Build a Python Interactive Data Dashboard with Dash & Plotly | Data Analytics: World Happiness Index

[@codewithjoshoffical]

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[@sugarfree1122]

I wanted to try visualizing this dataset myself, but I'm amazed by your work. You're awesome! Thanks Josh!

[@codewithjoshoffical]

Thank you so much! I’m happy to have you here, let me know if there’s any questions ✌🏼

[@sugarfree1122]

@@codewithjoshoffical This video is an hour long, but it took me way longer to follow along, haha. I’m doing a data analytics bootcamp in Germany, and I’ve just started learning Python. I haven’t gotten to Dash and Plotly yet, but making a dashboard with them looks super cool. I didn’t fully get your code, just followed it step by step. It would be awesome if you could do a video on Dash and Plotly from the basics for beginners like me. Looking forward to your next videos!

[@codewithjoshoffical]

Thanks! The dashboards definitely help if you have an understanding of HTML and containers but I can work on a Plotly series of time too. Not just projects. You said you’re in a bootcamp, not sure how you’re finding it but I will leave my Data Analytics series here for you. Maybe sth will be helpful! Data analytics playlist- kzbin.info/aero/PLEpRcxOmTFlP5cg2Xfa-QqiXC_FVI3xHm&si=me6mSe2hF09aQCEs

[@bubelerasmeni1846]

Super useful tutorial. Show us how we can deploy this locally. Thank you again, this was good.

[@codewithjoshoffical]

Thanks, I’m glad you found it insightful! I’ll keep this in mind as I make more of these style projects, possibly a one just for deployment too 😄

[@CapDavyJons]

You are awesome Josh, your great work and channel are highly appreciated ❤

[@codewithjoshoffical]

Thank you for the kind words! I’m glad you’re getting value from my channel 😁

[@TheAdventureOfLife]

Keep up the great work! This was cool, reminded me of time spent working with Flask somewhat

[@codewithjoshoffical]

I’m glad you enjoyed it! Web app but for data

[@ghostofuchiha8124]

Hey Josh , I just want to know how does a ML model handle data once its deployed in production.? Like when we build a model we scale the data , remove nulls ,transform it and then use it , but how does all this happen in already deployed models? Because a normal day to day life will have all the uncleaned data. Pleas help , I m really confused. I can build the ml , dl , transformers etc but am confused how is data preprocessing tackled after model is deployed . Basically how is all preprocessing captured in the model to be used after deployment , is it through columntransformers and pipelines or are there any other steps or is it under mlops umbrella ?

[@codewithjoshoffical]

I’m no master in ML but have worked with it for projects and what not. From my understanding once the model is deployed it handles new data in either a real-time or batch processing environment. It uses a preprocessing pipeline, which you can integrate with the model or deploy alongside it. This will transform incoming data the same way it was during training. There are quite a few steps, many of which still include things like cleaning, normalization, etc. You can use ColumnTransformers and Pipelines yes, but usually in a production environment it still falls into MLOps, which have more steps. Hope that answers helps out a bit 😁

[@rushikeshdane5855]

@@codewithjoshoffical ml ops is the answer

[@CapDavyJons]

Could you please teach us in the future how to create a charity web app that can display the total donations received and showcase different donation programs?

[@codewithjoshoffical]

Interesting Idea here 💡

[@ultimatesound8515]

Drop a like for this one 👍 Cool project.

[@codewithjoshoffical]

Thank you!