Update README.md

README.md

@@ -23,14 +23,6 @@ Korean sentiment classification dataset
 - Size: 460K(+180K)
 - Language: Korean-centric
 
-### Usage
-```python
-from datasets import load_dataset
-
-kr3 = load_dataset("Wittgensteinian/KR3", name='kr3', split='train')
-kr3 = kr3.remove_columns(['__index_level_0__']) # Original file didn't include this column. Suspect it's a hugging face issue.
-```
-
 ### ⚠️ Caution with `Rating` Column
 0 stands for negative review, 1 stands for positive review, and 2 stands for ambiguous review.  
 **Note that rating 2 is not intended to be used directly for supervised learning(classification).** This data is included for additional pre-training purpose or other usage.  
@@ -40,6 +32,19 @@ In other words, this dataset is basically a **binary** sentiment classification
 See all the codes for crawling/preprocessing the dataset and experiments with KR3 in [Gitlab Repo](https://gitlab.com/Wittgensteinian/kr3).  
 See Kaggle dataset in [Kaggle Dataset](https://www.kaggle.com/ninetyninenewton/kr3-korean-restaurant-reviews-with-ratings).
 
+### Usage
+```python
+from datasets import load_dataset
+
+kr3 = load_dataset("Wittgensteinian/KR3", name='kr3', split='train')
+kr3 = kr3.remove_columns(['__index_level_0__']) # Original file didn't include this column. Suspect it's a hugging face issue.
+```
+```python
+# drop reviews with ambiguous label
+kr3_binary = kr3.filter(lambda example: example['Rating'] != 2)
+```
+
+
 ### License
 **CC BY-NC-SA 4.0**