Update app.py

app.py

@@ -19,6 +19,14 @@ size_map = json.load(open("size_map.json"))
 raw_data = pd.read_csv("./tagged_data.csv")
 
 def plot_scatter(cat, x, y, col):
+    if cat != "All":
+        data = raw_data[raw_data["Category"] == cat]
+    else:
+        data = raw_data
+    # Group and normalize the data
+    grouped_cat = data.groupby(["model", "tag"]).size().reset_index(name="count").sort_values(by="count", ascending=False)
+    grouped_cat["count"] = grouped_cat.groupby(["model"])["count"].transform(lambda x: x / x.sum())
+    
     # minimal example
     pivot_df = grouped_cat.pivot(index='model', columns='tag', values='count').fillna(0).reset_index()
 
@@ -33,14 +41,6 @@ def plot_scatter(cat, x, y, col):
         color=col,
         color_continuous_scale="agsunset")
 
-    # if cat != "All":
-    #     data = raw_data[raw_data["Category"] == cat]
-    # else:
-    #     data = raw_data
-    # # Group and normalize the data
-    # grouped_cat = data.groupby(["model", "tag"]).size().reset_index(name="count").sort_values(by="count", ascending=False)
-    # grouped_cat["count"] = grouped_cat.groupby(["model"])["count"].transform(lambda x: x / x.sum())
-
     # # Pivot the data for stacking
     # pivot_df = grouped_cat.pivot(index='model', columns='tag', values='count').fillna(0)
     # # pivot_df = pivot_df.sort_values(by="A", ascending=False)