.

dashboard.py

@@ -0,0 +1,45 @@
+# -*- coding: utf-8 -*-
+"""dashboard
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1yT5Jix3VrdcKCeSgH-Gt-NSJnfHzX42H
+"""
+
+# 📊 Streamlit Dashboard Code (Save as `dashboard.py`)
+
+import streamlit as st
+import pandas as pd
+import os
+
+st.title("📊 Mental Health Datasets Comparison Dashboard")
+
+# Use absolute path if needed, fallback to local folder
+results_dir = os.path.abspath("EDA_results")
+dataset_dirs = [f for f in os.listdir(results_dir) if os.path.isdir(os.path.join(results_dir, f))]
+
+for ds in dataset_dirs:
+    st.subheader(f"📁 Dataset: {ds}")
+    ds_path = os.path.join(results_dir, ds)
+
+    col1, col2 = st.columns(2)
+
+    with col1:
+        plot1 = os.path.join(ds_path, "class_balance_plot.png")
+        plot2 = os.path.join(ds_path, "avg_text_length_plot.png")
+        if os.path.exists(plot1):
+            st.image(plot1, caption="Class Balance")
+        if os.path.exists(plot2):
+            st.image(plot2, caption="Avg Text Length by Label")
+
+    with col2:
+        wc = os.path.join(ds_path, "wordcloud.png")
+        if os.path.exists(wc):
+            st.image(wc, caption="Word Cloud")
+
+    entropy_path = os.path.join(ds_path, "entropy.csv")
+    if os.path.exists(entropy_path):
+        entropy = pd.read_csv(entropy_path)
+        if 'entropy' in entropy.columns:
+            st.metric(label="🔀 Entropy (Label Diversity)", value=round(entropy['entropy'][0], 3))

requirements.txt

@@ -0,0 +1,2 @@
+streamlit
+pandas

results_zip.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5a421945bff54a26c9c5e572a70c808c47ae603c947045630789c1577e45263b
+size 1614550