Update app.py

app.py

@@ -15,38 +15,48 @@ st.set_page_config(
 st.title("📊 Catalog Data Dashboard")
 st.markdown(
     """
-    This dashboard combines live Google Sheets data for:
+    This dashboard combines Static Data with live Google Sheets data for:
     - catalog onboarding  
-    - metadata completeness  
-    - mapping/scraping status  
+    - metadata completeness
     """
 )
 
+if st.button("🔄 Refresh Data"):
+    st.cache_data.clear()
+    st.toast("Refreshing data...", icon="🔄")
+    st.rerun()
+
 cat_onboarding_df, cat_metadata_df, cat_status_df = get_data()
 
-tab0, tab1, tab2, tab3, tab4 = st.tabs(["Overview", "Static Data", "Onboarding Status", "Metadata Completeness", "Mapping Status"])
+tab1, tab2, tab3 = st.tabs([
+                                # "Overview", 
+                                "Static Data", 
+                                "Onboarding Status", 
+                                "Metadata Completeness", 
+                                # "Mapping Status"
+])
 
 # =========================================================================================================================
 # Tab 0 - Overview
 # =========================================================================================================================
 
-with tab0:
-    st.header("Overiew")
-    if st.button("🔄 Refresh Data"):
-        st.cache_data.clear()
-        st.toast("Refreshing data...", icon="🔄")
-        st.rerun()
+# with tab0:
+#     st.header("Overiew")
+#     if st.button("🔄 Refresh Data"):
+#         st.cache_data.clear()
+#         st.toast("Refreshing data...", icon="🔄")
+#         st.rerun()
 
-    st.markdown("---")
-    st.subheader("Quick Data Preview")
+#     st.markdown("---")
+#     st.subheader("Quick Data Preview")
 
-    col1, col2, col3 = st.columns(3)
-    with col1:
-        st.dataframe(cat_onboarding_df.head(5))
-    with col2:
-        st.dataframe(cat_metadata_df.head(5))
-    with col3:
-        st.dataframe(cat_status_df.head(5))
+#     col1, col2, col3 = st.columns(3)
+#     with col1:
+#         st.dataframe(cat_onboarding_df.head(5))
+#     with col2:
+#         st.dataframe(cat_metadata_df.head(5))
+#     with col3:
+#         st.dataframe(cat_status_df.head(5))
 
 # =========================================================================================================================
 # Tab 0 - Static stuff
@@ -338,69 +348,69 @@ with tab3:
 
     st.plotly_chart(fig_field_coverage, use_container_width=True)
 
-    # heatmap 1
-        # Prepare data
-    z = cat_df_numeric[meta_cols].astype(float).to_numpy()
-    x = list(meta_cols)
-    y = list(cat_df_numeric["Catalog name"].astype(str))
-
-    # Build the heatmap (no annotation_text)
-    fig_heatmap = ff.create_annotated_heatmap(
-        z=z,
-        x=x,
-        y=y,
-        showscale=True,
-        colorscale=[
-            [0.0, "rgb(255,77,77)"],     # red for 0 (No)
-            [0.5, "rgb(255,204,0)"],     # yellow for 0.5 (Some)
-            [1.0, "rgb(0,204,102)"]      # green for 1 (Yes)
-        ],
-        annotation_text=None   # removes numbers
-    )
-
-    # Layout adjustments
-    fig_heatmap.update_layout(
-        title="Metadata Completeness Heatmap (Catalog vs Field)",
-        xaxis_title="Metadata Field",
-        yaxis_title="Catalog Name",
-        width=1600,   # make it wide
-        height=1000,  # make it tall so names fit
-        margin=dict(l=200, r=50, t=80, b=150),  # spacing for labels
-    )
-
-    # Tweak label angles for readability
-    fig_heatmap.update_xaxes(tickangle=-45)
-    fig_heatmap.update_yaxes(automargin=True)
-
-    st.plotly_chart(fig_heatmap, use_container_width=True)
-
-
-    # heatmap 2
-
-    fig_heatmap1 = px.imshow(
-    cat_df_numeric[meta_cols],
-    labels=dict(x="Metadata Field", y="Catalog Name", color="Completeness"),
-    x=meta_cols,
-    y=cat_df_numeric["Catalog name"],
-    color_continuous_scale=[
-        [0.0, "rgb(255,77,77)"],
-        [0.5, "rgb(255,204,0)"],
-        [1.0, "rgb(0,204,102)"]
-    ],
-    )
-
-    fig_heatmap1.update_layout(
-        title="Metadata Completeness Heatmap (Catalog vs Field)",
-        width=1600,
-        height=1000,
-        margin=dict(l=200, r=50, t=80, b=150),
-    )
-    fig_heatmap1.update_xaxes(tickangle=-45)
-
-    st.plotly_chart(fig_heatmap1, use_container_width=True)
-
-
-
-with tab4:
-    st.header("Catalog Mapping status")
+    # # heatmap 1
+    #     # Prepare data
+    # z = cat_df_numeric[meta_cols].astype(float).to_numpy()
+    # x = list(meta_cols)
+    # y = list(cat_df_numeric["Catalog name"].astype(str))
+
+    # # Build the heatmap (no annotation_text)
+    # fig_heatmap = ff.create_annotated_heatmap(
+    #     z=z,
+    #     x=x,
+    #     y=y,
+    #     showscale=True,
+    #     colorscale=[
+    #         [0.0, "rgb(255,77,77)"],     # red for 0 (No)
+    #         [0.5, "rgb(255,204,0)"],     # yellow for 0.5 (Some)
+    #         [1.0, "rgb(0,204,102)"]      # green for 1 (Yes)
+    #     ],
+    #     annotation_text=None   # removes numbers
+    # )
+
+    # # Layout adjustments
+    # fig_heatmap.update_layout(
+    #     title="Metadata Completeness Heatmap (Catalog vs Field)",
+    #     xaxis_title="Metadata Field",
+    #     yaxis_title="Catalog Name",
+    #     width=1600,   # make it wide
+    #     height=1000,  # make it tall so names fit
+    #     margin=dict(l=200, r=50, t=80, b=150),  # spacing for labels
+    # )
+
+    # # Tweak label angles for readability
+    # fig_heatmap.update_xaxes(tickangle=-45)
+    # fig_heatmap.update_yaxes(automargin=True)
+
+    # st.plotly_chart(fig_heatmap, use_container_width=True)
+
+
+    # # heatmap 2
+
+    # fig_heatmap1 = px.imshow(
+    # cat_df_numeric[meta_cols],
+    # labels=dict(x="Metadata Field", y="Catalog Name", color="Completeness"),
+    # x=meta_cols,
+    # y=cat_df_numeric["Catalog name"],
+    # color_continuous_scale=[
+    #     [0.0, "rgb(255,77,77)"],
+    #     [0.5, "rgb(255,204,0)"],
+    #     [1.0, "rgb(0,204,102)"]
+    # ],
+    # )
+
+    # fig_heatmap1.update_layout(
+    #     title="Metadata Completeness Heatmap (Catalog vs Field)",
+    #     width=1600,
+    #     height=1000,
+    #     margin=dict(l=200, r=50, t=80, b=150),
+    # )
+    # fig_heatmap1.update_xaxes(tickangle=-45)
+
+    # st.plotly_chart(fig_heatmap1, use_container_width=True)
+
+
+
+# with tab4:
+#     st.header("Catalog Mapping status")