jorisvandenbossche commented on code in PR #48969:
URL: https://github.com/apache/arrow/pull/48969#discussion_r2750001373
##########
python/pyarrow/table.pxi:
##########
@@ -1877,10 +1877,12 @@ cdef class _Tabular(_PandasConvertible):
>>> df = pd.DataFrame({'year': [None, 2022, 2019, 2021],
... 'n_legs': [2, 4, 5, 100],
... 'animals': ["Flamingo", "Horse", None,
"Centipede"]})
- >>> table = pa.Table.from_pandas(df)
+ >>> table = pa.Table.from_arrays(
+ ... [[None, 2022, 2019, 2021], [2, 4, 5, 100], ["Flamingo",
"Horse", None, "Centipede"]],
+ ... names=['year', 'n_legs', 'animals'])
Review Comment:
Not too important, but for future changes: if we want to keep the docstring
examples as simple as possible, I would say that keeping the dict-type creation
(as it is with pd.DataFrame) is easier than the arrays. So this could also be
something like:
```python
>>> table = pa.table({'year': [None, 2022, 2019, 2021],
... 'n_legs': [2, 4, 5, 100],
... 'animals': ["Flamingo", "Horse", None,
"Centipede"]})
```
i.e. essentially just swapping `pd.DataFrame(..)` with `pa.table(..)`
(also, the `df` creation can now be removed from the example, because it is
no longer used)
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