python

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… Read More »Pandas’ pivot_table vs. pivot

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.… Read More »Working with NaN’s (nulls/NA’s) in pandas: per column, per row and per group

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… Read More »Replacing multiple values in a pandas DataFrame column

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… Read More »Partial match of pandas DataFrame column name