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Update app.py
Browse files
app.py
CHANGED
@@ -239,33 +239,49 @@ if fetch_data:
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completeness_df = pd.DataFrame({"Field": completeness.index, "Completeness (%)": completeness.values})
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completeness_table = completeness_df.set_index("Field")
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# Prepare
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quick_stats_df_reset = quick_stats_df.reset_index(drop=True)
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styled_stats = (
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quick_stats_df_reset.style
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.background_gradient(cmap="
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.format({"Value": "{:.1f}"})
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.set_properties(**{
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"text-align": "center",
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"color": "
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"font-size": "
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"font-weight": "bold"
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})
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)
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#
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st.sidebar.dataframe(
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styled_stats,
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use_container_width=True,
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height=
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hide_index=True
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)
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st.sidebar.table(styled_stats)
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# Calculate Top 10 Subjects
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if 'subject' in metadata_df.columns:
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completeness_df = pd.DataFrame({"Field": completeness.index, "Completeness (%)": completeness.values})
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completeness_table = completeness_df.set_index("Field")
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# Prepare Quick Stats
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quick_stats_df_reset = quick_stats_df.reset_index(drop=True)
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# Apply background gradient to values
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styled_stats = (
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quick_stats_df_reset.style
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.background_gradient(cmap="Reds", subset=["Value"]) # π₯ red theme
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.format({"Value": "{:.1f}"})
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.set_properties(**{
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"text-align": "center",
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"color": "lightgray",
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"font-size": "1rem",
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"font-weight": "bold",
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"border-color": "#2b2b2b",
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})
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)
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# Custom CSS Card Wrapper
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st.sidebar.markdown("""
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<div style='
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background-color: #2e2e2e;
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padding: 1.5rem;
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border-radius: 12px;
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margin-bottom: 1.5rem;
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box-shadow: 0 8px 16px rgba(0, 0, 0, 0.3);
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transition: transform 0.3s ease, box-shadow 0.3s ease;
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'
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onmouseover="this.style.transform='scale(1.02)'; this.style.boxShadow='0 12px 24px rgba(0,0,0,0.4)';"
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onmouseout="this.style.transform='scale(1)'; this.style.boxShadow='0 8px 16px rgba(0,0,0,0.3)';"
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>
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<h4 style='color: #ff7f7f; margin-bottom: 1rem;'>π Quick Stats</h4>
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""", unsafe_allow_html=True)
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# Render styled table inside the "card"
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st.sidebar.dataframe(
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styled_stats,
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use_container_width=True,
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height=250,
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hide_index=True
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)
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# Close the div
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st.sidebar.markdown("</div>", unsafe_allow_html=True)
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# Calculate Top 10 Subjects
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if 'subject' in metadata_df.columns:
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