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Whether you’re starting a new project or expanding an existing one, as a data scientist, you’re always on the lookout for new material to explore. Knowing where to get data for data science projects can be challenging, and finding “good data” can be even more difficult. In this article, we’ll look at what makes “good data”, what format that data might be in, where to find it, and what the next steps are. 

This is a guest blog post by Adrian Boguszewski, author of OpenCV Image Viewer Plugin. The average programmer makes 70 errors per 1,000 lines of code and spends 75% of their time on debugging (source). In computer vision (CV), this process may involve not only fixing the code but also checking th…

The Gateway to Pandas course has been released on JetBrains Marketplace.

Data science has been the hottest thing for a while now, but it still continues to be a major talking point even today. In fact, according to the U.S. Bureau of Labor Statistics, it’s estimated that around 11.5 million data science jobs will be generated by 2026. We decided to look further into h…

Sooner or later in your data science journey, you’ll hit a point where you need to get data from a database. However, making the leap from reading a locally-stored CSV file into pandas to connecting to and querying databases can be a daunting task. In the first of a series of blog posts, we’ll explo…