Update app.py

app.py

@@ -1,7 +1,3 @@
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-
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-You said:
 import streamlit as st
 import pandas as pd
 from sklearn.model_selection import train_test_split
@@ -148,17 +144,21 @@ if uploaded_file is not None:
         st.subheader("Classification Model Performance Metrics")
         st.dataframe(metrics_df)
 
-        # Save metrics as PNG
-        fig, ax = plt.subplots()
-        sns.barplot(data=metrics_df, x="Model", y="Accuracy", ax=ax)
-        ax.set_title("Classification Model Performance")
+                # Save metrics as PNG (table form)
+        fig, ax = plt.subplots(figsize=(8, 4))
+        ax.axis('tight')
+        ax.axis('off')
+        table = plt.table(cellText=metrics_df.values, colLabels=metrics_df.columns, cellLoc='center', loc='center')
+        table.auto_set_font_size(False)
+        table.set_fontsize(10)
+        table.auto_set_column_width(col=list(range(len(metrics_df.columns))))
         buf = BytesIO()
         fig.savefig(buf, format="png")
         buf.seek(0)
         st.download_button(
-            label="Download Classification Report as PNG",
+            label="Download Classification Metrics Table as PNG",
             data=buf,
-            file_name="classification_report.png",
+            file_name="classification_metrics_table.png",
             mime="image/png"
         )
     
@@ -190,16 +190,22 @@ if uploaded_file is not None:
         st.subheader("Regression Model Performance Metrics")
         st.dataframe(regression_metrics_df)
 
-        # Save metrics as PNG
-        fig, ax = plt.subplots()
-        sns.barplot(data=regression_metrics_df, x="Model", y="R² Score", ax=ax)
-        ax.set_title("Regression Model Performance")
+        # Save metrics as PNG (table form)
+        fig, ax = plt.subplots(figsize=(8, 4))
+        ax.axis('tight')
+        ax.axis('off')
+        table = plt.table(cellText=regression_metrics_df.values, colLabels=regression_metrics_df.columns, cellLoc='center', loc='center')
+        table.auto_set_font_size(False)
+        table.set_fontsize(10)
+        table.auto_set_column_width(col=list(range(len(regression_metrics_df.columns))))
         buf = BytesIO()
         fig.savefig(buf, format="png")
         buf.seek(0)
         st.download_button(
-            label="Download Regression Report as PNG",
+            label="Download Regression Metrics Table as PNG",
             data=buf,
-            file_name="regression_report.png",
+            file_name="regression_metrics_table.png",
             mime="image/png"
-        )
+        )
+
+