Update app.py

app.py

@@ -3,14 +3,12 @@ from huggingface_hub import list_models, list_datasets, list_spaces
 import pandas as pd
 from datetime import datetime
 
-
 def get_user_stats():
     users = {}
     for k, fn in zip(['model', 'dataset', 'space'], [list_models, list_datasets, list_spaces]):
         for repo in fn(full=True):
             if repo.author is None:
                 continue
-
             if repo.author not in users:
                 users[repo.author] = {
                     x: 0 for x in [
@@ -30,21 +28,18 @@ def get_user_stats():
     for username, user_stats in users.items():
         users[username]['total_likes'] += sum([v for k, v in user_stats.items() if "likes" in k])
         users[username]['total_repos'] += sum([v for k, v in user_stats.items() if "num_" in k])
-
     for k, v in users.items():
         users[k] = dict(users[k])
-
     return users
 
 def make_clickable_user(user_id):
     link = "https://huggingface.co/" + user_id
-    return f'<a  target="_blank" href="{link}">{user_id}</a>'
-
+    return f'<a target="_blank" href="{link}">{user_id}</a>'
 
 def get_user_stats_df(limit=1000):
     users = get_user_stats()
     df = pd.DataFrame([{'username': make_clickable_user(k), **v} for k, v in users.items()])
-    df.sort_values(by=["total_likes"], ascending=False, inplace=True)
+    df.sort_values(by=["num_spaces"], ascending=False, inplace=True)  # Sort by num_spaces in descending order
     df.insert(0, "rank", list(range(1, len(df) + 1)))
     df = df[
         [
@@ -65,11 +60,12 @@ def get_user_stats_df(limit=1000):
     return df
 
 df = get_user_stats_df()
+
 desc = f"""
 # 🤗 Hugging Face User Stats
-
-Here are some stats on the top 1000 users/organizations on the Hugging Face Hub. **Updated {datetime.now().strftime("%d/%m/%y")}**
+Here are some stats on the top 1000 users/organizations on the Hugging Face Hub, sorted by the number of Spaces. **Updated {datetime.now().strftime("%d/%m/%y")}**
 """
+
 with gr.Blocks() as demo:
     gr.Markdown(desc)
     data = gr.components.Dataframe(
@@ -77,4 +73,5 @@ with gr.Blocks() as demo:
         type="pandas",
         datatype=["number", "markdown", "number", "number", "number", "number", "number", "number", "number", "number"],
     )
+
 demo.launch()