neurips 2024

df/PaperCentral.py

@@ -23,6 +23,7 @@ class PaperCentral:
     """
 
     CONFERENCES_ICONS = {
+        "NeurIPS2024": NEURIPS_ICO,
         "EMNLP2024": 'https://aclanthology.org/aclicon.ico',
         "CoRL2024": CORL_ICO,
         "ACMMM2024": "https://2024.acmmm.org/favicon.ico",
@@ -392,6 +393,12 @@ class PaperCentral:
 
         # Handle Hugging Face options
         if hf_options:
+            # Convert columns to numeric, handling non-numeric values
+            filtered_df['num_datasets'] = pd.to_numeric(filtered_df['num_datasets'], errors='coerce').fillna(0).astype(
+                int)
+            filtered_df['num_models'] = pd.to_numeric(filtered_df['num_models'], errors='coerce').fillna(0).astype(int)
+            filtered_df['num_spaces'] = pd.to_numeric(filtered_df['num_spaces'], errors='coerce').fillna(0).astype(int)
+
             if "🤗 artifacts" in hf_options:
                 filtered_df = filtered_df[
                     (filtered_df['paper_page'] != "") & (filtered_df['paper_page'].notna())
@@ -407,28 +414,25 @@ class PaperCentral:
                 if 'num_spaces' not in columns_to_show:
                     columns_to_show.append('num_spaces')
 
+                filtered_df = filtered_df[
+                    (filtered_df['num_datasets'] > 0) |
+                    (filtered_df['num_models'] > 0) |
+                    (filtered_df['num_spaces'] > 0)
+                    ]
+
             if "datasets" in hf_options:
                 if 'num_datasets' not in columns_to_show:
                     columns_to_show.append('num_datasets')
-                # Convert to integer, handling possible non-numeric values
-                filtered_df['num_datasets'] = pd.to_numeric(filtered_df['num_datasets'], errors='coerce').fillna(
-                    0).astype(int)
                 filtered_df = filtered_df[filtered_df['num_datasets'] != 0]
 
             if "models" in hf_options:
                 if 'num_models' not in columns_to_show:
                     columns_to_show.append('num_models')
-                # Convert to integer, handling possible non-numeric values
-                filtered_df['num_models'] = pd.to_numeric(filtered_df['num_models'], errors='coerce').fillna(0).astype(
-                    int)
                 filtered_df = filtered_df[filtered_df['num_models'] != 0]
 
             if "spaces" in hf_options:
                 if 'num_spaces' not in columns_to_show:
                     columns_to_show.append('num_spaces')
-                # Convert to integer, handling possible non-numeric values
-                filtered_df['num_spaces'] = pd.to_numeric(filtered_df['num_spaces'], errors='coerce').fillna(0).astype(
-                    int)
                 filtered_df = filtered_df[filtered_df['num_spaces'] != 0]
 
             if "github" in hf_options: