06_sharing_results_21_final_project.Rmd

```{r, include = FALSE}
ottrpal::set_knitr_image_path()
```

# GitHub and Final Data Project

In this project, we are going to have you form your own question and find data to explore it.

But, we will also want to practice using version control and getting our projects to be open source and available on GitHub.

### Starting up this project

1. Follow the `Creating A Repository` steps and subsequent chapters to create a new GitHub repository for this project.
2. Follow the instructions in `Cloning A Repository` chapter to also clone this project to your RStudio workspace
3. Work on formulating your data science question -- try to pick a topic you are interested in! You can gain inspiration by browsing some of the open source dataset websites we have discussed in the `Finding Data` chapter.
4. When you find a dataset and question combo you are interested in, you can feel free to borrow [this R Markdown template to get you started](https://github.com/datatrail-jhu/DataTrail_Projects/blob/main/06_Sharing_Results/data_project_final.Rmd). You can find this same file in your `DataTrail_Projects` RStudio project.  

### Your objectives!

To complete this project there are a few requirements you will need to fulfill. Remember that you are not on your own for this project! Data science is done best as a community, so please ask others (and instructors) questions you have when you get stuck!

1. Clearly state the data science question and goal for the analysis you are embarking on.
2. This project should be completely uploaded and up to date on GitHub. Follow the steps in `Pushing and Pulling Changes` chapter for how to git add, commit, and push the changes you have done.
3. Follow good organization principles -- you should at least have 2 folders: a `results` folder and a `data` folder. 4. 4. You should also have a README
5. Make a resulting plot that you save to a file.
6. Write up your final observations in regards to your original question. Note that some data science projects end with "This isn't what I thought it would be" or "that's strange" or "I think this is leading into another question I would need to investigate". Whatever your observations may be, write them up in your main R Markdown.
7. When you feel your analysis is ready for review, send your instructor the GitHub link to your project so they can review it.
8. Pat yourself on the back for all this work! You are a data scientist!