Read dataset including pandas metadata, if any. Other arguments passed through to :func:`read`, see docstring for further details. Parameters ---------- **kwargs : optional Additional options for :func:`read` Examples --------
(self, **kwargs)
| 1616 | return metadata |
| 1617 | |
| 1618 | def read_pandas(self, **kwargs): |
| 1619 | """ |
| 1620 | Read dataset including pandas metadata, if any. Other arguments passed |
| 1621 | through to :func:`read`, see docstring for further details. |
| 1622 | |
| 1623 | Parameters |
| 1624 | ---------- |
| 1625 | **kwargs : optional |
| 1626 | Additional options for :func:`read` |
| 1627 | |
| 1628 | Examples |
| 1629 | -------- |
| 1630 | Generate an example parquet file: |
| 1631 | |
| 1632 | >>> import pyarrow as pa |
| 1633 | >>> import pandas as pd |
| 1634 | >>> df = pd.DataFrame({'year': [2020, 2022, 2021, 2022, 2019, 2021], |
| 1635 | ... 'n_legs': [2, 2, 4, 4, 5, 100], |
| 1636 | ... 'animal': ["Flamingo", "Parrot", "Dog", "Horse", |
| 1637 | ... "Brittle stars", "Centipede"]}) |
| 1638 | >>> table = pa.Table.from_pandas(df) |
| 1639 | >>> import pyarrow.parquet as pq |
| 1640 | >>> pq.write_table(table, 'table_V2.parquet') |
| 1641 | >>> dataset = pq.ParquetDataset('table_V2.parquet') |
| 1642 | |
| 1643 | Read the dataset with pandas metadata: |
| 1644 | |
| 1645 | >>> dataset.read_pandas(columns=["n_legs"]) |
| 1646 | pyarrow.Table |
| 1647 | n_legs: int64 |
| 1648 | ---- |
| 1649 | n_legs: [[2,2,4,4,5,100]] |
| 1650 | |
| 1651 | >>> dataset.read_pandas(columns=["n_legs"]).schema.pandas_metadata |
| 1652 | {'index_columns': [{'kind': 'range', 'name': None, 'start': 0, ...} |
| 1653 | """ |
| 1654 | return self.read(use_pandas_metadata=True, **kwargs) |
| 1655 | |
| 1656 | @property |
| 1657 | def fragments(self): |