alex-d-jensen opened a new issue, #45640:
URL: https://github.com/apache/arrow/issues/45640
### Describe the bug, including details regarding any error messages,
version, and platform.
## Sample code to demonstrate:
```python
import pandas as pd
import pyarrow as pa
pandas_dataframe = pd.DataFrame(
{
"x_simple_col": [123],
"struct_col": [
{
"col9": "a_string",
"col1": True,
"a_nested_struct": {
"field": 1,
'a_field': 2
},
"b_array": ["cheese"],
},
],
}
)
pyarrow_schema = pa.schema(
fields=[
pa.field("x_simple_col", pa.int64()),
pa.field(
name="struct_col",
type=pa.struct(
fields=[
pa.field(name="col9", type=pa.string()),
pa.field(name="col1", type=pa.bool_()),
pa.field(
name="a_nested_struct",
type=pa.struct(
fields=[
pa.field(name="field", type=pa.int64()),
pa.field(name="a_field", type=pa.int64()),
]
),
),
pa.field(name="b_array",
type=pa.list_(value_type=pa.string())),
]
),
),
]
)
inferred_schema = pa.Schema.from_pandas(pandas_dataframe)
assert pyarrow_schema == inferred_schema
pyarrow_schema
inferred_schema
```
Gives output:
```
>>> assert pyarrow_schema == inferred_schema
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AssertionError
>>>
>>> pyarrow_schema
x_simple_col: int64
struct_col: struct<col9: string, col1: bool, a_nested_struct: struct<field:
int64, a_field: int64>, b_array: list<item: string>>
child 0, col9: string
child 1, col1: bool
child 2, a_nested_struct: struct<field: int64, a_field: int64>
child 0, field: int64
child 1, a_field: int64
child 3, b_array: list<item: string>
child 0, item: string
>>> inferred_schema
x_simple_col: int64
struct_col: struct<a_nested_struct: struct<a_field: int64, field: int64>,
b_array: list<item: string>, col1: bool, col9: string>
child 0, a_nested_struct: struct<a_field: int64, field: int64>
child 0, a_field: int64
child 1, field: int64
child 1, b_array: list<item: string>
child 0, item: string
child 2, col1: bool
child 3, col9: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' +
499
```
## Expected result:
inferred_schema and pyarrow_schema should match, including struct fields
order (given that documentation for structs mentions that fields are ordered
and that order matters when comparing schemas).
## Actual result:
Schema for structs (including nested structs/fields in structs inside
structs etc) has fields in alphabetical order, rather than in the order found
the data which the schema is inferred from via `from_pandas`.
Regular columns stay in given order - this only affects fields in structs.
## System info:
output from sw_vers:
ProductName: macOS
ProductVersion: 15.3.1
BuildVersion: 24D70
pyarrow version: 18.1.0 (also tried on 19.0.1).
pandas version: 2.2.3
### Component(s)
Python
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