Real-World Data Analysis & Visualization with Python! (Olympics Dataset Analysis)

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  • Опубліковано 25 лис 2024

КОМЕНТАРІ • 19

  • @KeithGalli
    @KeithGalli  4 місяці тому +3

    Shout out to everyone that tuned in today!! 🙌
    Link to the final app we deploy is here: keithgalli.shinyapps.io/olympics/.
    My notebook & app code can be found on this github branch: github.com/KeithGalli/Olympics-Dataset/tree/livestream
    Let me know what livestreams I should do in the future!

  • @alammaravilla8073
    @alammaravilla8073 3 місяці тому

    AMAZING LIVE STREAM, LOVED IT, THANK YOU FOR SHARING YOUR KNOWLEDGE WITH US!

  • @kulwantsembhi1982
    @kulwantsembhi1982 4 місяці тому +4

    complete data analysis in polars will be helpful

  • @jeremy4510
    @jeremy4510 3 місяці тому

    Subbed only with the hope youll do more lives

  • @TheGmr140
    @TheGmr140 4 місяці тому

    Nice code and information 😊

  • @garyphan-lo4vi
    @garyphan-lo4vi 4 місяці тому

    thank you for another information video ‼️‼️

  • @Clipaholick
    @Clipaholick 4 місяці тому

    great tutorial!!

  • @AK-Star007
    @AK-Star007 4 місяці тому

    What you show is how real world issues happen and resolved. That how we learn

  • @technicalsanjeev8630
    @technicalsanjeev8630 2 місяці тому

    Love from India 🥰🇮🇳

  • @nikitabogatyrev7091
    @nikitabogatyrev7091 4 місяці тому

    Hi, Thank you so much for your videos! Very useful. i like how you think make mistake etc during the video when you solve problems. Please could you please make another vidoe of solving data structure problem in algoExpert or leetcode or something like this.

    • @KeithGalli
      @KeithGalli  3 місяці тому

      Definitely will make more videos/livestreams doing algoexpert/leetcode soon!

  • @mebrarkucuk8557
    @mebrarkucuk8557 3 місяці тому +1

    How did you extract the data from website in the first place?

    • @KeithGalli
      @KeithGalli  3 місяці тому

      So basically each athlete has their own page on the olympedia.org website so I programmatically ran a loop that went from 1 to like 150000 scraping the info from each athlete page and combining it together into a single file. I added the scraping code to the github repo, you can check it out here: github.com/KeithGalli/Olympics-Dataset/blob/master/scrape_data.py

    • @mebrarkucuk8557
      @mebrarkucuk8557 3 місяці тому

      @@KeithGalli Oh 10x a lot sensei,
      You cannot even imagine how much progress you have made in my career. Please continue to learn and improve yourself, because there are many young people who are developing and learning with you.
      Greetings from Turkiye .We keep on following :))

  • @AkshayaAjay-156
    @AkshayaAjay-156 3 місяці тому

    Sir , did u scrap the different info of data and cleaned it and then uploaded in the git hub repo?. If so, Could you please make a video on that too so that we can learn how to scrap ,clean and combine

    • @KeithGalli
      @KeithGalli  3 місяці тому

      That's correct. I'm not sure if I'll make a video on the scraping portion, but I've shared the scraping code on github: github.com/KeithGalli/Olympics-Dataset/blob/master/scrape_data.py and you can watch the previous data cleaning live stream I did to see how we processed the raw data files: ua-cam.com/users/liveoad9tVEsfI0?si=G6ttSJxJpp8AiuDp

  • @sebastianalvarez1537
    @sebastianalvarez1537 3 місяці тому

    🏁🏁🏁

  • @nyctophilicenigma2838
    @nyctophilicenigma2838 3 місяці тому

    at this point 59:33 instead of removing YOG I just included only Olympic games and it's giving perfect result : 2974
    medals = results[(results['medal'].notna()) & (results['event'].str.endswith('(Olympic)'))]

    • @KeithGalli
      @KeithGalli  3 місяці тому

      Nice, good solution. Thanks for sharing!