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https://github.com/dsacms/reverse-scorecard-generation

Combine column-major HHS Zero Trust Scorecard Excel spreadsheets into a row-major CSV file.
https://github.com/dsacms/reverse-scorecard-generation

csv excel python

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Combine column-major HHS Zero Trust Scorecard Excel spreadsheets into a row-major CSV file.

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# Reverse Scorecard Generation

Combine column-major HHS Zero Trust Scorecard Excel spreadsheets into a row-major CSV file.

## About the Project

**Combine column-major HHS Zero Trust Scorecard Excel spreadsheets into a row-major CSV file.**

### Usage Instructions

Steps to use the script:

1. `cd` into the repo folder.
2. Install dependencies: `pip install -r requirements.txt`
3. Put Excel files in the `input_files` folder.
4. Run the script: `python script.py`.
5. The script will generate a `out.csv` file. OR, you can put an existing `out.csv` file in the repo folder and the script will append new roles to the CSV file (it will not overwrite existing rows).

## Core Team

A full list of contributors can be found on [https://github.cms.gov/DSACMS/reverse-scorecard-generation/graphs/contributors](https://github.cms.gov/DSACMS/reverse-scorecard-generation/graphs/contributors).

## Policies

### Open Source Policy

We adhere to the [CMS Open Source
Policy](https://github.com/CMSGov/cms-open-source-policy). If you have any
questions, just [shoot us an email](mailto:[email protected]).

### Security and Responsible Disclosure Policy

*Submit a vulnerability:* Unfortunately, we cannot accept secure submissions via
email or via GitHub Issues. Please use our website to submit vulnerabilities at
[https://hhs.responsibledisclosure.com](https://hhs.responsibledisclosure.com).
HHS maintains an acknowledgements page to recognize your efforts on behalf of
the American public, but you are also welcome to submit anonymously.

For more information about our Security, Vulnerability, and Responsible Disclosure Policies, see [SECURITY.md](SECURITY.md).

## Public domain

This project is in the public domain within the United States, and copyright and related rights in the work worldwide are waived through the [CC0 1.0 Universal public domain dedication](https://creativecommons.org/publicdomain/zero/1.0/) as indicated in [LICENSE](LICENSE).

All contributions to this project will be released under the CC0 dedication. By submitting a pull request or issue, you are agreeing to comply with this waiver of copyright interest.