Exploratory Data Analysis (EDA) is an essential step in any data science project, as it allows us to understand the data, detect patterns, and identify potential issues. In this article, we will explore how to use two popular Python libraries, Pandas and Matplotlib, to perform EDA. Pandas is a powerful library for data manipulation and analysis, while Matplotlib is a versatile library for data visualization. We will cover the basics of loading data into a pandas DataFrame, exploring the data using pandas functions, cleaning the data, and finally, visualizing the data using Matplotlib. By the end of this article, you will have a solid understanding of how to use Pandas and Matplotlib to perform EDA in Python.
Importing Libraries and Data
Importing Libraries
To use the pandas and Matplotlib libraries in your Python code, you need to first import them. You can do this using the import statement followed by the name of the library.