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Nine DataFrame Fixtures
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Classroom Contents
Employing NumPy's NPY Format for Faster Than Parquet DataFrame Storage
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- 1 Intro
- 2 The Quest for Complete DataFrame Serialization
- 3 NumPy Enhancement Proposal (NEP) 1
- 4 Promising Performance of NPZ versus Parquet
- 5 Overview
- 6 Components of a DataFrame
- 7 Block-Consolidation Strategies Unconsolidated Blocks
- 8 Block Consolidation & Complexity
- 9 The NPY Format
- 10 Converting Contiguous Bytes to an Array
- 11 NPY & Object Arrays
- 12 NPY Versions
- 13 The NPZ Format
- 14 Encoding a DataFrame as an NPZ
- 15 JSON Metadata
- 16 NPY Performance in Numpy
- 17 Lies, Damned Lles, and Benchmarks
- 18 Nine DataFrame Fixtures
- 19 Memory Maps
- 20 Memory Mapping an Array
- 21 Memory Mapping a DataFrame
- 22 Current State
- 23 Future Work
- 24 Conclusions
