You have the fundamentals of R Highcharts under your belt by now. The next logical step is to introduce a bit more complexity in the code, but for the greater good. And that good is implementing drilldown charts straight in R! This will allow you to click on individual chart ...

If you’re looking to take your R data visualization skills to the next level, interactivity is the name of the game. There aren’t too many packages that offer it out of the box, but you don’t need quantity if you have quality. Highcharts is among the most ...

In a world where compute time is billed by the second, make every one of them count. There are zero valid reasons to utilize a quarter of your CPU and memory, but achieving complete resource utilization isn’t always a straightforward task. That is if you don’t know about ...

Parallelizing R dataframe computation is a guaranteed way to shave minutes or even hours from your data processing pipeline compute time. Sure, it adds more complexity to the code, but it can drastically reduce your computing bills, especially if you’re doing everything in the cloud. R doParallel package provides ...

When it comes to deploying Shiny for Python applications, you have options – some of which are entirely free. If you have been a developer for some time, you know free deployment isn’t always a given, especially when working with newer, more demanding tech stacks. Luckily, GitHub pages allow you ...

Let’s face it – the technical aspect of writing R and Python packages from scratch isn’t complicated. However, the challenging part lies in proper testing. The goals with package tests are to ensure the package works properly and without any bugs on the client’s hardware and that the ...

Most of the real-world data is stored in databases, so knowing how to access different database systems from Shiny is a mandatory skill. With the rise of Shiny for Python, databases and their access got a whole new meaning, as Shiny developers are no longer limited to R. That being ...

Deep learning might seem like a challenging field to newcomers, but it’s gotten easier over the years due to amazing libraries and community. PyTorch library for Python is no exception, and it allows you to train deep learning models from scratch on any dataset. Sometimes it’s easier to ...

Want to include only the libraries you use in requirements.txt? Try pipreqs, a Python module for creating leaner requirements files.

There's more than one way to Python square roots. Learn 5 approaches to square roots in Python + some bonus advanced tricks.