Hacker News Worthy

Updated version:

Hacker News Project II.ipynb (36.8 KB)

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Hi Bruce,

Now I’ve reviewed your project. It looks really cool! Very profound data analysis, great idea to dig deeper, and great direction of digging: checking the most popular hours by day of week. I liked also your way of reasoning and all the observations and conclusions in markdown. Emphasizing the most important ideas is also a good practice. Ah, and also good idea to use pretty-printing (I mean, adding ---- to print small subtitles with print()). Well done!

What I would suggest to you:

  • It’s better to re-run the project when it’s already completed, to have all the code cells in order and starting from 1.
  • I noticed that you used too many quote marks in markdown explanations, for many words all around the project. Probably you might consider to remove some :slightly_smiling_face:
  • The code cell [108]: it’s enough to print only the rounded results: Average Rounded Ask Comments and Average Rounded Show Comments
  • There is one paragraph repeated twice: the first time after the subheadings ’ “Ask HN” and “Show HN” Totals’ (except for the first line), the second - after this one ’ “Ask HN” vs “Show HN” Comments’. I would suggest to you to remove the first one, since this paragraph actually describes the results of the code cell [108], which occurs further on.
  • You can consider putting the technical details related to the code itself as short comments inside the relevant code cells (especially in long code cells), while leaving all the observations and explanations of the results in the markdown cells.

Hope my ideas were helpful. Congratulations on having done a nice project!

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Thank you Elena for all your feedback.
I especially appreciate feedback that helps me to improve as I journey on!
Thank you for taking time to do that!
Best regards,
Bruce

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You are welcome Bruce! I’m glad that my suggestions were useful.
Happy learning!

Hello Elena.
I have cleaned up my original “Hacker News” project file as per your recommendations.
Would you be able to replace my original one I submitted with the latest one as attached?
Best regards,
BruceHacker News Project II.ipynb (36.8 KB)

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

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Hi Bruce,

That’s great that you’ve already updated your project!
And yes, I’ve replaced your original notebook with the latest version.

Thank you Elena for taking care of that!
Have a great weekend!
Bruce

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You are welcome Bruce! Have a great weekend you too!

Hi @sbgraham72
Thanks for sharing your project on Exploring the Hacker News. I love the way you have presented most of the explanations, use of comments is also of the best level. Much has been said by Elena, and just to add, I think it would better to provide in the introduction , the link of the dataset you are using and hope you will fix up this in your upcoming projects. Otherwise , congratulations for the good work and just wishing you the best in your upcoming projects.
Happy learning.

Thanks Brayan for your feedback.

I’m not sure what you mean by “the link of the dataset I’m using”.

When I import the dataset provided by DataQuest, I’m not sure of the database location.

Where exactly my saved Notebook “physically” is, I have no idea.

It is somewhat confusing to me.

Regards,

Bruce

Brayan:

A question about the Python Notebook type of file *.ipynb.
I’ve only been able to export my saved file from Jupyter as a *.ipynb type.
Once on my hard drive, can it be converted to a format that can be opened from Windows, like *.pdf or MsWord or …?
Thanks.
Bruce

Hi Bruce,

About the dataset link, you can usually find it in the first or second screen of a guided project. In your case, the necessary screen is the following:


You will find there this sentence:

You can find the data set here, but note that it has been reduced from almost 300,000 rows to approximately 20,000 rows by removing all submissions that did not receive any comments, and then randomly sampling from the remaining submissions.

Selecting that “here”, from the mission screen or directly from the sentence above, you’ll open the link to your dataset.

Now about rendering your jupyter notebook into pdf. First of all, I would highly recommend you for all your future guided projects to work not from the DQ platform, but from your local computer. The best solution is to install Anaconda and work in Jupyter from it. In this case, you can always save your projects wherever you want on your own computer. Also, from Jupyter your can download your notebook in many other formats, not only in ipynb. For this purpose, you should select File - Download as - … and then a format you want. You might consider selecting the format Markdown(.md). In this case, your project will be downloaded as a text file and, separately, pictures (if you have any graphs in your project). In the text, you’ll have also all your code, but in markdown form (i.e., using backticks ``).

Thank you Elena!
I do have Anaconda Navigator on my computer. So, I’ll try to operate from Jupyter on it next Guided Project.
I still haven’t figured out how to find my two Guided Projects in the Community.
Regards,
Bruce