Guided Project #1: Free Mobile Apps: An Exploratory Data Analysis

Hi everyone! I’ve been using Dataquest for about a month and have been having a blast learning data science.

I’m finally ready to share my first guided project – I spent a little too much time on it… I learned how to add fancy bar charts with the seaborn library, and added comments to all my functions. The final analysis is not very sophisticated, but tweaking my first data science project took a lot of learning and experimenting, so I’m satisfied.

Hope you guys enjoy it! Any feedback or suggestions are welcome. Here’s a link to the notebook on Github. If you liked the project, I’d really appreciate a star – I’m trying to take this data science portfolio building business more seriously.

Here’s a link to the last step of the mission:
https://app.dataquest.io/m/350/guided-project%3A-profitable-app-profiles-for-the-app-store-and-google-play-markets/14/next-steps

mobile-app-eda.ipynb (152.7 KB)



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

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You have done a great work here. The way you have incorporated charts are quite cool. Though they are a bit beyond me at this point of time as I’m a complete beginner with python. But it gives me ideas how I can keep on enriching these initial projects on a later time. Everything looks good, though I feel you could have added a conclusion from your analysis at the end. I know you have added a summary of results at the beginning. But a conclusion at the end would be great.

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Thanks Jithin! Really appreciate your positivity and feedback.

I accidentally uploaded a previous version of my notebook without a conclusion – it should have one now. It’s still not a very satisfying conclusion since my methods were a bit crude.

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Oh yes, I have seen the conclusion now. Looks like you are more experienced than me in this field. So if you think your methods were crude, I’ll just have to agree to that. Anyway great work.

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