Hacker News Project II.ipynb (36.8 KB)
Hacker News Project II.ipynb (36.8 KB)
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:
Average Rounded Ask Commentsand
Average Rounded Show Comments
Hope my ideas were helpful. Congratulations on having done a nice project!
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!
You are welcome Bruce! I’m glad that my suggestions were useful.
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?
BruceHacker News Project II.ipynb (36.8 KB)
Click here to view the jupyter notebook file in a new tab
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!
You are welcome Bruce! Have a great weekend you too!
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.
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.
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 …?
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 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.