positive_ratio', 'Negative_ratio'],
-                    var_name='Ratio_Type', value_name='Rate')
+        #melted_df = df.melt(id_vars='Date', value_vars=['Positive_ratio', 'Negative_ratio'],
+        #            var_name='Ratio_Type', value_name='Rate')
         # Line plot for the ratios
         line_plot = gr.LinePlot(
-            melted_df,
+            df,
             x='Date',
-            y='Rate',
-            title="Sentiment Ratios Over Time",
+            y='Positive_ratio',
+            title="Positive Rate Over Time",
             y_lim=[0, 100],   # Limit y-axis to 0-1 since it's a ratio
-            color = 'Ratio_Type'
+            #color = 'Ratio_Type'
         )
-
+        apply_btn.click(lambda start,end: gr.LinePlot(x_lim=[start, end]), [start, end], line_plot)
+        reset_btn.click(lambda : gr.LinePlot(x_lim=[df['Date'].min(), df['Date'].max()]), [], line_plot)
 demo.launch()