👉 View my Kaggle Notebook & Dataset. All questions and insights I wanted to discover are all noted in the Notebook.
April 2022, I started challenging myself with BOLT UBC Hackathon. At that time, I applied my limitted knowledge about Python analysis tools and libraries such as Pandas and Matplotlib to solve the case. However, I didn't feel very comfortable with them so it took me ages to wrap my head around the dataset. I found it interesting when being able to pull out new insights. Slow but fun. Obviously, 24 hours was too short for me to get anything done so I decided to keep that pace, relax and just got to watch the final pitch to know how the other teams deal with this case.
And it's worth it as I always tried to get back to my Jupyter Notebook and create a new version of my analysis even though the competition was over. Eight months after that, I rolled out the third version of this notebook and hosted it on Kaggle. This time, I asked more deeper questions, explored more aspects of the dataset where I have never touched before, did more complex transformation and extremely comfortable to use Pandas, Matplotlib and Plotly to answer questions that I want.
This is defintely not the final version of it as there is still room for me to improve. I'd love to hear any thoughts or recommendations that you have.
💖 Thank you for reading till the end and I'll keep posted if there is anything new.