Update README.md

README.md

@@ -67,6 +67,30 @@ amazon-2023-all-category-k-core/
 3. Filter out the `meta` data and `reviews` of items that are not in the filtered `ratings`.
 4. Save the datasets in `.parquet` format.
 
+### Core Code Snippets
+
+```python
+# Iteratively remove all users and items with fewer than k ratings
+
+k = 20
+
+while True:
+    user_counts = df['user_id'].value_counts()
+    item_counts = df['parent_asin'].value_counts()
+    
+    filtered_df = df[
+        df['user_id'].isin(user_counts[user_counts >= k].index) &
+        df['parent_asin'].isin(item_counts[item_counts >= k].index)
+    ]
+    
+    if len(filtered_df) == len(df):
+        break
+    
+    df = filtered_df
+
+# `df` or `filtered_df` would be the resulted data.
+```
+
 ## Dataset Sources
 
 The original dataset is available at [Amazon reviews dataset](https://amazon-reviews-2023.github.io/).