first commit for adding nfl data

[evanmolinelli]

Pull Request Guide

Checklist

Please check the following:

• You have checked the Pull Request guidelines.
• Tests for bug fixes or new features have been added.
• Docs have been added or updated.

Type

What kind of change does this Pull Request introduce?

• feat: New feature implementation.
• fix: Bug fix.
• docs: Documentation changes.
• style: Code style or format changes.
• refactor: Changes that are not features or bug fixes.
• tests: Test additions or corrections.
• chore: Maintenance code changes.
• other

Current behaviour

Describe the current behaviour or provide a link to an issue.

What is the new behavior?

Describe the new behaviour.

Does this Pull Request introduce a breaking change?

• Yes
• No

Other information

Provide any other information.

[georgedouzas]

Hi @evanmolinelli,

The goal is to create a new branch that only contains the NFL data and follows the naming conventions of the dataloaders. This branch will create a Prefect flow and update the data periodically. There I suggest the following:

1. Your nfl-data branch should be empty of commit history.
2. Check the naming conventions of the data columns and try to follow them (otherwise it can not be used directly by the dataloaders).

[evanmolinelli]

@georgedouzas Thanks for the feedback.

1. I'm going to create a new branch 'data-nfl' with an empty commit history.
2. Can you point me to the dataloaders specifically (files, etc.) and would the naming convention be similar to the dicts COLS_MAPPING and SCHEMA in the soccer.py or data columns in the processed/*.csv(s)?

[georgedouzas]

@evanmolinelli

You can check the file soccer.py. The dataloader class validates the column names and expects three different categories:

• Columns with the name convention 'odds__{bookmaker}{betting_market}{target}', for example 'odds__pinnacle_closing__over_2.5__full_time_goals'. Notice the double underscore. These columns contain the odds data of the selected bookmaker, for a specific betting market and target. The target is a subcategory of a betting market. For example instead of full time goals, we could describe half time goals for the same betting market over_2.5.
• Columns with the name 'target__{betting_market}__{target}', for example 'target__home_team__full_time_goals'. These columns contain the target data for a particular betting market and target as explained above.
• Any other column name.