Update app.py

app.py

@@ -53,7 +53,7 @@ COLUMN_GROUPS = {
     },
     "world_model_group": [
         'wm_recipe_percent_error', 'wm_geoguesser_mae', 'wm_weight_percent_error',
-        'wm_music_mae', 'wm_youtube_view_percent_error', 'Show Rec Score',
+        'wm_music_mae', 'Show Rec Score',
         "Show Rec MAE", "Show Rec Correlation", "Show Rec Std Dev Error"
     ],
 }
@@ -805,7 +805,7 @@ MASTER_COLUMN_ORDER = [
     "NatInt 💡",
     "Standard", "Pop Culture", "World Model",
     'wm_recipe_percent_error', 'wm_geoguesser_mae', 'wm_weight_percent_error',
-    'wm_music_mae', 'wm_youtube_view_percent_error',
+    'wm_music_mae',
     "Show Rec Score", # Main Score
     "Show Rec MAE", "Show Rec Correlation", "Show Rec Std Dev Error",
     # Writing
@@ -862,7 +862,6 @@ ALL_COLUMN_DEFS = {
     'wm_geoguesser_mae': create_numeric_column('wm_geoguesser_mae', headerName="GeoGuesser (km Error)", width=120, filterParams={"defaultOption": "lessThanOrEqual"}, sortingOrder=['asc', 'desc']),
     'wm_weight_percent_error': create_numeric_column('wm_weight_percent_error', headerName="Weight (% Error)", width=120, filterParams={"defaultOption": "lessThanOrEqual"}, sortingOrder=['asc', 'desc']),
     'wm_music_mae': create_numeric_column('wm_music_mae', headerName="Music (Error)", width=120, filterParams={"defaultOption": "lessThanOrEqual"}, sortingOrder=['asc', 'desc']),
-    'wm_youtube_view_percent_error': create_numeric_column('wm_youtube_view_percent_error', headerName="YouTube Views (% Error)", width=126, filterParams={"defaultOption": "lessThanOrEqual"}, sortingOrder=['asc', 'desc']),
     "Show Rec Score": create_numeric_column(
         "Show Rec Score", 
         headerName="Show Rec Score", 
@@ -1198,7 +1197,6 @@ app.layout = html.Div([
                     html.Li([html.Strong("GeoGuesser (km Error):"), " Identifies a location based on a description of its surroundings."]),
                     html.Li([html.Strong("Weight (% Error):"), " Estimates the weight of various objects based on their description."]),
                     html.Li([html.Strong("Music (Error):"), " Predicts a song's musical attributes (like bpm and loudness) based on its lyrics."]),
-                    html.Li([html.Strong("YouTube Views (% Error):"), " Estimates a video's view count from its title, given examples from the same channel."]),
                     html.Li([html.Strong("Show Recommendation Score:"), " A model's ability to predict what rating out of ten a person will rate a TV show based on their previous ratings."]),
                     html.Ul([
                         html.Li([html.Strong("Show Rec MAE:"), " The mean absolute error between the model's predicted ratings and the user's true ratings."]),