morgen01 / intro-data-capstone-biodiversity Goto Github PK

Your plot looks great, and it includes all the proper titles and axis labels.

Great job! Your variables are aptly named here. Your variable names are descriptive and specific as to what kind of information is being stored.

One suggestion: You could comment this chunk of code with details about what this code is trying to accomplish. What questions are you trying to answer with these lines? This will help you remember your thought process when you revisit your code and it will also help other readers better understand and critique your code.

Your calculations for the predicted weeks for the two national parks are correct. You should show the code that was used to calculate these results, so your work is reproducible and you can backup your results with solid reasoning.

Hi @morgen01 ! In order for your project to be graded, you also need to include your .py code file. Please leave a response here when you have done so or if you are having issues uploading your code file.

Great work! I probably won’t have much to say here because you pretty much nailed it all the way through.

Your Python work was excellent and very readable. You used many of the best practices related to variable naming conventions and proper indentation. Your code accomplished the tasks in the simplest and most straightforward ways, which is a sign of python coding mastery. I would suggest practicing documenting your code so that other readers can easily review your project and understand what you are trying to accomplish. You can do this through comments interspersed in your code and a README.

On your presentation:
You did a great job on explaining the relevant context information needed for this project through your explanation of the different conservation statuses and your explanation of the foot-and-mouth disease in sheep.

You present each slide as a question or certain task and show the code used to find the answer. You may want to consider keeping your presentation and code separate, as typically audience members will not have time to go over your code and analyze it in the midst of your presentation. The code also ends up fighting for space on your slides against your figures and your own comments. It is enough to present the results of your code and your conclusions and have a separate code file that audience members can visit later.

I think the flow of your presentation is great and makes logical sense. There are some slides that could be taken out without any detriment to your overall presentation. For example, it is not necessary to show every single transformation you made to the dataframes. You can instead just talk about the end resulting data frame you used, and your code file will speak to the individual transformation you used. For example, instead of explaining the lambda you used to select for sheep, you can just mention that you used a dataframe that was restricted to sheep species.

Excellent work overall.