Since I intensively started using Visual Studio Code across my devices, with PowerShell as my main terminal, I started running into the following error quite a lot: <file> cannot be loaded because running scripts is disabled on this system. For more information, see about_Execution_Policies at https:/go.microsoft.com/fwlink/?LinkID=135170. What’s happening here, is…
Ahh, user rights. The cause and solution to all of life’s identification problems. In this blog post I explain how you can access (private) google spreadsheets using the Python gspread library. Before you get started: make sure you have administrator rights to the spreadsheets you are trying to work with.…
Random Forest stays my number one go-to algorithm for quickly prototyping prediction algorithms. Last week, I worked on speeding up a feature engineering and training workflow for a marketing project. I moved from the traditional randomForest package to the — already three years old — package ranger. Here are my…
When you’re an R poweruser, pivoting tables in pandas feels unnecessarily complex. Why are there two pivot functions? Why does it return an index when you wanted a column? Why does it generate multi index columns? Those are the questions I tackle in this blog post. 💥 This blog post…
In this blog post, I will elaborate on a specific warning, the contexts in which it occurs and how you can solve or prevent it. It’s definitely in my top three of generic warnings that I bump into: NAs introduced by coercion Apparently, some NAs were added to my data…
I recently bought a Google Chromebook. It’s light, it’s fast, great battery, but it doesn’t support all the development tools that I’m used to when working on a Windows computer. There’s no Visual Studio Code (Python) and no RStudio (R). Me being a data scientist, that hurt in the beginning.…
Getting a firm understanding of NaNs in your dataset ensures you don’t draw wrong conclusions from an incomplete dataset. In this blog post I show how you can list the amount of NaNs per column, per row, and per group. First, let’s create some dummy data, and add some NaNs.…
Without going into detail, here’s something I truly hate in R: replacing multiple values. In Python’s pandas, it’s really easy. In this blog post I try several methods: list comprehension, apply(), replace() and map(). First, let’s create some dummy data. First, let’s try with list comprehension. The get() function tries…
Here’s another post about seemingly convenient things in pandas. Let’s produce a DataFrame from partially matched columns from another DataFrame. Let’s create some dummy data. Let’s say we are trying to select the columns that contain the world ‘color’. Here’s a solution I found on the web. By converting the…
Having R as my data science lingua franca, some things in pandas feel less intuitive. As I’m slowly transitioning to pandas, I’ll be posting a lot of examples over the next couple of weeks. Here’s the first one: concatenating columns values of a pandas DataFrame into another (new) column. First…