Python Pandas

Let’s take a look at a few different ways to filter and select rows in a pandas dataframe based on multiple conditions. If you want to watch a YouTube video based on this tutorial, it is embedded below. To start we’re going to create a simple dataframe in python: pd.dataframe created 6 functions to filter […]

In this lesson, we are going to take a look at the Pandas Melt function. This is a way to transform a dataframe to convert columns to rows. Later in this lesson, we will take a look at some of the benefits of using melt with a groupby and plotting. This lesson is based on […]

By using query, you can simply filter down a dataframe in a more readable format. In this lesson we will go over how to use this with numbers, strings, variables, and more. If you want to watch a YouTube video, the one this lesson is based on is down below. Let’s start by importing in […]

The pandas.shift() function is a powerful and versatile tool in data analysis with Python. It allows you to shift the values of a DataFrame or Series up or down along an axis, making it especially useful for comparing a row or column to its previous or future counterpart.  This functionality is commonly applied in time […]

Using explode within Python Pnadas allows you to transform each element of a list to a new row within a dataframe. Python Pandas Explode YouTube Video If you want a video demonstration of how the code works, checkout the video below on our YouTube channel. When working with Python Pandas the first step is to […]

Many data analysts begin their journey with SQL, learning how to use GROUP BY to aggregate and summarize data. As they advance, they often transition to Python for more complex data manipulation. One of the key features in Python’s Pandas library is the groupby function, which allows for powerful and flexible data grouping and aggregation. […]