author 是一个结构体，包含 name 和 country 两个字段。取出作者的国家和姓名，按国家统计：
n_articles：该国家的文章数。n_authors：该国家不同作者姓名的个数，姓名为 null 的不计入。规则：
country 为 null。author 为 null 的文章，视为姓名和国家都是 null（归入 null 国家这一组）。输入
articles(article_id, title, author, tags, published_at, word_count)：author 为 struct<name: string, country: string>输出
列为 country, n_articles, n_authors，行顺序不限。
articles blog/articles
| # | article_idint64 | titlestring | authorstruct<name: string, country: string> | tagslist<string> | published_atdatetime | word_countint64 |
|---|---|---|---|---|---|---|
| 1 | 1 | A gentle intro to DuckDB | {"name": "Hans Muller", "country": "DE"} | ["etl", "Python", "rust"] | 2026-02-07 18:20:00 | 353 |
| 2 | 2 | Testing Python | {"name": "Bob Smith", "country": "US"} | ["SQL"] | 2026-09-02 17:13:00 | 3726 |
| 3 | 3 | 10 tips for dataframes | {"name": "Bob Smith", "country": "US"} | ["pandas"] | 2026-07-23 20:39:00 | 362 |
| 4 | 4 | Debugging DuckDB | {"name": "Amy Chen", "country": "US"} | [] | 2026-01-20 22:03:00 | 3845 |
| 5 | 5 | Debugging window functions | {"name": "Ana Souza", "country": "BR"} | [] | 2026-08-20 10:17:00 | 3899 |
| 6 | 6 | Getting started with Polars | {"name": "王芳", "country": "CN"} | ["polars"] | 2026-05-17 19:28:00 | 2086 |
| 7 | 7 | Testing dataframes | {"name": "Ana Souza", "country": "BR"} | ["rust", "ml", "go"] | 2026-08-01 17:58:00 | 1251 |
| 8 | 8 | Benchmarking pandas | {"name": "王芳", "country": "CN"} | ["Python", "pandas", "ml", "go"] | 2026-02-27 20:10:00 | 2984 |
| 9 | 9 | Benchmarking Python | {"name": "Hans Muller", "country": "DE"} | ["etl"] | 2026-09-09 09:30:00 | 1709 |
| 10 | 10 | 10 tips for dataframes | {"name": "Amy Chen", "country": "US"} | null | 2026-08-11 21:07:00 | 2000 |
| 11 | 11 | Debugging pandas | {"name": "Amy Chen", "country": "US"} | ["python", "viz"] | 2026-06-23 17:24:00 | 3908 |
| 12 | 12 | Getting started with SQL | {"name": "Ana Souza", "country": "BR"} | ["sql"] | 2026-03-01 18:14:00 | 2493 |
| 13 | 13 | Common pitfalls in SQL | {"name": "Li Wei", "country": "CN"} | ["python", "pandas", "python"] | 2026-03-25 19:46:00 | 473 |
| 14 | 14 | A gentle intro to ETL | {"name": "王芳", "country": "CN"} | ["viz", "SQL", "etl", "go"] | 2026-07-21 18:59:00 | 3850 |
| 15 | 15 | Common pitfalls in Python | {"name": "Amy Chen", "country": "US"} | ["SQL", "polars"] | 2026-06-08 15:27:00 | 1357 |
| 16 | 16 | Getting started with ETL | {"name": "Ana Souza", "country": "BR"} | ["rust", "ml", "python"] | 2026-07-16 18:30:00 | 2713 |
| 17 | 17 | A gentle intro to pandas | {"name": "Kenji Sato", "country": "JP"} | ["Python", "ml"] | 2026-05-27 20:35:00 | 2305 |
| 18 | 18 | Getting started with pandas | {"name": "Li Wei", "country": "CN"} | null | 2026-06-17 11:01:00 | 1790 |
| 19 | 19 | A gentle intro to ETL | {"name": "Kenji Sato", "country": "JP"} | ["duckdb", "SQL", "viz"] | 2026-02-27 21:10:00 | 3630 |
| 20 | 20 | Benchmarking DuckDB | {"name": "Li Wei", "country": "CN"} | ["Python", "duckdb"] | 2026-05-07 13:35:00 | 1067 |
| # | countryString | n_articlesInt64 | n_authorsInt64 |
|---|---|---|---|
| 1 | BR | 5 | 1 |
| 2 | JP | 4 | 1 |
| 3 | null | 4 | 1 |
| 4 | DE | 5 | 1 |
| 5 | US | 12 | 2 |
| 6 | CN | 10 | 2 |