AlenkaF commented on issue #37517:
URL: https://github.com/apache/arrow/issues/37517#issuecomment-1704739142
Could you first verify the pyarrow version you are using (check
`pyarrow.__version__`)? Then could you also inspect the columns of the parquet
file, you can use pyarrow for that (`table=pq.read_table('example.parquet')`and
then check the schema of the table object `table.schema`).
I tried couple of examples using map type and none of them error:
```python
>>> import pyarrow as pa
>>> data = [[{'key': 'a', 'value': "1"}, {'key': 'b', 'value': "2"}],
[{'key': 'c', 'value': "3"}]]
>>> map_type = pa.map_(pa.string(), pa.string())
>>> table = pa.table([pa.array(data, type=map_type)],
names=["array_element"])
>>> table.schema
array_element: map<string, string>
child 0, entries: struct<key: string not null, value: string> not null
child 0, key: string not null
child 1, value: string
>>> table.to_pandas()
array_element
0 [(a, 1), (b, 2)]
1 [(c, 3)]
>>> table = pa.table([pa.array(data, type=pa.list_(map_type))],
names=["array_element"])
>>> table.schema
array_element: list<item: map<string, string>>
child 0, item: map<string, string>
child 0, entries: struct<key: string not null, value: string> not null
child 0, key: string not null
child 1, value: string
>>> table.to_pandas()
array_element
0 [[(key, a), (value, 1)], [(key, b), (value, 2)]]
1 [[(key, c), (value, 3)]]
>>> inner = pa.array(data, type=map_type)
>>> array = pa.MapArray.from_arrays([0, 2], ['a', 'b'], inner)
>>> table = pa.table({'array_element': array})
>>> table.schema
array_element: map<string, map<string, string>>
child 0, entries: struct<key: string not null, value: map<string, string>>
not null
child 0, key: string not null
child 1, value: map<string, string>
child 0, entries: struct<key: string not null, value: string> not
null
child 0, key: string not null
child 1, value: string
>>> table.to_pandas()
array_element
0 [(a, [('a', '1'), ('b', '2')]), (b, [('c', '3'...
```
Duplicate of https://github.com/apache/arrow/issues/12396
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