A favorite among data scientists, the R programming language offers ease of use and versatility across a wide spectrum of projects
Working on a simple project in R is a great introduction to the language and its programming environment. It’ll not only give you a sense of the libraries at your disposal, but will give you valuable exposure to real data science work.
In this article, we’ll introduce R and data science generally, before suggesting a few projects for R novices.
Relational databases store information in tables — tables with columns analogous to elements in a data structure and rows which are an instance of that data structure. Sometimes the question becomes how to identify the specific data needed, how to filter away the unwanted. The SQL-language SELECT statement extracts data from those tables, its WHERE clause filters out data which doesn’t satisfy specified conditions, and the LIKE modifier filters existing data through exact matches and wildcard searches. This blog entry will demonstrate use of the LIKE clause and cover wildcard characters and their use in search patterns.
Over the past decade, big data has had a tremendous impact on business — yet we’re still just scratching the surface. To move forward, we need to have the right tools in place to manage big data’s potential. In this article, we’ll present Hadoop as one solution to the problem of storing and analyzing big data.
One of the most common ways programmers use the
Math object is to create random numbers. Randomness is used programmatically in art, science, and gaming. Whether you’re simulating the stroke of a sable paintbrush, running a controlled medical trial, building an online casino, or encrypting anything, you need random numbers.
setInterval(). Each function defines specific times that dynamic events should happen; they work differently and are best used in different contexts..