streamlit.errors.StreamlitAPIException: The default value 'Galen Sasaki' is not part of the options.

Removed manual defaults for filters in session state; each multiselect now simply uses its full options list as the default.

On Clear All Filters, we reset standing, dept, and mark names for re-initialization.

For Faculty selection, we:

Initialize st.session_state.names to the available names on first load or after clear.

Prune it to remain a subset of the dynamically filtered name_opts.

Use that as the default, so you never get a “default not in options” error.

app.py

@@ -24,46 +24,50 @@ def wrap_labels(labels, width=40):
 # Sidebar: Filters
 # ---------------------------------------------------
 st.sidebar.title("Filters")
-# Ensure session state keys exist
-if 'standing' not in st.session_state:
-    st.session_state.standing = sorted(df['Standing'].dropna().astype(str).unique())
-if 'dept' not in st.session_state:
-    st.session_state.dept = sorted(df['Dept Track'].dropna().astype(str).unique())
 
-clear = st.sidebar.button("Clear All Filters")
-if clear:
-    st.session_state.standing = sorted(df['Standing'].dropna().astype(str).unique())
-    st.session_state.dept = sorted(df['Dept Track'].dropna().astype(str).unique())
+# Base options
+def_opts = sorted(df['Dept Track'].dropna().astype(str).unique())
+def_stand = sorted(df['Standing'].dropna().astype(str).unique())
 
-standing_opts = sorted(df['Standing'].dropna().astype(str).unique())
-dept_opts = sorted(df['Dept Track'].dropna().astype(str).unique())
+# Clear filters button
+if st.sidebar.button("Clear All Filters"):
+    st.session_state.standing = def_stand
+    st.session_state.dept = def_opts
+    # We'll reinitialize names below
+    st.session_state.names = None
 
+# Multiselects for filters, store in session_state
 standing_sel = st.sidebar.multiselect(
     "Filter by Standing:",
-    options=standing_opts,
-    default=st.session_state.standing,
+    options=def_stand,
+    default=def_stand,
     key='standing'
 )
 dept_sel = st.sidebar.multiselect(
     "Filter by Dept Track:",
-    options=dept_opts,
-    default=st.session_state.dept,
+    options=def_opts,
+    default=def_opts,
     key='dept'
 )
 
-# Auto-filter names based on filters
+# Determine available names based on current filters
 mask = (
     df['Standing'].astype(str).isin(standing_sel) &
     df['Dept Track'].astype(str).isin(dept_sel)
 )
-name_options = sorted(df.loc[mask, 'Name'].astype(str).unique())
+name_opts = sorted(df.loc[mask, 'Name'].astype(str).unique())
 
-if 'names' not in st.session_state or clear:
-    st.session_state.names = name_options
+# Initialize or clean session_state.names
+if 'names' not in st.session_state or st.session_state.names is None:
+    st.session_state.names = name_opts.copy()
+else:
+    # drop any names no longer in options
+    st.session_state.names = [n for n in st.session_state.names if n in name_opts]
 
+# Faculty selection
 name_sel = st.sidebar.multiselect(
     "Select Faculty:",
-    options=name_options,
+    options=name_opts,
     default=st.session_state.names,
     key='names'
 )
@@ -73,7 +77,7 @@ name_sel = st.sidebar.multiselect(
 # ---------------------------------------------------
 st.title("Faculty Heatmap Explorer")
 
-# 1) Heatmap display
+# Heatmap
 if not name_sel:
     st.warning("No faculty selected — please choose at least one.")
     fig = px.imshow(
@@ -89,9 +93,9 @@ else:
         sum_df = mat if sum_df is None else sum_df.add(mat, fill_value=0)
     avg_df = sum_df.div(len(name_sel))
 
-    # Wrap y labels (rows)
+    # Wrap labels
     wrapped_y = wrap_labels(list(avg_df.index), width=40)
-    wrapped_x = list(avg_df.columns)  # x labels usually short
+    wrapped_x = list(avg_df.columns)
 
     fig = px.imshow(
         avg_df.values,
@@ -104,11 +108,10 @@ else:
     fig.update_yaxes(autorange='reversed')
     st.plotly_chart(fig, use_container_width=True)
 
-    # 2) Click-to-list values
+    # Cell details
     st.subheader("Cell Details")
     events = plotly_events(fig, click_event=True, key="heatmap")
     if events:
-        # Determine original row & col from pointNumber
         n_cols = avg_df.shape[1]
         pt = events[0]
         pt_num = pt.get('pointNumber', None)
@@ -118,11 +121,9 @@ else:
             y_lab = avg_df.index[row_idx]
             x_lab = avg_df.columns[col_idx]
         else:
-            # fallback: use string labels (unlikely)
-            y_lab_wrapped = pt['y']
+            y_wrapped = pt['y']
             x_lab = pt['x']
-            # map back wrapped to original
-            y_lab = avg_df.index[wrapped_y.index(y_lab_wrapped)]
+            y_lab = avg_df.index[wrapped_y.index(y_wrapped)]
 
         # Gather non-zero values
         records = []
@@ -138,3 +139,4 @@ else:
             st.info("No non-zero values for this cell.")
     else:
         st.write("Click on a heatmap cell to list faculty and their values.")
+