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csverve

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Documentation Status

Csverve, pronounced like "swerve" with a "v", is a package for manipulating tabular data.

Features

  • Take in a regular gzipped CSV file and convert it to csverve format
  • Merge gzipped CSZ files
  • Concatenate gzipped CSV files (handles large datasets)
  • Rewrite a gzipped CSV file (delete headers etc.)
  • Annotate - add a column based on provided dictionary
  • Write pandas DataFrame to csverve CSV
  • Read a csverve CSV

Requirements

Every gzipped CSV file must be accompanied by a meta YAML file. The meta yaml file must have the exact name as the gzipped CSV file, with the addition of a .yaml ending.

csv.gz.yaml must contain:

  • column names
  • dtypes for each column
  • separator
  • header (bool) to specify if file has header or not

Example:

columns:
 - dtype: int
   name: prediction_id
 - dtype: str
   name: chromosome_1
 - dtype: str
   name: strand_1
 header: true
 sep: "\t"

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

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