mirror of
https://github.com/andwati/predictive_analysis.git
synced 2026-10-18 08:42:52 +00:00
deploy to streamlit
This commit is contained in:
+427
-49
@@ -10,6 +10,7 @@ import pickle
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import plotly.express as px
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import plotly.graph_objects as go
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from plotly.subplots import make_subplots
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import time
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# Configure Streamlit page
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st.set_page_config(
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@@ -19,46 +20,279 @@ st.set_page_config(
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initial_sidebar_state="expanded"
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)
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# Custom CSS for beautiful styling
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# Rose Pine Dark Theme CSS
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st.markdown("""
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<style>
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/* Import Google Fonts */
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@import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700&display=swap');
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/* Rose Pine Color Palette */
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:root {
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--rp-base: #191724;
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--rp-surface: #1f1d2e;
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--rp-overlay: #26233a;
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--rp-muted: #6e6a86;
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--rp-subtle: #908caa;
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--rp-text: #e0def4;
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--rp-love: #eb6f92;
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--rp-gold: #f6c177;
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--rp-rose: #ebbcba;
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--rp-pine: #31748f;
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--rp-foam: #9ccfd8;
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--rp-iris: #c4a7e7;
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}
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/* Global Styles */
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.stApp {
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font-family: 'Inter', sans-serif;
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background-color: var(--rp-base);
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color: var(--rp-text);
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}
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/* Override Streamlit's default colors */
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.main .block-container {
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background-color: var(--rp-base);
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color: var(--rp-text);
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}
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/* Sidebar styling */
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.css-1d391kg {
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background-color: var(--rp-surface);
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}
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.css-1lcbmhc {
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background-color: var(--rp-surface);
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}
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/* Header Styles */
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.main-header {
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font-size: 3rem;
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color: #1f77b4;
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font-size: 3.5rem;
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background: linear-gradient(135deg, var(--rp-iris), var(--rp-foam));
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-webkit-background-clip: text;
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-webkit-text-fill-color: transparent;
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background-clip: text;
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text-align: center;
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margin-bottom: 2rem;
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font-weight: bold;
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}
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.sub-header {
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font-size: 1.5rem;
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color: #2c3e50;
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margin-bottom: 1rem;
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font-weight: 700;
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letter-spacing: -1px;
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}
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.prediction-box {
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padding: 2rem;
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border-radius: 10px;
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.subtitle {
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text-align: center;
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font-size: 1.5rem;
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font-weight: bold;
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margin: 1rem 0;
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font-size: 1.2rem;
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color: var(--rp-subtle);
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margin-bottom: 3rem;
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font-weight: 400;
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}
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.sub-header {
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font-size: 1.4rem;
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color: var(--rp-text);
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margin-bottom: 1.5rem;
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font-weight: 600;
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border-bottom: 2px solid var(--rp-overlay);
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padding-bottom: 0.5rem;
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}
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/* Prediction Result Boxes */
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.prediction-box {
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padding: 2.5rem 2rem;
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border-radius: 16px;
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text-align: center;
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font-size: 1.8rem;
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font-weight: 700;
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margin: 2rem 0;
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box-shadow: 0 10px 30px rgba(0,0,0,0.3);
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transform: translateY(0);
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transition: transform 0.3s ease, box-shadow 0.3s ease;
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border: 2px solid;
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}
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.prediction-box:hover {
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transform: translateY(-5px);
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box-shadow: 0 20px 40px rgba(0,0,0,0.4);
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}
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.graduate-box {
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background: linear-gradient(135deg, #28a745, #20c997);
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color: white;
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background: linear-gradient(135deg, var(--rp-foam), var(--rp-pine));
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color: var(--rp-base);
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border-color: var(--rp-foam);
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}
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.dropout-box {
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background: linear-gradient(135deg, #dc3545, #fd7e14);
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color: white;
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background: linear-gradient(135deg, var(--rp-love), #c74665);
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color: var(--rp-text);
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border-color: var(--rp-love);
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}
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.enrolled-box {
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background: linear-gradient(135deg, #ffc107, #fd7e14);
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color: white;
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background: linear-gradient(135deg, var(--rp-gold), #e6a85c);
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color: var(--rp-base);
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border-color: var(--rp-gold);
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}
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/* Metric Cards */
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.metric-card {
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background: #f8f9fa;
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background: linear-gradient(135deg, var(--rp-surface), var(--rp-overlay));
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padding: 1.5rem;
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border-radius: 12px;
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border-left: 4px solid var(--rp-iris);
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box-shadow: 0 4px 12px rgba(0,0,0,0.2);
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transition: transform 0.2s ease;
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}
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.metric-card:hover {
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transform: translateY(-2px);
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box-shadow: 0 8px 20px rgba(0,0,0,0.3);
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}
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.metric-card h4 {
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color: var(--rp-subtle);
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font-weight: 600;
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margin-bottom: 0.5rem;
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}
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.metric-card h2 {
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color: var(--rp-iris);
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font-weight: 700;
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}
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/* Sidebar Styling */
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.sidebar-section {
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background: var(--rp-overlay);
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padding: 1rem;
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border-radius: 8px;
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border-left: 4px solid #1f77b4;
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margin-bottom: 1rem;
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border-left: 3px solid var(--rp-iris);
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}
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/* Info boxes */
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.info-box {
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background: linear-gradient(135deg, var(--rp-overlay), var(--rp-surface));
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padding: 1.5rem;
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border-radius: 12px;
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border-left: 4px solid var(--rp-foam);
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margin: 1rem 0;
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color: var(--rp-text);
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}
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.warning-box {
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background: linear-gradient(135deg, var(--rp-overlay), var(--rp-surface));
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padding: 1.5rem;
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border-radius: 12px;
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border-left: 4px solid var(--rp-gold);
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margin: 1rem 0;
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color: var(--rp-text);
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}
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.success-box {
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background: linear-gradient(135deg, var(--rp-overlay), var(--rp-surface));
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padding: 1.5rem;
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border-radius: 12px;
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border-left: 4px solid var(--rp-pine);
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margin: 1rem 0;
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color: var(--rp-text);
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}
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/* Button Styling */
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.stButton > button {
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background: linear-gradient(135deg, var(--rp-iris), var(--rp-love));
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color: var(--rp-text);
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border: none;
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border-radius: 25px;
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font-weight: 600;
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font-size: 1.1rem;
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padding: 0.75rem 2rem;
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transition: transform 0.2s ease, box-shadow 0.2s ease;
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}
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.stButton > button:hover {
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transform: translateY(-2px);
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box-shadow: 0 8px 20px rgba(196, 167, 231, 0.4);
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}
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/* Streamlit widget overrides */
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.stSelectbox > div > div {
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background-color: var(--rp-surface);
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color: var(--rp-text);
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border-color: var(--rp-overlay);
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}
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.stNumberInput > div > div > input {
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background-color: var(--rp-surface);
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color: var(--rp-text);
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border-color: var(--rp-overlay);
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}
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.stRadio > div {
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background-color: var(--rp-surface);
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border-radius: 8px;
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padding: 0.5rem;
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}
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/* Progress indicator */
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.progress-container {
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background: var(--rp-overlay);
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border-radius: 10px;
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height: 8px;
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margin: 1rem 0;
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}
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.progress-bar {
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background: linear-gradient(90deg, var(--rp-iris), var(--rp-foam));
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height: 100%;
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border-radius: 10px;
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transition: width 0.3s ease;
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}
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/* Section dividers */
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.section-divider {
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height: 2px;
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background: linear-gradient(90deg, transparent, var(--rp-iris), transparent);
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margin: 2rem 0;
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}
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/* Text color overrides */
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.markdown-text-container {
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color: var(--rp-text);
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}
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h1, h2, h3, h4, h5, h6 {
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color: var(--rp-text);
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}
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.stMarkdown {
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color: var(--rp-text);
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}
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/* Animations */
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@keyframes fadeInUp {
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from {
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opacity: 0;
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transform: translateY(30px);
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}
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to {
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opacity: 1;
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transform: translateY(0);
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}
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}
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.fade-in {
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animation: fadeInUp 0.6s ease forwards;
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}
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/* Mobile responsiveness */
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@media (max-width: 768px) {
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.main-header {
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font-size: 2.5rem !important;
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}
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.prediction-box {
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font-size: 1.4rem !important;
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padding: 1.5rem 1rem !important;
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}
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.metric-card {
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padding: 1rem !important;
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}
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}
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</style>
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""", unsafe_allow_html=True)
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@@ -252,7 +486,10 @@ def main():
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# Header
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st.markdown('<h1 class="main-header">Student Success Predictor</h1>', unsafe_allow_html=True)
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st.markdown("**Predict whether a student will Graduate, Dropout, or remain Enrolled based on academic and demographic factors.**")
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st.markdown('<p class="subtitle">Predict whether a student will Graduate, Dropout, or remain Enrolled based on academic and demographic factors using advanced machine learning.</p>', unsafe_allow_html=True)
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# Progress indicator (shows completion percentage)
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progress_placeholder = st.empty()
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# Sidebar for input
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st.sidebar.markdown('<h2 class="sub-header">Student Information</h2>', unsafe_allow_html=True)
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@@ -260,10 +497,12 @@ def main():
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# Create input form
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with st.sidebar:
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# Quick presets
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st.markdown("### Quick Start")
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st.markdown('<div class="sidebar-section">', unsafe_allow_html=True)
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st.markdown("### 🚀 Quick Start")
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preset = st.selectbox("Load Sample Data",
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["Custom Entry", "Typical Graduate Student", "At-Risk Student", "International Student"],
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help="Choose a preset to quickly fill common scenarios")
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st.markdown('</div>', unsafe_allow_html=True)
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# Set default values based on preset
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defaults = {
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@@ -274,10 +513,16 @@ def main():
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}
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if preset != "Custom Entry":
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st.info(f"Loading {preset} preset values. You can modify any field below.")
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st.markdown(f'<div class="success-box">✅ Loading <strong>{preset}</strong> preset values. You can modify any field below.</div>', unsafe_allow_html=True)
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# Form progress tracking
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form_sections = ["Personal Information", "Academic Background", "Family Background", "Financial & Social", "1st Semester Performance", "2nd Semester Performance", "Economic Indicators"]
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current_section = 0
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# Personal Information
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st.markdown("### Personal Information")
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st.markdown('<div class="section-divider"></div>', unsafe_allow_html=True)
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st.markdown("### 👤 Personal Information")
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st.markdown('<div class="info-box">Basic demographic information about the student</div>', unsafe_allow_html=True)
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marital_status = st.selectbox(
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"Marital Status",
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@@ -291,7 +536,9 @@ def main():
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nationality = st.selectbox("Nationality", [1, 2, 6, 11, 13, 14, 17, 21, 22, 24, 25, 26, 32, 41, 62, 100, 101, 103, 105, 108, 109], index=0)
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# Academic Background
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st.markdown("### Academic Background")
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st.markdown('<div class="section-divider"></div>', unsafe_allow_html=True)
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st.markdown("### 🎓 Academic Background")
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st.markdown('<div class="info-box">Information about the student\'s application and academic history</div>', unsafe_allow_html=True)
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application_mode = st.selectbox(
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"Application Mode",
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@@ -324,7 +571,9 @@ def main():
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admission_grade = st.number_input("Admission Grade", min_value=95, max_value=190, value=defaults[preset]["adm_grade"], step=1)
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# Family Background
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st.markdown("### Family Background")
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st.markdown('<div class="section-divider"></div>', unsafe_allow_html=True)
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st.markdown("### 👨👩👧👦 Family Background")
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st.markdown('<div class="info-box">Parent education and occupation information</div>', unsafe_allow_html=True)
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mothers_qualification = st.selectbox(
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"Mother's Qualification",
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@@ -351,7 +600,9 @@ def main():
|
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)
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||||
# Financial and Social Factors
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st.markdown("### Financial & Social")
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st.markdown('<div class="section-divider"></div>', unsafe_allow_html=True)
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||||
st.markdown("### 💰 Financial & Social")
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||||
st.markdown('<div class="info-box">Student financial status and special circumstances</div>', unsafe_allow_html=True)
|
||||
|
||||
col1, col2 = st.columns(2)
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with col1:
|
||||
@@ -364,8 +615,9 @@ def main():
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international = st.radio("International Student", [0, 1], format_func=lambda x: "No" if x == 0 else "Yes", horizontal=True)
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|
||||
# Academic Performance - 1st Semester
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||||
st.markdown("### 1st Semester Performance")
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||||
st.caption("Enter the student's academic performance for their first semester")
|
||||
st.markdown('<div class="section-divider"></div>', unsafe_allow_html=True)
|
||||
st.markdown("### 📚 1st Semester Performance")
|
||||
st.markdown('<div class="warning-box">⚠️ <strong>Important:</strong> Academic performance is a key predictor of student success</div>', unsafe_allow_html=True)
|
||||
|
||||
# Set default academic values based on preset
|
||||
first_sem_defaults = {
|
||||
@@ -386,8 +638,9 @@ def main():
|
||||
curricular_units_1st_sem_without_evaluations = st.number_input("Without Evaluations", min_value=0, max_value=14, value=first_sem_defaults[preset]["without"], step=1, key="1st_without", help="Courses registered but not evaluated")
|
||||
|
||||
# Academic Performance - 2nd Semester
|
||||
st.markdown("### 2nd Semester Performance")
|
||||
st.caption("Enter the student's academic performance for their second semester")
|
||||
st.markdown('<div class="section-divider"></div>', unsafe_allow_html=True)
|
||||
st.markdown("### 📖 2nd Semester Performance")
|
||||
st.markdown('<div class="info-box">Second semester data helps improve prediction accuracy</div>', unsafe_allow_html=True)
|
||||
|
||||
# Set default academic values for 2nd semester based on preset
|
||||
second_sem_defaults = {
|
||||
@@ -408,8 +661,9 @@ def main():
|
||||
curricular_units_2nd_sem_without_evaluations = st.number_input("Without Evaluations", min_value=0, max_value=12, value=second_sem_defaults[preset]["without"], step=1, key="2nd_without", help="Courses registered but not evaluated")
|
||||
|
||||
# Economic Indicators
|
||||
st.markdown("### Economic Indicators")
|
||||
st.caption("These are typically set by the institution based on current economic conditions")
|
||||
st.markdown('<div class="section-divider"></div>', unsafe_allow_html=True)
|
||||
st.markdown("### 📊 Economic Indicators")
|
||||
st.markdown('<div class="info-box">📈 Economic context data - typically set by institution based on current conditions</div>', unsafe_allow_html=True)
|
||||
|
||||
col1, col2, col3 = st.columns(3)
|
||||
with col1:
|
||||
@@ -465,9 +719,32 @@ def main():
|
||||
with col1:
|
||||
st.markdown('<h2 class="sub-header">Prediction Results</h2>', unsafe_allow_html=True)
|
||||
|
||||
# Make prediction
|
||||
if st.button("Predict Student Outcome", type="primary"):
|
||||
with st.spinner("Analyzing student data..."):
|
||||
# Prediction button with enhanced styling
|
||||
predict_button = st.button("🔬 Analyze Student Data", type="primary", use_container_width=True)
|
||||
|
||||
if predict_button:
|
||||
# Enhanced loading animation
|
||||
progress_bar = st.progress(0)
|
||||
status_text = st.empty()
|
||||
|
||||
# Simulate processing steps
|
||||
steps = [
|
||||
("Loading student data...", 20),
|
||||
("Preprocessing features...", 40),
|
||||
("Running machine learning model...", 70),
|
||||
("Calculating prediction confidence...", 90),
|
||||
("Finalizing results...", 100)
|
||||
]
|
||||
|
||||
for step, progress in steps:
|
||||
status_text.text(step)
|
||||
progress_bar.progress(progress)
|
||||
time.sleep(0.3)
|
||||
|
||||
# Clear progress indicators
|
||||
progress_bar.empty()
|
||||
status_text.empty()
|
||||
|
||||
# Preprocess input
|
||||
processed_input = preprocess_input(user_input, preprocessing_info)
|
||||
|
||||
@@ -479,16 +756,56 @@ def main():
|
||||
target_reverse_mapping = preprocessing_info['target_reverse_mapping']
|
||||
predicted_outcome = target_reverse_mapping[prediction]
|
||||
|
||||
# Display prediction with styling
|
||||
# Store in session state for export
|
||||
st.session_state['last_prediction'] = {
|
||||
'outcome': predicted_outcome,
|
||||
'probabilities': prediction_proba,
|
||||
'timestamp': time.time()
|
||||
}
|
||||
|
||||
# Enhanced prediction display with confidence indicators
|
||||
confidence_level = max(prediction_proba)
|
||||
confidence_text = "High" if confidence_level > 0.7 else "Medium" if confidence_level > 0.5 else "Low"
|
||||
|
||||
# Display prediction with enhanced styling and confidence
|
||||
if predicted_outcome == "Graduate":
|
||||
st.markdown(f'<div class="prediction-box graduate-box">Predicted Outcome: GRADUATE</div>', unsafe_allow_html=True)
|
||||
st.markdown(f'''<div class="prediction-box graduate-box fade-in">
|
||||
🎓 GRADUATE
|
||||
<br><small style="font-size: 1rem; opacity: 0.9;">Confidence: {confidence_level:.1%} ({confidence_text})</small>
|
||||
</div>''', unsafe_allow_html=True)
|
||||
st.balloons()
|
||||
elif predicted_outcome == "Dropout":
|
||||
st.markdown(f'<div class="prediction-box dropout-box">Predicted Outcome: DROPOUT</div>', unsafe_allow_html=True)
|
||||
st.markdown(f'''<div class="prediction-box dropout-box fade-in">
|
||||
⚠️ AT RISK OF DROPOUT
|
||||
<br><small style="font-size: 1rem; opacity: 0.9;">Confidence: {confidence_level:.1%} ({confidence_text})</small>
|
||||
</div>''', unsafe_allow_html=True)
|
||||
else:
|
||||
st.markdown(f'<div class="prediction-box enrolled-box">Predicted Outcome: ENROLLED</div>', unsafe_allow_html=True)
|
||||
st.markdown(f'''<div class="prediction-box enrolled-box fade-in">
|
||||
📚 LIKELY TO STAY ENROLLED
|
||||
<br><small style="font-size: 1rem; opacity: 0.9;">Confidence: {confidence_level:.1%} ({confidence_text})</small>
|
||||
</div>''', unsafe_allow_html=True)
|
||||
|
||||
# Add personalized recommendations based on prediction
|
||||
st.markdown("### 💡 Personalized Recommendations")
|
||||
|
||||
if predicted_outcome == "Graduate":
|
||||
st.markdown('<div class="success-box">🎯 <strong>Success Indicators:</strong> This student shows strong potential for graduation. Continue supporting their academic journey.</div>', unsafe_allow_html=True)
|
||||
elif predicted_outcome == "Dropout":
|
||||
recommendations = []
|
||||
if user_input['Curricular units 1st sem (approved)'] == 0:
|
||||
recommendations.append("📚 **Academic Support:** Provide tutoring for struggling courses")
|
||||
if user_input['Scholarship holder'] == 0:
|
||||
recommendations.append("💰 **Financial Aid:** Consider scholarship opportunities")
|
||||
if user_input['Age at enrollment'] > 25:
|
||||
recommendations.append("🕐 **Flexible Scheduling:** Offer evening or part-time options")
|
||||
|
||||
if recommendations:
|
||||
st.markdown('<div class="warning-box">🎯 <strong>Intervention Strategies:</strong><br>' + '<br>'.join(recommendations) + '</div>', unsafe_allow_html=True)
|
||||
else:
|
||||
st.markdown('<div class="info-box">📈 <strong>Monitoring Needed:</strong> This student may benefit from regular check-ins and academic support.</div>', unsafe_allow_html=True)
|
||||
|
||||
# Display probabilities
|
||||
st.markdown("### Prediction Confidence")
|
||||
st.markdown("### 📊 Prediction Confidence")
|
||||
|
||||
prob_df = pd.DataFrame({
|
||||
'Outcome': ['Dropout', 'Enrolled', 'Graduate'],
|
||||
@@ -539,16 +856,40 @@ def main():
|
||||
""", unsafe_allow_html=True)
|
||||
|
||||
with col2:
|
||||
st.markdown('<h2 class="sub-header">About the Model</h2>', unsafe_allow_html=True)
|
||||
st.markdown('<h2 class="sub-header">📊 Model Insights</h2>', unsafe_allow_html=True)
|
||||
|
||||
st.info("""
|
||||
**Model Details:**
|
||||
# Dynamic model information based on current inputs
|
||||
st.markdown('<div class="info-box">', unsafe_allow_html=True)
|
||||
st.markdown("""
|
||||
**🤖 Model Details:**
|
||||
- **Algorithm:** Random Forest Classifier
|
||||
- **Features:** 36 student characteristics
|
||||
- **Training Accuracy:** 100%
|
||||
- **Test Accuracy:** 93.84%
|
||||
- **Classes:** Graduate, Dropout, Enrolled
|
||||
""")
|
||||
st.markdown('</div>', unsafe_allow_html=True)
|
||||
|
||||
# Add input validation feedback
|
||||
st.markdown("### 🔍 Input Validation")
|
||||
validation_container = st.container()
|
||||
|
||||
# Basic validation checks
|
||||
validation_issues = []
|
||||
|
||||
# Check for unrealistic combinations
|
||||
if user_input['Age at enrollment'] < 17:
|
||||
validation_issues.append("⚠️ Age seems too low for enrollment")
|
||||
if user_input['Curricular units 1st sem (approved)'] > user_input['Curricular units 1st sem (enrolled)']:
|
||||
validation_issues.append("⚠️ Approved units exceed enrolled units (1st sem)")
|
||||
if user_input['Curricular units 2nd sem (approved)'] > user_input['Curricular units 2nd sem (enrolled)']:
|
||||
validation_issues.append("⚠️ Approved units exceed enrolled units (2nd sem)")
|
||||
|
||||
if validation_issues:
|
||||
for issue in validation_issues:
|
||||
st.warning(issue)
|
||||
else:
|
||||
st.success("✅ All inputs look valid!")
|
||||
|
||||
st.markdown("### Key Factors")
|
||||
st.markdown("""
|
||||
@@ -594,9 +935,46 @@ def main():
|
||||
|
||||
st.plotly_chart(fig_perf, use_container_width=True)
|
||||
|
||||
# Footer
|
||||
# Add export functionality
|
||||
st.markdown("### 📥 Export Results")
|
||||
|
||||
if st.session_state.get('last_prediction'):
|
||||
export_data = {
|
||||
'timestamp': time.strftime('%Y-%m-%d %H:%M:%S'),
|
||||
'prediction': st.session_state['last_prediction']['outcome'],
|
||||
'confidence': f"{max(st.session_state['last_prediction']['probabilities']):.1%}",
|
||||
'student_data': user_input
|
||||
}
|
||||
|
||||
# Convert to JSON for download
|
||||
import json
|
||||
json_str = json.dumps(export_data, indent=2, ensure_ascii=False)
|
||||
|
||||
st.download_button(
|
||||
label="📁 Download Prediction Report",
|
||||
data=json_str,
|
||||
file_name=f"student_prediction_{time.strftime('%Y%m%d_%H%M%S')}.json",
|
||||
mime="application/json"
|
||||
)
|
||||
|
||||
# Enhanced Footer with additional info
|
||||
st.markdown('<div class="section-divider"></div>', unsafe_allow_html=True)
|
||||
col1, col2, col3 = st.columns(3)
|
||||
|
||||
with col1:
|
||||
st.markdown("**📊 Data Source**")
|
||||
st.caption("UCI ML Repository - Student Academic Success")
|
||||
|
||||
with col2:
|
||||
st.markdown("**🔬 Model Info**")
|
||||
st.caption("Random Forest with 93.84% accuracy")
|
||||
|
||||
with col3:
|
||||
st.markdown("**🛠️ Built With**")
|
||||
st.caption("Streamlit • scikit-learn • Plotly")
|
||||
|
||||
st.markdown("---")
|
||||
st.markdown("*Developed using Streamlit and scikit-learn*")
|
||||
st.markdown('<p style="text-align: center; color: #6c757d; font-size: 0.9rem;">🎓 Empowering educational institutions with data-driven insights for student success</p>', unsafe_allow_html=True)
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user