Category: Data Science

Regular Expressions (RegEx) in Google Data Studio – Guide With Examples

Regular expressions are great helpers for every data analyst because they allows to transform dimensions applying quite complicated logic rules. In Google Data Studio I often use REGEXP text functions – so I decided to share with you some my most often use cases. In addition – we’ll find out the difference between REGEXP_REPLACE, REGEXP_EXTRACT Read more about Regular Expressions (RegEx) in Google Data Studio – Guide With Examples[…]

Pandas Python Library = Excel On Steroids (tutorial for beginners)

People that never tried programming often think, that programming is something very complicated and hard to start. Honestly I had the same thinking until I tried python – one of the most intuitive programming languages with a low entry barrier. While learning programming it’s important to be able instantly try your knowledge in practice. In Read more about Pandas Python Library = Excel On Steroids (tutorial for beginners)[…]

How To Automate Facebook Ads Reporting In Google Data Studio With Python And FB Marketing API

If You ever wanted to create a dashboard with Facebook Ads data – You probably had an issue with data connectors. The most popular like Supermetrics costs lot of money, although there are some cheap solutions like Pipelinica. But also You can try to create your own solution for free. There is a scheme of Read more about How To Automate Facebook Ads Reporting In Google Data Studio With Python And FB Marketing API[…]

Markov Chain Attribution – Simple Explanation Of Removal Effect

“Markov Chain Attribution” is one of the most popular data driven attribution models. The most important concept behind this model is removal effect. In this article I`ll try to explain the math behind removal effect in a simple way without any formulas. As an example we will take a very simple use case – four Read more about Markov Chain Attribution – Simple Explanation Of Removal Effect[…]

Parallel Coordinates For Multidimensional Data Visualization

Parallel coordinates were invented in far 1885 by French engineer and mathematician Philbert Maurice d’Ocagne. When I discovered this way of visualization – I was really impressed how it allows to visualize such a complicated thing as multidimensional data in a simple and intuitive way. This is how I visualized few dimensions of Mobile App Read more about Parallel Coordinates For Multidimensional Data Visualization[…]