Ggplot is R’s premier data visualization package. Its popularity can likely be attributed to its ease of use — with just a few lines of code you are able to produce great visualizations. This is especially great for beginners who are just beginning their journey into R, as it’s very encouraging that you can create something visual with just two lines of code:

ggplot(data = iris, aes(x = Sepal.Length, y = Sepal.Width)) +
  geom_point()

What is Scorigami?

Scorigami is a concept thought up by Jon Bois. It is the art of building final scores that have never happened before in NFL history. Due to the unique nature of how points are scored in (American) Football, there are a lot of scores that are possible, but have never happened.

It’s always exciting when a Scorigami happens — over 180k people follow a Twitter account built for this exact purpose.

Mechanical keyboards look and sound great. Not only that, but they’re a lot more fun to type on as the feedback is more tactile than a normal keyboard. However, mechanical keyboards are expensive, with some of the costliest models ranging from a couple hundred dollars to over a thousand dollars. When investing in a piece of tech like this, are there any benefits to typing speed?

When I first discovered mechanical keyboards, it was back in 2013. I was an undergraduate at UC Berkeley, and just splurged $120 on a new keyboard.

As a consumer, Yelp provides helpful information when you’re looking to visit a business for the first time. Whether it’s looking for a new place to eat Chinese food, a new gym to join, or a place to get your haircut — Yelp is a great resource for making a very personal decision on whether or not you want to visit a business.

Yelp data becomes fascinating when you take a macro view. This requires scraping business data across hundreds of American cities. By doing this, we have one of the richest business datasets that covers a majority of America…

Data visualization is one of the most powerful tools in analytics. It’s the best way to make sense of and communicate data to others. While a powerful tool, it is only as useful as the hands they are in. In visualizing data, as in any other field — there are rules, best practices, and guidelines. Of course, there are also mistakes.

I wanted to go over five of the most common mistakes that I’ve experienced and seen. …

Whether you’re trying to build a portfolio to be a stronger data science candidate, or looking to take on a new data-related challenge that can earn you money — I want to make the case the Daily Fantasy Sports is a great candidate for your next project.

What is Daily Fantasy Sports (DFS), and how is it related to data science? DFS mirrors season-long fantasy sports but condenses it into a shorter, more sweat-inducing format. With a lot of sports being book-shelved this year, eSports has also become a popular category under this model.

In DFS, you need to make…

One of the most underrated skills that a data scientist can develop is the skill of writing.

Why is this? When we think about the role of a data scientist, it breaks down to four main buckets:

1. Being the person who understands the data the most: When working with engineers, product managers, or data scientists from other teams — you should be the data expert. This is because you the most hands-on experience with the data in your domain. Not only that, but as a data scientist you should be shaping what/how data is tracked and how they are defined.
2. …

For those in college, two of the most important decisions you’ll have to make are:

• What do I want to major in?
• What career do I want to pursue?

Unsurprisingly, these two decisions are closely intertwined. In order to pursue a career in software engineering right out of college, it’s important that you major in computer science. If you want to go into investment banking, economics, or business make the most sense.

Having gone to a competitive school, there was always a lot of chatter around a third topic: What careers are the most lucrative? …