Learn Data Analysis with Python: A Case Study

In this post, I’ll do a brief tutorial on Python for data analysis. Analyzing data can be an enjoyable, well-paying job. Payscale estimates show that entry-level positions have an average salary above USD $60k. However, there are hard-skill requirements that you must meet, such as knowledge of SQL or a data analysis programming language such as Python or R. 

To illustrate using Python for data analysis, we’ll be studying infidelity in marriages, which should be an interesting project. Let’s get started!

How to begin a data analysis project using Python

First, we need a software called an integrated development environment (IDE) to perform analysis with Python. My choice is Google Colaboratory, which I feel provides the most frictionless experience. You can use it directly from your Google Drive. In the video below, I walk you through how to set up a Google Colab, and also walk you through the tutorial

Now that we’re set up, we need tools. In Python, these are called libraries. Here, we will add Pandas and Seaborn, which Python will use to manipulate, analyze, and visualize the data. 

• Pandas is an open-source library that assists Python in manipulating and analyzing data.
• Seaborn is a library that Python uses to create meaningful data visualizations.

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