How did data scientists load csv files before pandas?

The Pandas library was first introduced to Python in 2008 by Wes McKinney. He initially started working on Pandas to solve the data manipulation and analysis problems he encountered while working in quantitative finance. The first version of Pandas was released in 2009, and it has since become one of the most widely used data manipulation libraries in the Python ecosystem.

Pandas, therefore, has been used by data scientists for the past 15 years. Before the arrival of this library, however, people had to use other means to load data into a python program. In this post I will illustrate two methods that I have found to upload files before pandas became the mainstay of python data science programming:-

1. Python’s inbuilt csv module
2. Numpy

Python’s inbuilt csv module

Python’s inbuilt csv module is a great way to load and read files without pandas. I have Python 3.11 installed on my laptop, but none of the libraries, so this would be a good choice for me if I wanted to write a program in Python IDLE.

The methodology of using Python’s csv module is as follows:-

1. Import matplotlib.pyplot library because I am going to plot a graph with the data.
2. Import the csv module.