jorisvandenbossche commented on code in PR #14080:
URL: https://github.com/apache/arrow/pull/14080#discussion_r970732387
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python/pyarrow/pandas_compat.py:
##########
@@ -541,7 +541,7 @@ def dataframe_to_types(df, preserve_index, columns=None):
if _pandas_api.is_categorical(values):
type_ = pa.array(c, from_pandas=True).type
elif _pandas_api.is_extension_array_dtype(values):
- type_ = pa.array(c.head(0), from_pandas=True).type
+ type_ = pa.array(c[:0], from_pandas=True).type
Review Comment:
So for the case that `c` is a Series and not Index, this [:0] currently is
always positional (so that's fine). But to be sure I was just checking on
pandas main, and this now gives a warning that this will change in the future:
```
In [9]: s = pd.Series([1, 2], index=[1, 2])
In [10]: s[:0]
<ipython-input-10-48e1b387a0b4>:1: FutureWarning: The behavior of
`series[i:j]` with an integer-dtype index is deprecated. In a future version,
this will be treated as *label-based* indexing, consistent with e.g.
`series[i]` lookups. To retain the old behavior, use `series.iloc[i:j]`. To get
the future behavior, use `series.loc[i:j]`.
s[:0]
Out[10]: Series([], dtype: int64)
```
So we should avoid running into this warning.
I am thinking that we could maybe also use `values[:0]` instead?
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