There are many ways to remove a column in a pandas DataFrame. However, some ways are better than others. In this blog post, I elaborate on multiple solutions and what the pros and cons are. First, let’s load the iris dataset from the Seaborn package on GitHub. Drop a pandas…
In some situations, especially when adding some basic error handling to your Python scripts, you want to check if a column exists before performing operations on it. In this blog post I tell you how. For starters, let’s load the iris dataset from the Seaborn package on GitHub. I’ll be…
Another blog post about an absolute starter subject. Calculating the numbers of rows of a pandas DataFrame is really simple. Yet there are many ways to do them. In this blog post, we elaborate on each and every one of the possible solutions. By looking at the codebase of pandas,…
Apparently, this is something that many (even experienced) data scientists still google. Sometimes you’re dealing with a comma-separated value file that has no header. In this blog post I explain how to deal with this when you’re loading these files with pandas in Python. The read_csv function in pandas is…
I’m still working with the donors dataset, as I have been in many of my latest blog posts. Now, I wanted to calculate the Jaccard text similarity index between the essays from the data set, and use this index as a feature. In this blog post, I outline how you…
It’s an operation I use quite a lot, but I never took the time to find out which solution is fastest. That’s why I decided to dedicate this blog post on how to concatenate columns in pandas (Python) and their execution speed. I’ve been working with the “donors” dataset from…
The title of this blog post says it all: let’s solve a warning. It’s one that occurs when you’re using Pandas’ read_csv. Let’s start with just doing that. Let’s say you run into the following error: Solve DtypeWarning: Columns (X,X) have mixed types. Specify dtype option on import or set…
As an R-native, switching to Python and Pandas has its little annoyances. In R, when you print a data frame, or its head, you get to see the whole shebang. In Pandas, this is not the case: rows and columns get truncated to keep the output manageable. However, there are…
Without a doubt, Pandas is one of the most popular Python packages within Data Science. However, coming from an R background, discovering the difference between the join and merge method was mind-boggling. Especially if it generates confusing errors that urge you to use pd.concat, which you shouldn’t. This is the…
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. To answer some questions…
