Update app.py

app.py

@@ -4,9 +4,10 @@ import bcrypt
 import datetime
 import re
 import pytz
-import numpy as np  
-import pandas as pd  
-import plotly.express as px  
+import numpy as np
+import pandas as pd
+import plotly.express as px
+import plotly.graph_objs as go  # Import Plotly's graph objects
 
 # MySQL Connection
 connection = mysql.connector.connect(
@@ -84,8 +85,6 @@ if 'username' not in st.session_state:
     st.session_state.username = ''
 if 'current_page' not in st.session_state:
     st.session_state.current_page = 'login'
-if 'employee_submitted' not in st.session_state:
-    st.session_state.employee_submitted = False
 
 # Page styling
 st.markdown("""
@@ -139,7 +138,9 @@ st.markdown("""
 
 # Login page
 def login():
-    st.markdown('<p class="big-font">Performance Prediction Login</p>', unsafe_allow_html=True)
+    st.image("performance prediction.jpeg", use_column_width=True)
+    st.markdown('<p class="big-font">Performance Nexus Login</p>', unsafe_allow_html=True)
+
 
     col1, col2, col3 = st.columns([1, 2, 1])
 
@@ -223,78 +224,96 @@ def reset_password_page():
             elif not username_exists(username):
                 st.error("Username not found. Enter a valid username.")
             elif not new_password or not re_password:
-                st.error("Enter all the credentials.")
-            elif len(new_password) <= 3:
-                st.error("Password too short. Enter a longer password.")
+                st.error("Enter new password and confirm password.")
             elif new_password != re_password:
-                st.error("Passwords do not match! Please re-enter.")
+                st.error("Passwords do not match. Please re-enter.")
+            elif len(new_password) <= 3:
+                st.error("Password too short")
             else:
                 reset_password(username, new_password)
-                st.success("Password has been reset successfully! Please login with your new password.")
+                st.success("Password reset successful. You can now login with your new password.")
+                st.session_state.reset_password = False
                 st.session_state.current_page = 'login'
                 st.experimental_rerun()
 
-    st.markdown("<br>", unsafe_allow_html=True)
-    st.markdown("<div class='link-text'>Remember your password?</div>", unsafe_allow_html=True)
-    if st.button('Login'):
-        st.session_state.current_page = 'login'
-        st.experimental_rerun()
+    if not st.session_state.get('reset_password', False):
+        st.markdown("<br>", unsafe_allow_html=True)
+        st.markdown("<div class='link-text'>Back to Login?</div>", unsafe_allow_html=True)
+        if st.button('Login'):
+            st.session_state.current_page = 'login'
+            st.experimental_rerun()
+
+rotating_images = ["path_to_image1.png", "path_to_image2.png", "path_to_image3.png"]
 
-# Home page
 def home_page():
-    st.sidebar.title(f"Welcome, {st.session_state.username}!")
-    
-    # Sidebar for inputting employee details
-    st.sidebar.header("Enter Employee Details")
-    employee_name = st.sidebar.text_input("Employee Name")
-    employee_id = st.sidebar.text_input("Employee ID")
-    employee_age = st.sidebar.number_input("Employee Age", min_value=18, max_value=65, value=30)
-    employee_join_date = st.sidebar.date_input("Joining Date", value=datetime.date(2020, 1, 1))
-    employee_appraisal_date = st.sidebar.date_input("Last Appraisal Date", value=datetime.date(2023, 1, 1))
-    
-    if st.sidebar.button("Submit"):
-        st.session_state.employee_submitted = True
-        st.sidebar.success(f"Employee {employee_name} (ID: {employee_id}, Age: {employee_age}) details submitted successfully!")
+    st.title(f"Welcome to the Performance Nexus Dashboard, {st.session_state.username}!")
 
+    # Display rotating images
+    for image_path in rotating_images:
+        st.image(image_path, use_column_width=True)
+        st.markdown("<br>", unsafe_allow_html=True)
+        st.markdown("<hr>", unsafe_allow_html=True)
+
+    # Sidebar for user input
+    st.sidebar.header("Input Parameters")
+    employee_id = st.sidebar.number_input("Employee ID", min_value=1, max_value=1000, value=1)
+    department = st.sidebar.selectbox("Department", ["Sales", "Marketing", "Engineering", "HR"])
+    experience = st.sidebar.slider("Years of Experience", 0, 20, 5)
+    
     # Main dashboard area
-    st.title("Performance Prediction Dashboard")
+    col1, col2 = st.columns(2)
     
-    if st.session_state.employee_submitted:
-        tab1, tab2 = st.tabs(["Overview", "Performance Insights"])
+    with col1:
+        st.subheader("Employee Performance Score")
+        # Placeholder for performance prediction
+        performance_score = np.random.randint(60, 100)
+        st.metric("Predicted Performance", f"{performance_score}%", "4%")
         
-        with tab1:
-            col1, col2 = st.columns(2)
-            
-            with col1:
-                st.subheader("Employee Performance Score")
-                performance_score = np.random.randint(60, 100)
-                st.metric("Predicted Performance", f"{performance_score}%", "4%")
-                
-                st.subheader("Key Factors Influencing Performance")
-                factors = pd.DataFrame({
-                    'Factor': ['Experience', 'Training', 'Projects', 'Teamwork'],
-                    'Impact': [0.3, 0.25, 0.28, 0.17]
-                })
-                fig = px.bar(factors, x='Impact', y='Factor', orientation='h', color='Factor',
-                             color_discrete_sequence=px.colors.qualitative.Bold)
-                st.plotly_chart(fig)
-
-            with col2:
-                st.subheader("Performance Trend")
-                dates = pd.date_range(start="2023-01-01", end="2023-12-31", freq="M")
-                performance = np.random.randint(70, 100, size=len(dates))
-                trend_data = pd.DataFrame({"Date": dates, "Performance": performance})
-                fig = px.line(trend_data, x="Date", y="Performance", title='Performance Over Time',
-                              line_shape='spline', render_mode='svg', color_discrete_sequence=['#1E88E5'])
-                st.plotly_chart(fig)
-                
-        with tab2:
-            st.subheader("Performance Insights")
-            st.write(f"Based on the analysis for Employee ID {employee_id}:")
-            st.write(f"- Current performance is {'above' if performance_score > 80 else 'below'} average")
-            st.write(f"- Key area for improvement: {'Training' if performance_score < 80 else 'Project Management'}")
-            st.write(f"- Recommended action: {'Enroll in advanced skills program' if performance_score < 80 else 'Take on leadership role in upcoming project'}")
-    
+        st.subheader("Key Factors Influencing Performance")
+        factors = pd.DataFrame({
+            'Factor': ['Experience', 'Training', 'Projects', 'Teamwork'],
+            'Impact': [0.3, 0.25, 0.28, 0.17]
+        })
+        fig = px.bar(factors, x='Impact', y='Factor', orientation='h')
+        st.plotly_chart(fig)
+
+    with col2:
+        st.subheader("Performance Trend")
+        # Placeholder for performance trend
+        dates = pd.date_range(start="2023-01-01", end="2023-12-31", freq="M")
+        performance = np.random.randint(70, 100, size=len(dates))
+        trend_data = pd.DataFrame({"Date": dates, "Performance": performance})
+        fig = px.line(trend_data, x="Date", y="Performance")
+        st.plotly_chart(fig)
+
+        # Gauge chart for employee rating
+        st.subheader("Employee Rating")
+        fig = go.Figure(go.Indicator(
+            mode = "gauge+number",
+            value = performance_score,
+            domain = {'x': [0, 1], 'y': [0, 1]},
+            title = {'text': "Employee Rating"},
+            gauge = {
+                'axis': {'range': [None, 100]},
+                'steps' : [
+                    {'range': [0, 60], 'color': "lightgray"},
+                    {'range': [60, 80], 'color': "gray"},
+                    {'range': [80, 100], 'color': "green"}],
+                'threshold' : {
+                    'line': {'color': "red", 'width': 4},
+                    'thickness': 0.75,
+                    'value': performance_score}}))
+        st.plotly_chart(fig)
+
+
+    # Additional insights
+    st.subheader("Performance Insights")
+    st.write(f"Based on the analysis for Employee ID {employee_id} in the {department} department:")
+    st.write(f"- Current performance is {'above' if performance_score > 80 else 'below'} average")
+    st.write(f"- Key area for improvement: {'Training' if performance_score < 80 else 'Project Management'}")
+    st.write(f"- Recommended action: {'Enroll in advanced skills program' if performance_score < 80 else 'Take on leadership role in upcoming project'}")
+
+    # Logout button
     if st.button("Logout"):
         st.session_state.login_successful = False
         st.session_state.username = ''
@@ -302,6 +321,9 @@ def home_page():
         st.experimental_rerun()
 
 # Main app logic
+if 'current_page' not in st.session_state:
+    st.session_state.current_page = 'login'
+
 if st.session_state.current_page == 'login':
     login()
 elif st.session_state.current_page == 'sign_up':