My first guided project. Happy with the results. A shout out to wanzulfikri for guidance.
ListOfBanks.ipynb (5.9 KB)
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Hi @Frankie,
Great job completing your first guided project (and thank you very much for the shout out).
It’s great that you took initiative and apply the lessons from one context (“Prison Break”) to another context (“UK Banks”).
I don’t comment much on people’s first guided project because most of the time it’s not reflective of their true capabilities. In reality, most people’s abilities shine very bright when they start sharing their second, third, fourth, etc…guided projects; it’s probably because of the buildup of confidence as they get better and better at doing data science (and handling the tools that come with it).
Anyhow, there are general suggestions that work for most projects:
- Add an introduction. Describe the project, what you intend to answer and why it’s important to get those answers. Another thing to consider adding is a link to the data source and give a brief summary of your findings.
- Add headings and subheadings accordingly. When using the Jupyter notebook, learning how to use Markdown is important especially if you want to explain your project via text. Not everyone reading the project will have the technical know-how to understand the code, so having text explanations is crucial.
- Add code comments. Important for technical readers and your future self as documentation on what your code is doing. No need to comment on everything; focus on the tricky parts. But if you’re starting out, overcommenting is much better than undercomment at least to until writing comment has become a habit.
This project style guide by Dataquest can be very helpful if you want more pointers on how to improve any project.
Keep up with the good work. Cheers.
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Thanks Wan.
This is helpful, when i do my next guided project I will implement these points. Hopefully I can add it to my portfolio.
I am approaching my second guided project, so i am exited to spend some time on that!
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