π In this meet-up, we will clean and tidy a messy Kaggle dataset using Python - preview the dataset here. You may choose to download it prior to the meet-up and follow along on your own machine, though just watching is ok, too. π Whilst I was originally intending to centre the meetup around a book/literary theme, I found the aforementioned dataframe (csv) just right for a short meet-up. Though it is titled Amazon book reviews - which is how I found it - it seems to be more about personal care product reviews. π Following a presentation and before/after demo, we will go straight into the code along. π You may find this meet-up useful if you are a beginner, just like me, and interested in playing around with real-world data, data analysis or data science in a broader sense. See you there π FAQs π How much is this meetup? This is a free meetup hosted by a fellow learner. π Do I have to be a PRO member to participate? You don't have to have a PRO account but you may need a free Codecademy account to sign on to the meet-up. π What if I'm late? You can join after the event has started. No stress. You can also check in a few minutes early for a chat with me and your fellow learners. π£ Do I have to actively be involved? You can participate in the code along and keep your camera and mic off or on - completely up to you. Just watching is fine too. π₯ Will this meet-up be recorded? The presentation bit will be recorded, the code along will not. π§Ύ I have something to share with you. Any questions or suggestions, get in touch directly below via the Contact Us button below β¬οΈ, via the Contact Us button on the Codecademy Seoul main page or this anonymous Google feedback form. A huge part of data science involves acquiring raw data and getting it into a form ready for analysis. Some have estimated that data scientists spend 80% of their time cleaning and manipulating data, and only 20% of their time actually analysing it or building models from it. [Source]
Saturday, April 16, 2022
5:30 AM β 6:00 AM UTC
5:30 AM | Intro & Agenda |
5:35 AM | Presentation |
5:45 AM | Code Along |
6:00 AM | Wrap-up |