Recently, I decided to enroll into Moringa School and fuel my data curiosity. Since May, I have been thrown into the deep end of data wrangling using Pandas, visualization using Tableau and exploratory data analysis. I had the chance to do a solo project and this is the outcome.
We were tasked to analyze the NTSB Aviation Accidents database and figure out the safest planes a company can buy. It seemed odd to look at crashed aircraft to figure out safety issues but I set my fingers on the keyboard and coded away.
Data wrangling was my biggest hurdle. Overthinking took first place as questions filled my mind on columns to drop, how to handle the missing data and handling inconsistent data input. In the end, I got the hang of it and Pandas became fun.
Visualization using Seaborn and also Tableau proved challenging too but our Technical Mentor had done a good job showing us what to do. I have a lot to learn but I am positive I am on the right track.
Here is the complete GitHub Repo for those interested in the complete project. I will appreciate all feedback as I strive to get better.
Lessons learnt
- You do not always have to show everything. Present only what the stakeholders need to see. Less is more.
- Data cleaning is a really messy job, but very worth it when done right. Take your time to ensure cleaner insights.
- There is no one-size-fits-all method in Data Science. Everyone has their own unique way to manipulate, visualize data and tell a story. Create your own.
- Accept help. Get into a community. That's how you grow.
I'll keep you updated as I keep going in this journey. Next stop: SQL and Statistics. Till next time, Happy coding everyone.
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