Update pages/2_Data_CLeaning_and_Preprocessing.py

pages/2_Data_CLeaning_and_Preprocessing.py

@@ -35,8 +35,11 @@ if df is not None:
     numeric_columns = df.select_dtypes(include=['float64', 'int64']).columns
     if len(numeric_columns) > 0:
         st.subheader("Histograms for Numeric Columns:")
-        # Create a subplot for all histograms
-        fig, axs = plt.subplots(len(numeric_columns), 1, figsize=(10, 5 * len(numeric_columns)))
+        # Create a multidimensional subplot (grid) for all histograms
+        num_plots = len(numeric_columns)
+        rows = (num_plots + 1) // 2  # To create a 2-column grid layout for histograms
+        fig, axs = plt.subplots(rows, 2, figsize=(12, 12))
+        axs = axs.flatten()  # Flatten the 2D array of axes to iterate over
         
         color_palettes_hist = ['Set1', 'Set2', 'Set3', 'Paired', 'Pastel1']  # Different color palettes for histograms
         for i, col in enumerate(numeric_columns):
@@ -47,8 +50,9 @@ if df is not None:
         plt.clf()
 
         st.subheader("Boxplots for Numeric Columns:")
-        # Create a subplot for all boxplots
-        fig, axs = plt.subplots(len(numeric_columns), 1, figsize=(10, 5 * len(numeric_columns)))
+        # Create a multidimensional subplot (grid) for all boxplots
+        fig, axs = plt.subplots(rows, 2, figsize=(12, 12))
+        axs = axs.flatten()  # Flatten the 2D array of axes to iterate over
         
         color_palettes_box = ['coolwarm', 'Blues', 'viridis', 'cubehelix', 'crest']  # Different color palettes for boxplots
         for i, col in enumerate(numeric_columns):
@@ -69,7 +73,7 @@ if df is not None:
         st.write(f"Value Counts for '{selected_cat_col}':")
         st.write(df[selected_cat_col].value_counts())
 
-        plt.figure(figsize=(10, 5))
+        plt.figure(figsize=(12, 6))
         sns.countplot(x=selected_cat_col, data=df, palette='coolwarm')  # Unique palette for categorical data
         plt.title(f'Bar Plot of {selected_cat_col}')
         st.pyplot(plt)