=======
csverve
=======
.. image:: https://img.shields.io/pypi/v/csverve.svg
:target: https://pypi.python.org/pypi/csverve
.. image:: https://img.shields.io/travis/mondrian-scwgs/csverve.svg
:target: https://travis-ci.com/mondrian-scwgs/csverve
.. image:: https://readthedocs.org/projects/csverve/badge/?version=latest
:target: https://csverve.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
Csverve, pronounced like "swerve" with a "v", is a package for manipulating tabular data.
* Free software: MIT license
* Documentation: https://csverve.readthedocs.io.
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:
.. code-block:: yaml
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.
.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
=======
History
=======
0.1.0 (2020-12-16)
------------------
* First release on PyPI.
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