Titanic Data Analysis

Greetings everybody, I shared this project some months ago: Titanic Data: An in-depth Explanatory Data Analysis - #2 by Ezemonye_Omereji and @Ezemonye_Omereji made some good suggestions on how to make it better so I heeded to his advice and applied all the suggestion gave me.

so here it is and I am open to more suggestions
titanic-data-analysis.ipynb (29.8 KB)

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Hi @OlutokiJohn,

Great job on implementing helpful suggestions from @Ezemonye_Omereji and updating your project! :+1:

You have to fix one thing though: re-run all the code cells in your project. Otherwise, they’re unrendered for now.

As for your pictures, once @WilfriedF gave me good advice that I’m still using. I suggest you apply the same approach.

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@OlutokiJohn ,
I must say this is great tenacity here :clap: and I am motivated to see you return the project with a mention :smile:.
So, you may need to implement notes from @Elena_Kosourova as I am unable to view your plots.
Please keep posted.

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oh I am very sorry, the file was too large to be attached, i’d rerun and post again

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I’ve made the necessary corrections kindly help me go through it, @Elena_Kosourova too

Thank you

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@OlutokiJohn ,
Very well done in achieving your set out goal and I will commend you again for this dedicated time, energy and resources :raised_hands: .
Firstly, you now have a more factual introduction which I consider good :+1:.

  1. I noticed 2 assignment operators “=” sign in one line?
    image

  2. Visualizations are now titled :clap: even though some titles were quite long like
    image

could be “Passenger Classes Vs Gender” and, how is this different from
image

then, this:
image

could be “Distribution of City Passengers Vs Classes

and here:
image

  1. You had more than 3 catplots in trying to answer question 1 with other questions too, and defining a function would’ve been better for code reuse and less code writing.

  2. I think you missed the question-visualization-observation framework in some of your early visualizations but correctly placed in others. Good work.

  3. Conclusion is very impressive and clear.
    Keep this energy going. Kudos!

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Thank you very much for your comments

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