GP: Exploring eBay car sales data with pandas

Hey there!
The time came for me to share my first completed project! I’m psyched! :crazy_face:
I started from zero knowledge on coding, so, please, don’t be harsh.
Looking forward to your feedback!

Link to the last screen of the project: Learn data science with Python and R projects

Ebay Cars.ipynb (73.7 KB)

Click here to view the jupyter notebook file in a new tab

Hello @daryaholodova! Thanks for sharing your first project with the Community:) I read through the project and I’d said that it’s well organized and you always come straight to the point. Your conclusions are very short which is very important for a reader who wants useful information as quickly as possible.

Some suggestions from my part:

  • Avoid heading’s numbering, it only distracts the reader’s attention
  • Come up with some more attractive subheadings in the Data Cleaning part or remove them at all, right now there are very long and add only little useful information
  • Avoid too obvious code comments like “#Checking the result” in [3]
  • Pay attention to the warning in [7]
  • Have you checked what percentage of entries with the price of 0 you’d removed?
  • In “Damaged cars prices” it’s not immediately clear what “no” and “yes” mean
  • In “Conclusions”, you can explain why more expensive cars, in your opinion, have higher numbers on the odometer

That’s it! Happy coding and good luck with your next project :grinning_face_with_smiling_eyes:

1 Like

Thanks a lot, Artur!
I think yours are very valuable advice!
I will try to make some corrections according to them.
As for the warning about default regex value, I haven’t worked with re module before, so I will have to do some research first.

Спасибо и хорошего дня!

1 Like

Hi @daryaholodova!

I said that you have to avoid numbered heading but it’s not a rule because you may find the opinion that it’s necessary to keep the project in order. I share this opinion if the project is huge:)

1 Like

Thanks for the follow-up, Artur!
Yeah I get what you mean. Depends on the case, and the only hard rule is to prioritize clarity.

1 Like