When it comes to Data Science, I'm always shooting to be the very best, like no one ever was, so what's a better dataset to analyse than this POKEMON dataset from Kaggle! Today is the first day of the 5 Day Data Challenge on Kaggle and we are reading in and summarizing a .csv in Python. Check it out below, or click this link if you'd prefer to read my code on the Gist website instead. Thanks!
The Business Challenge: We need to know which salary to assign to a person depending on how many years of experience they have in the business. We have a prospective employee with 5 years of experience, and we need to know how much we should pay them. Based on the data we have about 30 employees; their Years of Experience and their Salary, can we predict an employee's Salary only given their Years of Experience?
This is my first Kaggle submission, including data cleaning, feature selection and visualisations to make some first impressions on what the data story is telling us about who is most likely to survive. I'll be making some other submissions soon including testing out a few different Machine Learning classifiers to make predictions.
Over the last week I've been figuring out how to web scrape, using some handy tutorials from the internet (mostly this one from Data Science Dojo). I've learnt a lot about Python and Beautiful Soup, and I'm here to share some of that sweet, sweet knowledge with you today! I'm a big fan of video … Continue reading Web-scraping Final Fantasy VII with Python & Beautiful Soup
I'm currently teaching myself how to web scrape with python. Once I've worked out all the kinks in that, I'll upload something on here to show you some tips and tricks on how it works, and where I went wrong/right along the way. In the meantime, I've been trying to figure out how to use … Continue reading ‘For’ loops in python tutorial
