I would like to share my notebook of the 6th Guided Project: Employee Exit Surveys .
The focus of the elaborated work was the data cleaning part.
I would especially be keen to get your remarks and opinions on my solution of “Screen 9”,
converting “institute_service” column into the “service_cat”.
Guided_Project_7_Clean_and_Analyze_Employee_Exit_Surveys.ipynb (755.3 KB)
Click here to view the jupyter notebook file in a new tab
Seems like you are on a GP completion spree! Congratulations!
I would combine feedback to both these projects in one go.
Guided Project 6: Data Cleaning - Employee Exit Surveys - Share / Projects - Dataquest Community & Guided-Project 7: Star Wars survey - Share / Projects - Dataquest Community
I have common pointers to share with you:
- First thing that stands out is you searched out related projects and mentioned the work of our peers. More importantly, you highlighted why their research mattered and how to move forward with their work! (Thanks to @kwu as well for that in-depth analysis )
- You put efforts into making your plots stand out and diversify them, with not just titles marked by also axes labels and colour schematics.
However, I would encourage you to add a bit of narrative and story-telling format to your projects. I understand if you find it difficult. The coding part is not easy perhaps but can be learnt and debugged. It’s capturing enough attention from your readers and selling your analysis which is also part of Data Analytics/Science.
Also, I assume you are a native English speaker while writing this. If that’s not the case then let’s learn it together and help each other! Let me know your thoughts…
thanks for the feedback, I think it’s a valid remark that I am still struggling with the “commenting/narrative” part of my Notebooks. So I’ll strongly focus on that!
As for your question, I am not an English native speaker.
then let’s both learn how to write better projects and present them. Let me know if there’s any way I can help you in future.