My 3rd Guided Project: Exploring Hacker News Posts

I just finished my 3rd guided project on Dataquest. By following the normal data science workflow, I collected and downlaoded the Hacker News dataset on Jupyter notebook, then clean the data to extract the relevant information needed for the analysis.

In conclusion, I was able to find out that Ask Posts made at 15:00 (16:00 WAT) generated more average number of comments than other hours. Thus, it is the perfect time to make an Ask Post. In addition, considering the top 5 hours with most average number of comments, I found out that any Ask Post made between 15:00 and 21:00 will have higher chance of receiving more comments.

I would like to receive your feedbacks on areas of improvement. The solution notebook is provided below.

P3 Exploring Hacker News Posts.ipynb (19.0 KB)

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

2 Likes

Hello,

Well done on completing the project.

I’m not sure my suggestions will necessarily be an improvement to your work, so feel free to disregard when it’s not.

  1. In the introduction, consider giving your readers context on why you want to answer the two questions. True, the project is provided by Dataquest, but let’s say that it’s you who decided to start the project because you need the answers to those questions. For example, why is it important for you to know whether Ask Post or Show Post receive the most comments on average?
  2. Consider making your analysis more interpretive. Why do you think the results are the way they are? What factors are possibly affecting those results? Are there limitations in your analysis? What data might be missing? What could be done better next time?

Anyhow, keep up the good work.

2 Likes

Thank you for the feedback. I will surely check it out and make improvements on the introduction and analysis.

1 Like

Hi @abdullahimadabo

Great job on 3rd project:

  • It was easy to follow and divided into clear sections with headings.
  • Great job adding comments to explain code.
  • The output from the code was easy to read.
  • The variable names were easy to understand.
  • Great job storytelling

After reading your project, I was quickly able to learn the best time to make a post and which title to use.

1 Like

I appreciate your feedback.
It encourages me to keep going.
Thank you.

Great job on completing your 3rd Project :smile:, some things you did well.

  • Clear introduction
  • I like the comments within the code to make it more easier to understand what was going on.

Possible improvements:

  1. When you worked out your Average comments per post maybe worth creating a function? Since in that code you repeated the same task twice.

  2. Maybe worth exploring other types of questions Dataquest didn’t provided. That way it makes it more unique. Example maybe worth trying to answer: Do post within 15:00 to 16:00 has also higher average points?

Beside that well done, and keep up the work! :grinning: :+1:t5:

1 Like