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| <li class="toctree-l3"><a class="reference internal" href="pyarrow.types.is_primitive.html">pyarrow.types.is_primitive</a></li> |
| </ul> |
| </details></li> |
| <li class="toctree-l2 has-children"><a class="reference internal" href="../api/arrays.html">Arrays and Scalars</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.array.html">pyarrow.array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.nulls.html">pyarrow.nulls</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Array.html">pyarrow.Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.BooleanArray.html">pyarrow.BooleanArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.FloatingPointArray.html">pyarrow.FloatingPointArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.IntegerArray.html">pyarrow.IntegerArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Int8Array.html">pyarrow.Int8Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Int16Array.html">pyarrow.Int16Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Int32Array.html">pyarrow.Int32Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Int64Array.html">pyarrow.Int64Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.NullArray.html">pyarrow.NullArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.NumericArray.html">pyarrow.NumericArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.UInt8Array.html">pyarrow.UInt8Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.UInt16Array.html">pyarrow.UInt16Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.UInt32Array.html">pyarrow.UInt32Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.UInt64Array.html">pyarrow.UInt64Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.HalfFloatArray.html">pyarrow.HalfFloatArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.FloatArray.html">pyarrow.FloatArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.DoubleArray.html">pyarrow.DoubleArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.BinaryArray.html">pyarrow.BinaryArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.StringArray.html">pyarrow.StringArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.FixedSizeBinaryArray.html">pyarrow.FixedSizeBinaryArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.LargeBinaryArray.html">pyarrow.LargeBinaryArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.LargeStringArray.html">pyarrow.LargeStringArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.BinaryViewArray.html">pyarrow.BinaryViewArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.StringViewArray.html">pyarrow.StringViewArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Time32Array.html">pyarrow.Time32Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Time64Array.html">pyarrow.Time64Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Date32Array.html">pyarrow.Date32Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Date64Array.html">pyarrow.Date64Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.TimestampArray.html">pyarrow.TimestampArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.DurationArray.html">pyarrow.DurationArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.MonthDayNanoIntervalArray.html">pyarrow.MonthDayNanoIntervalArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Decimal32Array.html">pyarrow.Decimal32Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Decimal64Array.html">pyarrow.Decimal64Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Decimal128Array.html">pyarrow.Decimal128Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Decimal256Array.html">pyarrow.Decimal256Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.DictionaryArray.html">pyarrow.DictionaryArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.ListArray.html">pyarrow.ListArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.FixedSizeListArray.html">pyarrow.FixedSizeListArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.LargeListArray.html">pyarrow.LargeListArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.ListViewArray.html">pyarrow.ListViewArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.LargeListViewArray.html">pyarrow.LargeListViewArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.MapArray.html">pyarrow.MapArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.RunEndEncodedArray.html">pyarrow.RunEndEncodedArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.StructArray.html">pyarrow.StructArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.UnionArray.html">pyarrow.UnionArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.ExtensionArray.html">pyarrow.ExtensionArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.FixedShapeTensorArray.html">pyarrow.FixedShapeTensorArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.OpaqueArray.html">pyarrow.OpaqueArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.JsonArray.html">pyarrow.JsonArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.UuidArray.html">pyarrow.UuidArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Bool8Array.html">pyarrow.Bool8Array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.scalar.html">pyarrow.scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.NA.html">pyarrow.NA</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Scalar.html">pyarrow.Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.BooleanScalar.html">pyarrow.BooleanScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Int8Scalar.html">pyarrow.Int8Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Int16Scalar.html">pyarrow.Int16Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Int32Scalar.html">pyarrow.Int32Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Int64Scalar.html">pyarrow.Int64Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.NullScalar.html">pyarrow.NullScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.UInt8Scalar.html">pyarrow.UInt8Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.UInt16Scalar.html">pyarrow.UInt16Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.UInt32Scalar.html">pyarrow.UInt32Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.UInt64Scalar.html">pyarrow.UInt64Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.HalfFloatScalar.html">pyarrow.HalfFloatScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.FloatScalar.html">pyarrow.FloatScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.DoubleScalar.html">pyarrow.DoubleScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.BinaryScalar.html">pyarrow.BinaryScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.StringScalar.html">pyarrow.StringScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.FixedSizeBinaryScalar.html">pyarrow.FixedSizeBinaryScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.LargeBinaryScalar.html">pyarrow.LargeBinaryScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.LargeStringScalar.html">pyarrow.LargeStringScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.BinaryViewScalar.html">pyarrow.BinaryViewScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.StringViewScalar.html">pyarrow.StringViewScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Time32Scalar.html">pyarrow.Time32Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Time64Scalar.html">pyarrow.Time64Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Date32Scalar.html">pyarrow.Date32Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Date64Scalar.html">pyarrow.Date64Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.TimestampScalar.html">pyarrow.TimestampScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.DurationScalar.html">pyarrow.DurationScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.MonthDayNanoIntervalScalar.html">pyarrow.MonthDayNanoIntervalScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Decimal128Scalar.html">pyarrow.Decimal128Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Decimal256Scalar.html">pyarrow.Decimal256Scalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.DictionaryScalar.html">pyarrow.DictionaryScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.RunEndEncodedScalar.html">pyarrow.RunEndEncodedScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.ListScalar.html">pyarrow.ListScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.FixedSizeListScalar.html">pyarrow.FixedSizeListScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.LargeListScalar.html">pyarrow.LargeListScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.ListViewScalar.html">pyarrow.ListViewScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.LargeListViewScalar.html">pyarrow.LargeListViewScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.MapScalar.html">pyarrow.MapScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.StructScalar.html">pyarrow.StructScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.UnionScalar.html">pyarrow.UnionScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.ExtensionScalar.html">pyarrow.ExtensionScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.FixedShapeTensorScalar.html">pyarrow.FixedShapeTensorScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.OpaqueScalar.html">pyarrow.OpaqueScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.JsonScalar.html">pyarrow.JsonScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.UuidScalar.html">pyarrow.UuidScalar</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Bool8Scalar.html">pyarrow.Bool8Scalar</a></li> |
| </ul> |
| </details></li> |
| <li class="toctree-l2 has-children"><a class="reference internal" href="../api/memory.html">Buffers and Memory</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.allocate_buffer.html">pyarrow.allocate_buffer</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.py_buffer.html">pyarrow.py_buffer</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.foreign_buffer.html">pyarrow.foreign_buffer</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Buffer.html">pyarrow.Buffer</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.ResizableBuffer.html">pyarrow.ResizableBuffer</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Codec.html">pyarrow.Codec</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compress.html">pyarrow.compress</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.decompress.html">pyarrow.decompress</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.MemoryPool.html">pyarrow.MemoryPool</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.default_memory_pool.html">pyarrow.default_memory_pool</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.jemalloc_memory_pool.html">pyarrow.jemalloc_memory_pool</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.mimalloc_memory_pool.html">pyarrow.mimalloc_memory_pool</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.system_memory_pool.html">pyarrow.system_memory_pool</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.jemalloc_set_decay_ms.html">pyarrow.jemalloc_set_decay_ms</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.set_memory_pool.html">pyarrow.set_memory_pool</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.log_memory_allocations.html">pyarrow.log_memory_allocations</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.total_allocated_bytes.html">pyarrow.total_allocated_bytes</a></li> |
| </ul> |
| </details></li> |
| <li class="toctree-l2 has-children"><a class="reference internal" href="../api/tables.html">Tables and Tensors</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.chunked_array.html">pyarrow.chunked_array</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.concat_arrays.html">pyarrow.concat_arrays</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.concat_tables.html">pyarrow.concat_tables</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.record_batch.html">pyarrow.record_batch</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.concat_batches.html">pyarrow.concat_batches</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.table.html">pyarrow.table</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.ChunkedArray.html">pyarrow.ChunkedArray</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.RecordBatch.html">pyarrow.RecordBatch</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Table.html">pyarrow.Table</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.TableGroupBy.html">pyarrow.TableGroupBy</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.RecordBatchReader.html">pyarrow.RecordBatchReader</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.interchange.from_dataframe.html">pyarrow.interchange.from_dataframe</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.Tensor.html">pyarrow.Tensor</a></li> |
| </ul> |
| </details></li> |
| <li class="toctree-l2 has-children"><a class="reference internal" href="../api/compute.html">Compute Functions</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.all.html">pyarrow.compute.all</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.any.html">pyarrow.compute.any</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.approximate_median.html">pyarrow.compute.approximate_median</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.count.html">pyarrow.compute.count</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.count_distinct.html">pyarrow.compute.count_distinct</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.index.html">pyarrow.compute.index</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.max.html">pyarrow.compute.max</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.mean.html">pyarrow.compute.mean</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.min.html">pyarrow.compute.min</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.min_max.html">pyarrow.compute.min_max</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.mode.html">pyarrow.compute.mode</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.pivot_wider.html">pyarrow.compute.pivot_wider</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.product.html">pyarrow.compute.product</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.quantile.html">pyarrow.compute.quantile</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.stddev.html">pyarrow.compute.stddev</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.sum.html">pyarrow.compute.sum</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.tdigest.html">pyarrow.compute.tdigest</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.variance.html">pyarrow.compute.variance</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.cumulative_sum.html">pyarrow.compute.cumulative_sum</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.cumulative_sum_checked.html">pyarrow.compute.cumulative_sum_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.cumulative_prod.html">pyarrow.compute.cumulative_prod</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.cumulative_prod_checked.html">pyarrow.compute.cumulative_prod_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.cumulative_max.html">pyarrow.compute.cumulative_max</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.cumulative_min.html">pyarrow.compute.cumulative_min</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.abs.html">pyarrow.compute.abs</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.abs_checked.html">pyarrow.compute.abs_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.add.html">pyarrow.compute.add</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.add_checked.html">pyarrow.compute.add_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.divide.html">pyarrow.compute.divide</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.divide_checked.html">pyarrow.compute.divide_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.multiply.html">pyarrow.compute.multiply</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.multiply_checked.html">pyarrow.compute.multiply_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.negate.html">pyarrow.compute.negate</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.negate_checked.html">pyarrow.compute.negate_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.power.html">pyarrow.compute.power</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.power_checked.html">pyarrow.compute.power_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.sign.html">pyarrow.compute.sign</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.sqrt.html">pyarrow.compute.sqrt</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.sqrt_checked.html">pyarrow.compute.sqrt_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.subtract.html">pyarrow.compute.subtract</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.subtract_checked.html">pyarrow.compute.subtract_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.compute.bit_wise_and.html">pyarrow.compute.bit_wise_and</a></li> |
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| <li class="toctree-l2 has-children"><a class="reference internal" href="../api/acero.html">Acero - Streaming Execution Engine</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
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| <li class="toctree-l2 has-children"><a class="reference internal" href="../api/substrait.html">Substrait</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
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| <li class="toctree-l2 has-children"><a class="reference internal" href="../api/files.html">Streams and File Access</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
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| <li class="toctree-l3"><a class="reference internal" href="pyarrow.PythonFile.html">pyarrow.PythonFile</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="pyarrow.BufferOutputStream.html">pyarrow.BufferOutputStream</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.FixedSizeBufferWriter.html">pyarrow.FixedSizeBufferWriter</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="pyarrow.CompressedOutputStream.html">pyarrow.CompressedOutputStream</a></li> |
| </ul> |
| </details></li> |
| <li class="toctree-l2 has-children"><a class="reference internal" href="../api/ipc.html">Serialization and IPC</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
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| <li class="toctree-l3"><a class="reference internal" href="pyarrow.ipc.open_stream.html">pyarrow.ipc.open_stream</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.ipc.read_message.html">pyarrow.ipc.read_message</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.ipc.read_record_batch.html">pyarrow.ipc.read_record_batch</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="pyarrow.ipc.MessageReader.html">pyarrow.ipc.MessageReader</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.ipc.RecordBatchFileReader.html">pyarrow.ipc.RecordBatchFileReader</a></li> |
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| </details></li> |
| <li class="toctree-l2 has-children"><a class="reference internal" href="../api/flight.html">Arrow Flight</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
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| <li class="toctree-l3"><a class="reference internal" href="pyarrow.flight.FlightInfo.html">pyarrow.flight.FlightInfo</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.flight.Location.html">pyarrow.flight.Location</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="pyarrow.flight.MetadataRecordBatchWriter.html">pyarrow.flight.MetadataRecordBatchWriter</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="pyarrow.flight.Ticket.html">pyarrow.flight.Ticket</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="pyarrow.flight.FlightClient.html">pyarrow.flight.FlightClient</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="pyarrow.flight.FlightStreamWriter.html">pyarrow.flight.FlightStreamWriter</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="pyarrow.flight.GeneratorStream.html">pyarrow.flight.GeneratorStream</a></li> |
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| <dl class="py function"> |
| <dt class="sig sig-object py" id="pyarrow.dataset.dataset"> |
| <span class="sig-prename descclassname"><span class="pre">pyarrow.dataset.</span></span><span class="sig-name descname"><span class="pre">dataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">source</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">schema</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">format</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filesystem</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">partitioning</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">partition_base_dir</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exclude_invalid_files</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ignore_prefixes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/dataset.html#dataset"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyarrow.dataset.dataset" title="Permalink to this definition">#</a></dt> |
| <dd><p>Open a dataset.</p> |
| <p>Datasets provides functionality to efficiently work with tabular, |
| potentially larger than memory and multi-file dataset.</p> |
| <ul class="simple"> |
| <li><p>A unified interface for different sources, like Parquet and Feather</p></li> |
| <li><p>Discovery of sources (crawling directories, handle directory-based |
| partitioned datasets, basic schema normalization)</p></li> |
| <li><p>Optimized reading with predicate pushdown (filtering rows), projection |
| (selecting columns), parallel reading or fine-grained managing of tasks.</p></li> |
| </ul> |
| <p>Note that this is the high-level API, to have more control over the dataset |
| construction use the low-level API classes (FileSystemDataset, |
| FilesystemDatasetFactory, etc.)</p> |
| <dl class="field-list"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>source</strong><span class="classifier">path, <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a> of paths, dataset, <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a> of datasets, (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a> of) <a class="reference internal" href="pyarrow.RecordBatch.html#pyarrow.RecordBatch" title="pyarrow.RecordBatch"><code class="xref py py-obj docutils literal notranslate"><span class="pre">RecordBatch</span></code></a> or <a class="reference internal" href="pyarrow.Table.html#pyarrow.Table" title="pyarrow.Table"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Table</span></code></a>, <a class="reference external" href="https://docs.python.org/3/glossary.html#term-iterable" title="(in Python v3.13)"><span>iterable</span></a> of <a class="reference internal" href="pyarrow.RecordBatch.html#pyarrow.RecordBatch" title="pyarrow.RecordBatch"><code class="xref py py-obj docutils literal notranslate"><span class="pre">RecordBatch</span></code></a>, RecordBatchReader, or URI</span></dt><dd><dl class="simple"> |
| <dt>Path pointing to a single file:</dt><dd><p>Open a FileSystemDataset from a single file.</p> |
| </dd> |
| <dt>Path pointing to a directory:</dt><dd><p>The directory gets discovered recursively according to a |
| partitioning scheme if given.</p> |
| </dd> |
| <dt>List of file paths:</dt><dd><p>Create a FileSystemDataset from explicitly given files. The files |
| must be located on the same filesystem given by the filesystem |
| parameter. |
| Note that in contrary of construction from a single file, passing |
| URIs as paths is not allowed.</p> |
| </dd> |
| <dt>List of datasets:</dt><dd><p>A nested UnionDataset gets constructed, it allows arbitrary |
| composition of other datasets. |
| Note that additional keyword arguments are not allowed.</p> |
| </dd> |
| <dt>(List of) batches or tables, iterable of batches, or RecordBatchReader:</dt><dd><p>Create an InMemoryDataset. If an iterable or empty list is given, |
| a schema must also be given. If an iterable or RecordBatchReader |
| is given, the resulting dataset can only be scanned once; further |
| attempts will raise an error.</p> |
| </dd> |
| </dl> |
| </dd> |
| <dt><strong>schema</strong><span class="classifier"><a class="reference internal" href="pyarrow.Schema.html#pyarrow.Schema" title="pyarrow.Schema"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Schema</span></code></a>, optional</span></dt><dd><p>Optionally provide the Schema for the Dataset, in which case it will |
| not be inferred from the source.</p> |
| </dd> |
| <dt><strong>format</strong><span class="classifier"><a class="reference internal" href="pyarrow.dataset.FileFormat.html#pyarrow.dataset.FileFormat" title="pyarrow.dataset.FileFormat"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FileFormat</span></code></a> or <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a></span></dt><dd><p>Currently “parquet”, “ipc”/”arrow”/”feather”, “csv”, “json”, and “orc” are |
| supported. For Feather, only version 2 files are supported.</p> |
| </dd> |
| <dt><strong>filesystem</strong><span class="classifier"><a class="reference internal" href="pyarrow.fs.FileSystem.html#pyarrow.fs.FileSystem" title="pyarrow.fs.FileSystem"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FileSystem</span></code></a> or URI <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>If a single path is given as source and filesystem is None, then the |
| filesystem will be inferred from the path. |
| If an URI string is passed, then a filesystem object is constructed |
| using the URI’s optional path component as a directory prefix. See the |
| examples below. |
| Note that the URIs on Windows must follow ‘<a class="reference external" href="file:///C">file:///C</a>:…’ or |
| ‘<a class="reference external" href="file:/C">file:/C</a>:…’ patterns.</p> |
| </dd> |
| <dt><strong>partitioning</strong><span class="classifier"><a class="reference internal" href="pyarrow.dataset.Partitioning.html#pyarrow.dataset.Partitioning" title="pyarrow.dataset.Partitioning"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Partitioning</span></code></a>, <a class="reference internal" href="pyarrow.dataset.PartitioningFactory.html#pyarrow.dataset.PartitioningFactory" title="pyarrow.dataset.PartitioningFactory"><code class="xref py py-obj docutils literal notranslate"><span class="pre">PartitioningFactory</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a> of <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a></span></dt><dd><p>The partitioning scheme specified with the <code class="docutils literal notranslate"><span class="pre">partitioning()</span></code> |
| function. A flavor string can be used as shortcut, and with a list of |
| field names a DirectoryPartitioning will be inferred.</p> |
| </dd> |
| <dt><strong>partition_base_dir</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a>, optional</span></dt><dd><p>For the purposes of applying the partitioning, paths will be |
| stripped of the partition_base_dir. Files not matching the |
| partition_base_dir prefix will be skipped for partitioning discovery. |
| The ignored files will still be part of the Dataset, but will not |
| have partition information.</p> |
| </dd> |
| <dt><strong>exclude_invalid_files</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a>, optional (default <a class="reference external" href="https://docs.python.org/3/library/constants.html#True" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">True</span></code></a>)</span></dt><dd><p>If True, invalid files will be excluded (file format specific check). |
| This will incur IO for each files in a serial and single threaded |
| fashion. Disabling this feature will skip the IO, but unsupported |
| files may be present in the Dataset (resulting in an error at scan |
| time).</p> |
| </dd> |
| <dt><strong>ignore_prefixes</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a>, optional</span></dt><dd><p>Files matching any of these prefixes will be ignored by the |
| discovery process. This is matched to the basename of a path. |
| By default this is [‘.’, ‘_’]. |
| Note that discovery happens only if a directory is passed as source.</p> |
| </dd> |
| </dl> |
| </dd> |
| <dt class="field-even">Returns<span class="colon">:</span></dt> |
| <dd class="field-even"><dl> |
| <dt><strong>dataset</strong><span class="classifier"><a class="reference internal" href="pyarrow.dataset.Dataset.html#pyarrow.dataset.Dataset" title="pyarrow.dataset.Dataset"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Dataset</span></code></a></span></dt><dd><p>Either a FileSystemDataset or a UnionDataset depending on the source |
| parameter.</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <p class="rubric">Examples</p> |
| <p>Creating an example Table:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span><span class="w"> </span><span class="nn">pyarrow</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">pa</span> |
| <span class="gp">>>> </span><span class="kn">import</span><span class="w"> </span><span class="nn">pyarrow.parquet</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">pq</span> |
| <span class="gp">>>> </span><span class="n">table</span> <span class="o">=</span> <span class="n">pa</span><span class="o">.</span><span class="n">table</span><span class="p">({</span><span class="s1">'year'</span><span class="p">:</span> <span class="p">[</span><span class="mi">2020</span><span class="p">,</span> <span class="mi">2022</span><span class="p">,</span> <span class="mi">2021</span><span class="p">,</span> <span class="mi">2022</span><span class="p">,</span> <span class="mi">2019</span><span class="p">,</span> <span class="mi">2021</span><span class="p">],</span> |
| <span class="gp">... </span> <span class="s1">'n_legs'</span><span class="p">:</span> <span class="p">[</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">100</span><span class="p">],</span> |
| <span class="gp">... </span> <span class="s1">'animal'</span><span class="p">:</span> <span class="p">[</span><span class="s2">"Flamingo"</span><span class="p">,</span> <span class="s2">"Parrot"</span><span class="p">,</span> <span class="s2">"Dog"</span><span class="p">,</span> <span class="s2">"Horse"</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="s2">"Brittle stars"</span><span class="p">,</span> <span class="s2">"Centipede"</span><span class="p">]})</span> |
| <span class="gp">>>> </span><span class="n">pq</span><span class="o">.</span><span class="n">write_table</span><span class="p">(</span><span class="n">table</span><span class="p">,</span> <span class="s2">"file.parquet"</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Opening a single file:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span><span class="w"> </span><span class="nn">pyarrow.dataset</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">ds</span> |
| <span class="gp">>>> </span><span class="n">dataset</span> <span class="o">=</span> <span class="n">ds</span><span class="o">.</span><span class="n">dataset</span><span class="p">(</span><span class="s2">"file.parquet"</span><span class="p">,</span> <span class="nb">format</span><span class="o">=</span><span class="s2">"parquet"</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">dataset</span><span class="o">.</span><span class="n">to_table</span><span class="p">()</span> |
| <span class="go">pyarrow.Table</span> |
| <span class="go">year: int64</span> |
| <span class="go">n_legs: int64</span> |
| <span class="go">animal: string</span> |
| <span class="go">----</span> |
| <span class="go">year: [[2020,2022,2021,2022,2019,2021]]</span> |
| <span class="go">n_legs: [[2,2,4,4,5,100]]</span> |
| <span class="go">animal: [["Flamingo","Parrot","Dog","Horse","Brittle stars","Centipede"]]</span> |
| </pre></div> |
| </div> |
| <p>Opening a single file with an explicit schema:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">myschema</span> <span class="o">=</span> <span class="n">pa</span><span class="o">.</span><span class="n">schema</span><span class="p">([</span> |
| <span class="gp">... </span> <span class="p">(</span><span class="s1">'n_legs'</span><span class="p">,</span> <span class="n">pa</span><span class="o">.</span><span class="n">int64</span><span class="p">()),</span> |
| <span class="gp">... </span> <span class="p">(</span><span class="s1">'animal'</span><span class="p">,</span> <span class="n">pa</span><span class="o">.</span><span class="n">string</span><span class="p">())])</span> |
| <span class="gp">>>> </span><span class="n">dataset</span> <span class="o">=</span> <span class="n">ds</span><span class="o">.</span><span class="n">dataset</span><span class="p">(</span><span class="s2">"file.parquet"</span><span class="p">,</span> <span class="n">schema</span><span class="o">=</span><span class="n">myschema</span><span class="p">,</span> <span class="nb">format</span><span class="o">=</span><span class="s2">"parquet"</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">dataset</span><span class="o">.</span><span class="n">to_table</span><span class="p">()</span> |
| <span class="go">pyarrow.Table</span> |
| <span class="go">n_legs: int64</span> |
| <span class="go">animal: string</span> |
| <span class="go">----</span> |
| <span class="go">n_legs: [[2,2,4,4,5,100]]</span> |
| <span class="go">animal: [["Flamingo","Parrot","Dog","Horse","Brittle stars","Centipede"]]</span> |
| </pre></div> |
| </div> |
| <p>Opening a dataset for a single directory:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">ds</span><span class="o">.</span><span class="n">write_dataset</span><span class="p">(</span><span class="n">table</span><span class="p">,</span> <span class="s2">"partitioned_dataset"</span><span class="p">,</span> <span class="nb">format</span><span class="o">=</span><span class="s2">"parquet"</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="n">partitioning</span><span class="o">=</span><span class="p">[</span><span class="s1">'year'</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">dataset</span> <span class="o">=</span> <span class="n">ds</span><span class="o">.</span><span class="n">dataset</span><span class="p">(</span><span class="s2">"partitioned_dataset"</span><span class="p">,</span> <span class="nb">format</span><span class="o">=</span><span class="s2">"parquet"</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">dataset</span><span class="o">.</span><span class="n">to_table</span><span class="p">()</span> |
| <span class="go">pyarrow.Table</span> |
| <span class="go">n_legs: int64</span> |
| <span class="go">animal: string</span> |
| <span class="go">----</span> |
| <span class="go">n_legs: [[5],[2],[4,100],[2,4]]</span> |
| <span class="go">animal: [["Brittle stars"],["Flamingo"],...["Parrot","Horse"]]</span> |
| </pre></div> |
| </div> |
| <p>For a single directory from a S3 bucket:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">ds</span><span class="o">.</span><span class="n">dataset</span><span class="p">(</span><span class="s2">"s3://mybucket/nyc-taxi/"</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="nb">format</span><span class="o">=</span><span class="s2">"parquet"</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Opening a dataset from a list of relatives local paths:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">dataset</span> <span class="o">=</span> <span class="n">ds</span><span class="o">.</span><span class="n">dataset</span><span class="p">([</span> |
| <span class="gp">... </span> <span class="s2">"partitioned_dataset/2019/part-0.parquet"</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="s2">"partitioned_dataset/2020/part-0.parquet"</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="s2">"partitioned_dataset/2021/part-0.parquet"</span><span class="p">,</span> |
| <span class="gp">... </span><span class="p">],</span> <span class="nb">format</span><span class="o">=</span><span class="s1">'parquet'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">dataset</span><span class="o">.</span><span class="n">to_table</span><span class="p">()</span> |
| <span class="go">pyarrow.Table</span> |
| <span class="go">n_legs: int64</span> |
| <span class="go">animal: string</span> |
| <span class="go">----</span> |
| <span class="go">n_legs: [[5],[2],[4,100]]</span> |
| <span class="go">animal: [["Brittle stars"],["Flamingo"],["Dog","Centipede"]]</span> |
| </pre></div> |
| </div> |
| <p>With filesystem provided:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">paths</span> <span class="o">=</span> <span class="p">[</span> |
| <span class="gp">... </span> <span class="s1">'part0/data.parquet'</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="s1">'part1/data.parquet'</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="s1">'part3/data.parquet'</span><span class="p">,</span> |
| <span class="gp">... </span><span class="p">]</span> |
| <span class="gp">>>> </span><span class="n">ds</span><span class="o">.</span><span class="n">dataset</span><span class="p">(</span><span class="n">paths</span><span class="p">,</span> <span class="n">filesystem</span><span class="o">=</span><span class="s1">'file:///directory/prefix,</span> |
| <span class="gp">... </span> <span class="nb">format</span><span class="o">=</span><span class="s1">'parquet'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Which is equivalent with:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">fs</span> <span class="o">=</span> <span class="n">SubTreeFileSystem</span><span class="p">(</span><span class="s2">"/directory/prefix"</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="n">LocalFileSystem</span><span class="p">())</span> |
| <span class="gp">>>> </span><span class="n">ds</span><span class="o">.</span><span class="n">dataset</span><span class="p">(</span><span class="n">paths</span><span class="p">,</span> <span class="n">filesystem</span><span class="o">=</span><span class="n">fs</span><span class="p">,</span> <span class="nb">format</span><span class="o">=</span><span class="s1">'parquet'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>With a remote filesystem URI:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">paths</span> <span class="o">=</span> <span class="p">[</span> |
| <span class="gp">... </span> <span class="s1">'nested/directory/part0/data.parquet'</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="s1">'nested/directory/part1/data.parquet'</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="s1">'nested/directory/part3/data.parquet'</span><span class="p">,</span> |
| <span class="gp">... </span><span class="p">]</span> |
| <span class="gp">>>> </span><span class="n">ds</span><span class="o">.</span><span class="n">dataset</span><span class="p">(</span><span class="n">paths</span><span class="p">,</span> <span class="n">filesystem</span><span class="o">=</span><span class="s1">'s3://bucket/'</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="nb">format</span><span class="o">=</span><span class="s1">'parquet'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Similarly to the local example, the directory prefix may be included in the |
| filesystem URI:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">ds</span><span class="o">.</span><span class="n">dataset</span><span class="p">(</span><span class="n">paths</span><span class="p">,</span> <span class="n">filesystem</span><span class="o">=</span><span class="s1">'s3://bucket/nested/directory'</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="nb">format</span><span class="o">=</span><span class="s1">'parquet'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Construction of a nested dataset:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">ds</span><span class="o">.</span><span class="n">dataset</span><span class="p">([</span> |
| <span class="gp">... </span> <span class="n">dataset</span><span class="p">(</span><span class="s2">"s3://old-taxi-data"</span><span class="p">,</span> <span class="nb">format</span><span class="o">=</span><span class="s2">"parquet"</span><span class="p">),</span> |
| <span class="gp">... </span> <span class="n">dataset</span><span class="p">(</span><span class="s2">"local/path/to/data"</span><span class="p">,</span> <span class="nb">format</span><span class="o">=</span><span class="s2">"ipc"</span><span class="p">)</span> |
| <span class="gp">... </span><span class="p">])</span> |
| </pre></div> |
| </div> |
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