Project review - Predicting Car prices

Hey guys,

Here is my submission for the guided project - Predicting Car Prices.
Predicting Export Car prices.ipynb (1.0 MB)
Looking for some constructive feedback!

Thank you
Raj Tulluri

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


View updated notebook here

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hey @Raj

Thanks for sharing your project!

I am not yet at this mission. I am lagging behind actually, so I can’t comment on anything to do with your code.

I would like to share my thoughts on the plots - they are big, bold, with sharp colors and axis labels. :ok_hand:
Where are the titles though? at least for the bar and box plots? and “residual histogram/ plot” really? :thinking: :thought_balloon:

And the conclusion part is very detailed as well, although I won’t get it now.

2 Likes

Hey @Rucha
Thank you for the feedback!
I had made these changes i.e. naming the plots etc when I uploaded the notebook to my Github. So I posted it here before and forgot to attach the link to my Github.
You can view the notebook here:- https://nbviewer.jupyter.org/github/rajtulluri/Predicting-Car-Prices/blob/master/Predicting%20Export%20Car%20prices.ipynb

What about it?

Thank you so much for reviewing it :grinning:

hi @Raj

I may be jumping the line here, but for me it was like why title it residual histogram?

As I said I am not yet at this mission so not sure what exactly residual is.

but my guess is you are trying to plot something like “Distribution of Residual…”? or histogram plays a role here?

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Hey @Rucha
So basically, Residual is the error in the actual value and the predicted value. Those plots are in fact called as Residual plots. Hence I named it so.
Thanks again for going through the project!
Raj Tulluri

Hey @Raj,

I really love the updated version of this project of yours! You have definitely gone above and beyond the requirements of the tasks. Especially when it comes to visualisations:

  • They are so interesting that they made me curious about going on to the next plot. The colors, labellings and position of these plots are just perfect. They help the reader in drawing conclusions from the data, as all visualisations should.
  • I love the correlation analysis. It was so interesting to see how various physical features of the cars are/aren’t correlated with its price.
  • I am also amazed by those graphs that have histograms and boxplots beside each other. That is such an amazing way to look at the data! :heart_eyes:

I think you can modify the plots of

  • Number of vehicles sold per engine type / Average price of vehicles sold per engine type and
  • Number of vehicles sold per number of cylinders / Average price of vehicles sold per number of cylinders

It will be much easier for the viewer to draw conclusions if the x-axis labels on the 2 subplots followed the same pattern.

Thanks so much for sharing you amazing work with the community, Raj. Looking forward to seeing more from you in here! :smile:

2 Likes

Hey @nityesh

Thank you so much for reviewing it! :smile:
Ohh yes, I see what you mean. I had missed that. Thank you for the feedback.
I have made the required changes.

Raj Tulluri

1 Like

Hey @Raj just wanted to say outstanding Job on this Project, I am still behind and I didn’t get the ML part but the Visualization it was just INSPIRING, I personally want to thank you for sharing this amazing project and looking up to your work for reference and improving my visualization abilities.
Good Job, keep up!

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Hey @alijajedonis

Thank you so much for those kind words. :smile: :smile:

Really liked your project @Raj. A great visualization attracts your attention and keeps you reading!

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Thank you so much @artur.sannikov96

@Raj nice job on your project. Looks great and reads great as well.

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Hey @eugeniosp3

Thank you so much!!