docs : docstrings examples - dtypes

[anopsy]

Just a quick check: considering I'll have to use cast to get some of the datatypes, maybe I should wrap the from_native into a func after all?

What type of PR is this? (check all applicable)

• 💾 Refactor
• ✨ Feature
• 🐛 Bug Fix
• 🔧 Optimization
• 📝 Documentation
• ✅ Test
• 🐳 Other

Related issues

• Related issue docs: add docstring examples for dtypes #1077
• Closes #

Checklist

• Code follows style guide (ruff)
• Tests added
• Documented the changes

If you have comments or can explain your changes, please do so below.

[MarcoGorelli]

thanks @anopsy !

for Categorical, it looks like casting from string is unsupported in old pyarrow versions* - but you can create the categorical directly:

>>> ca = pa.chunked_array(pa.array(['a', 'b'], type=pa.dictionary(pa.uint32(), pa.string())))
>>> nw.from_native(ca, series_only=True)
┌─────────────────────────────────────────┐
| Narwhals Series                         |
| Use `.to_native()` to see native output |
└─────────────────────────────────────────┘
>>> nw.from_native(ca, series_only=True).dtype
Categorical

For Struct / List / Array, there is a way to do that in pandas too use pd.ArrowDtype:

In [11]: pd.Series(data, dtype=pd.ArrowDtype(pa.large_list(pa.large_string())))
Out[11]:
0      ['narwhal' 'orca']
1    ['beluga' 'vaquita']
dtype: large_list<item: large_string>[pyarrow]

Similarly, for the struct example, I think you could use

pa.struct({'a': pa.int64(), 'b': pa.large_list(pa.large_string())})

---

*maybe we should only run doctests on the latest versions...that would save us a lot of # doctest: +SKIPs which would be a good thing