Update README.md

README.md

@@ -12,6 +12,8 @@ size_categories:
 # Overview
 This dataset provides a convenient and user-friendly format of data from [Aozora Bunko (青空文庫)](https://www.aozora.gr.jp/), a website that compiles public-domain books in Japan, ideal for Machine Learning applications.
 
+[For Japanese] 日本語での概要説明を Qiita に記載しました: https://qiita.com/akeyhero/items/b53eae1c0bc4d54e321f
+
 # Methodology
 
 The code to reproduce this dataset is made available on GitHub: [globis-org/aozorabunko-exctractor](https://github.com/globis-org/aozorabunko-extractor).
@@ -41,5 +43,41 @@ The data in the `text` field was then cleaned in the following sequence:
 
 If you prefer to employ only modern Japanese, you can filter entries with: `row["meta"]["文字遣い種別"] == "新字新仮名"`.
 
+# Example
+
+```py
+>>> from datasets import load_dataset
+>>> ds = load_dataset('globis-university/aozorabunko-clean')
+>>> ds
+DatasetDict({
+    train: Dataset({
+        features: ['text', 'footnote', 'meta'],
+        num_rows: 16951
+    })
+})
+>>> ds = ds.filter(lambda row: row['meta']['文字遣い種別'] == '新字新仮名')  # only modern Japanese
+>>> ds
+DatasetDict({
+    train: Dataset({
+        features: ['text', 'footnote', 'meta'],
+        num_rows: 10246
+    })
+})
+>>> book = ds['train'][0]  # one of works
+>>> book['meta']['作品名']
+'ウェストミンスター寺院'
+>>> text = book['text']  # main content
+>>> len(text)
+10639
+>>> print(text[:100])
+深いおどろきにうたれて、
+名高いウェストミンスターに
+真鍮や石の記念碑となって
+すべての王侯貴族が集まっているのをみれば、
+今はさげすみも、ほこりも、見栄もない。
+善にかえった貴人の姿、
+華美と俗世の
+```
+
 # License
 CC BY 4.0