Create pages/3 EDA.py

pages/3 EDA.py

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+import streamlit as st
+
+# Page Title
+st.title("📈 Exploratory Data Analysis (EDA)")
+
+# Data Exploration Section
+st.markdown("""
+### 🔍 Data Exploration:
+The dataset was analyzed to uncover patterns and relationships between features and depression status.
+
+Key areas of focus included:
+- Distribution of depression across genders  
+- Impact of academic pressure on depression risk  
+- Correlation between sleep duration and mental well-being  
+- Relationship between financial stress and depression  
+- Influence of CGPA and dietary habits on student mental health
+""")
+
+# Key Observations Section
+st.markdown("""
+### 📊 Key Observations:
+- Students reporting **higher academic pressure** were more likely to show signs of depression  
+- **Inadequate sleep** and **unbalanced diet** were common among students predicted as depressed  
+- **Financial stress** and **low CGPA** had strong associations with depression  
+- Female students showed slightly higher reported cases of depression in the dataset
+""")
+
+# Visualization Techniques Section
+st.markdown("""
+### 📉 Visualization Techniques:
+- **Countplots** to examine category distributions like gender, class, and stress levels  
+- **Boxplots** to explore spread and variation in numerical features (e.g., CGPA, Age)  
+- **Heatmaps** to visualize feature correlations and identify multicollinearity
+
+These insights helped refine feature selection and informed model-building decisions.
+""")
+
+
+if st.button("Next >>"):
+    st.switch_page(r"pages\4 Feature Engineering.py")
+
+if st.button("<< Back"):
+    st.switch_page(r"pages\2 Data Understanding.py")