The first step in building a data science model is: Collecting data.
For beginners in data science, it is easier to grab ready-to-use data files in CSV format from many available public data sources. If anyone is interested, I will list the sites for free publicly available in the future article.
This article is for anyone who would like to learn how to scrape website quickly and easily using the tool in Python you already know (Pandas). I will cover a little bit on the basics of web scraping before talking about the libraries.
I had a problem updating Anaconda Navigator with its UI and managed to solve by updating using the command line. So I wrote this article so it benefits other people and I can also come back if I face this problem in the future. Note that this blog post will be very very short, but very useful.
When was the last time you update your R and RStudio?
I installed RStudio and R a year ago, and never update it since then. Today I just noticed I cannot install new R packages because of my old R version. So I explore some ways to update R and would like to share with someone who is also looking to update R on RStudio.
Last month I attended the Quantify Datathon 2017 event. We are given AirBnb data from insideairbnb.com, then we have 5 days to explore and comes up with the model and/or visualization. Here is the final product from my team, Team Gravy.
It was 3 years ago that I worked with people who used React for the first time. After that, I had many chances to get in contact with React. But I haven’t really write frontend using React until today.
I am quite amazed with the React ecosystem and would like to share my comparison here.
Today I found an online tool that can get the stats of the published articles from Google Analytics. That’s how I got interested in Google Analytics API. As I am studying Data Science at the moment, knowing how to do web analytics would open up a lot of new possibilities.