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

• Free software: MIT license
• Documentation: https://csverve.readthedocs.io.

• 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

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.

• 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"

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