Today, we walk thru a basic machine learning pipeline including a train/test split and make use of a random search to conduct a hyperparameter tuning. This architecture is the backbone of many statistical machine learning tasks and hence usefuls as to keep close-by as a code-snippet!
Do you need to create pivot tables in Excel, but prefer to work with Python? This is exactly what we are dealing with tody! In this post, we read in a csv file on a zoo’s food expenses and create a pivot table out of it - all in Python!
In this code snippet, we look at how to edit axis and legend labels in seaborn. While this is a very basic task, it is one I find myself often searching the internet for. To give you (and me) a shortcut to a code example, I created this little post.
In this short post, we are looking at how to implement plotly graphs into your own blog posts. For this, I am assuming that you use a site-generating framework that is based on either markdown or html files. For DS-Econ I am using Hexo.
