AlenkaF opened a new pull request, #14613:
URL: https://github.com/apache/arrow/pull/14613
### Produce a `__dataframe__` object
- [ ] Implement the `DataFrame`, `Column` and `Buffers` class
- [ ] Test `pa.Table` -> `pd.DataFrame`
What should be added/corrected after the initial test:
- [ ] Data without missing values (produce a validity buffer in case of no
missing values)
- [ ] Boolean values do not transfer correctly (only the first element is
produced)
- [ ] Variable-length strings (the test currently fails due to, what seems,
an error in pandas implementation)
---
This code should work, currently it does for integers and floats with
missing values:
```python
import pyarrow as pa
import pandas as pd
table = pa.table(
{
"a": [1, 2, None], # dtype kind INT = 0
"b": [3, 4, None], # dtype kind INT = 0
"c": [1.5, 2.5, None], # dtype kind FLOAT = 2
"d": [9, 10, None], # dtype kind INT = 0
# "e": [True, False, None], # dtype kind BOOLEAN = 20
# "f": ["a", "", "c"], # dtype kind STRING = 21
}
)
exchange_df = table.__dataframe__()
exchange_df._df
# pyarrow.Table
# a: int64
# b: int64
# c: double
# d: int64
# ----
# a: [[1,2,null]]
# b: [[3,4,null]]
# c: [[1.5,2.5,null]]
# d: [[9,10,null]]
from pandas.core.interchange.from_dataframe import from_dataframe
from_dataframe(exchange_df)
# a b c d
# 0 1 3 1.5 9
# 1 2 4 2.5 10
# 2 0 0 0.0 0
```
---
### Consume a `__dataframe__` object
- [ ] Implement `from_dataframe` method
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