Update app.py

app.py

@@ -130,6 +130,18 @@ ENGAGED_STR = 'Engaged (Respect, Responsibility, Effort)'
 PARTIALLY_ENGAGED_STR = 'Partially Engaged (about 50%)'
 NOT_ENGAGED_STR = 'Not Engaged (less than 50%)'
 
+def safe_convert_to_time(series, format_str=None):
+    try:
+        # Attempt to convert to time, ignoring errors
+        converted = pd.to_datetime(series, errors='coerce').dt.time
+        if format_str:
+            # Format if a format string is provided
+            return pd.Series([time.strftime(format_str) if time is not None else None for time in converted])
+        return converted
+    except Exception as e:
+        print(f"Error converting series to time: {e}")
+        return series
+
 def safe_convert_to_datetime(series, format_str=None):
     try:
         # Attempt to convert to datetime, ignoring errors
@@ -146,8 +158,8 @@ def format_session_data(df):
     # Format "Date of Session" and "Timestamp" columns with safe conversion
     df['Date of Session'] = safe_convert_to_datetime(df['Date of Session'], '%m/%d/%Y')
     df['Timestamp'] = safe_convert_to_datetime(df['Timestamp'], '%I:%M %p')
-    df['Session Start Time'] = safe_convert_to_datetime(df['Session Start Time'], '%I:%M %p')
-    df['Session End Time'] = safe_convert_to_datetime(df['Session End Time'], '%I:%M %p')
+    df['Session Start Time'] = safe_convert_to_time(df['Session Start Time'], '%I:%M %p')
+    df['Session End Time'] = safe_convert_to_time(df['Session End Time'], '%I:%M %p')
 
     # Reorder columns
     df = df[['Date of Session', 'Timestamp'] + [col for col in df.columns if col not in ['Date of Session', 'Timestamp']]]
@@ -365,21 +377,28 @@ def compute_student_metrics(df):
     return student_metrics_df
 
 def plot_student_metrics(student_metrics_df):
-    # Create a stacked bar chart for attendance and engagement
+    # Create the figure and axis
     fig, ax = plt.subplots()
 
-    # Plotting the Attendance and Engagement as stacked bars
-    ax.bar(student_metrics_df['Student'], student_metrics_df['Attendance (%)'], label='Attendance (%)', color='#005288')
-    ax.bar(student_metrics_df['Student'], student_metrics_df['Engagement (%)'], 
-           bottom=student_metrics_df['Attendance (%)'], label='Engagement (%)', color='#3AB0FF')
+    # Width for the bars and offset for overlapping effect
+    bar_width = 0.4
+    index = range(len(student_metrics_df))
+
+    # Plot Attendance and Engagement bars side by side with transparency
+    ax.bar([i - bar_width/2 for i in index], student_metrics_df['Attendance (%)'], 
+           width=bar_width, label='Attendance (%)', color='#005288', alpha=0.7)
+    ax.bar([i + bar_width/2 for i in index], student_metrics_df['Engagement (%)'], 
+           width=bar_width, label='Engagement (%)', color='#3AB0FF', alpha=0.7)
 
-    # Setting the labels, title, and legend
+    # Set labels, title, and legend
     ax.set_xlabel('Student')
     ax.set_ylabel('Percentage (%)')
     ax.set_title('Student Attendance and Engagement Metrics')
     ax.legend()
-    plt.xticks(rotation=45)
+    ax.set_xticks(index)
+    ax.set_xticklabels(student_metrics_df['Student'], rotation=45)
 
+    # Display the plot
     st.pyplot(fig)
 
     return fig