Update app.py

app.py

@@ -1,7 +1,5 @@
 import streamlit as st
 import pandas as pd
-import matplotlib.pyplot as plt
-import io
 from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import LabelEncoder
 from sklearn.ensemble import RandomForestClassifier
@@ -12,6 +10,7 @@ from sklearn.tree import DecisionTreeClassifier
 from sklearn.naive_bayes import GaussianNB
 from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score
 from tabulate import tabulate
+import io
 
 # Function to convert DataFrame to Excel format
 def to_excel(df):
@@ -21,25 +20,6 @@ def to_excel(df):
     output.seek(0)
     return output
 
-# Function to save table as PNG
-def save_table_as_png(df):
-    fig, ax = plt.subplots(figsize=(8, 6))
-    ax.axis('tight')
-    ax.axis('off')
-    
-    # Create a table from the DataFrame
-    table = ax.table(cellText=df.values, colLabels=df.columns, loc='center', cellLoc='center')
-    table.auto_set_font_size(False)
-    table.set_fontsize(10)
-    table.scale(1.2, 1.2)
-
-    # Save the table as a PNG image
-    img_path = "/tmp/model_report.png"
-    plt.savefig(img_path, format="png", bbox_inches="tight")
-    plt.close(fig)
-    
-    return img_path
-
 # File uploader
 st.title("Model Training with Metrics")
 uploaded_file = st.file_uploader("Choose a CSV file", type=["csv"])
@@ -130,7 +110,7 @@ if uploaded_file is not None:
 
             # Option to download the model performance metrics (Results Table)
             st.download_button(
-                label="Download Model Report (Excel)",
+                label="Download Model Report",
                 data=to_excel(metrics_df),  # The metrics dataframe
                 file_name="model_report.xlsx",
                 mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
@@ -138,18 +118,8 @@ if uploaded_file is not None:
 
             # Option to download the cleaned dataset
             st.download_button(
-                label="Download Cleaned Dataset (Excel)",
+                label="Download Cleaned Dataset",
                 data=to_excel(df),  # The cleaned dataset is 'df'
                 file_name="cleaned_dataset.xlsx",
                 mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
             )
-
-            # Option to download the report as PNG
-            img_path = save_table_as_png(metrics_df)
-            with open(img_path, "rb") as file:
-                st.download_button(
-                    label="Download Model Report (PNG)",
-                    data=file,
-                    file_name="model_report.png",
-                    mime="image/png"
-                )