General Guidelines

When writing an issue for a data scientist, it's important to be clear and specific about the problem you are trying to solve or the task you want them to perform. Here are some tips on how to write an effective issue for a data scientist:

1. Provide a one-line overview: Begin by providing a one-line overview of the issue. This should be a brief and clear summary of the problem you are trying to solve or the task you need the engineer to perform.
2. Clearly define the problem: Clearly define the problem you are trying to solve or the task you want the data scientist to perform. Be specific about the desired outcome and any constraints or limitations that must be taken into account.
3. Specify the workspace requirements: Specify any requirements for the workspace, such as the tools, software, and data needed to complete the project. Include any constraints, such as budget or timeline, that the data scientist should consider when creating the workspace.
4. Provide steps for each part of the issue: For each part of the issue, provide clear and specific steps for working on the code. This can include specifying which files to modify, which functions or methods to use, or any other relevant details. Be sure to include any necessary guidance or resources.
5. Provide data and examples: Provide data and examples that the data scientist can use to understand the problem and develop a solution. This can include sample data sets, visualizations, or other relevant information.
6. Specify any requirements: Specify any specific requirements or constraints that the data scientist must consider when working on the issue. This can include deadlines, budget constraints, or other project requirements.
7. Use clear and concise language: Use clear and concise language to describe the issue and any requirements. Avoid using technical jargon or overly complex language that might confuse the data scientist.
8. Describe the desired outcome: Clearly describe the desired outcome of the project and how the workspace will help achieve that outcome. This can help the data scientist understand the importance of the task and focus their efforts on creating a workspace that meets your needs.
9. Provide any necessary guidance or resources: If there are specific guidelines or resources that the data scientist should use when creating the workspace, provide those in the issue. This can help ensure that the workspace is created correctly and efficiently.
10. Be open to collaboration: Be open to collaboration and feedback from the data scientist. Encourage them to ask questions and provide input, and work together to develop the best possible solution.

Overall, when writing an issue for a data scientist, it's important to be clear and specific about the problem or task you are assigning them. By providing context, data, and examples, and by being open to collaboration, you can help the data scientist develop a solution that meets your needs and moves your project forward.