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        "description": "# Intake-parquet\n\n[![Build Status](https://travis-ci.org/ContinuumIO/intake-parquet.svg?branch=master)](https://travis-ci.org/ContinuumIO/intake-parquet)\n[![Documentation Status](https://readthedocs.org/projects/intake-parquet/badge/?version=latest)](http://intake-parquet.readthedocs.io/en/latest/?badge=latest)\n\n[Intake data loader](https://github.com/ContinuumIO/intake/) interface to the parquet binary tabular data format.\n\nParquet is very popular in the big-data ecosystem, because it provides columnar\nand chunk-wise access to the data, with efficient encodings and compression. This makes\nthe format particularly effective for streaming through large subsections of even\nlarger data-sets, hence it's common use with Hadoop and Spark.\n\nParquet data may be single files, directories of files, or nested directories, where\nthe directory names are meaningful in the partitioning of the data.\n\n### Features\n\nThe parquet plugin allows for:\n\n- efficient metadata parsing, so you know the data types and number of records without\n  loading any data\n- random access of partitions\n- column and index selection, load only the data you need\n- passing of value-based filters, that you only load those partitions containing some\n  valid data (NB: does not filter the values within a partition)\n\n### Installation\n\nThe conda install instructions are:\n\n```\nconda install -c conda-forge intake-parquet\n```\n\n### Examples\n\nSee the notebook in the examples/ directory.",
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