Python exploratory data analysis and why it's important

What is exploratory data analysis? 

Exploratory data analysis focuses on what insights you can derive from the data. The process starts with defining the problem you need the data to solve. One of the first steps is to figure out what the business objective you need to address is. What is the specific end goal for your analysis?

Once you know the business objective, it's possible to prepare your data and develop different models to achieve that goal. It also allows you to summarize the available data, find correlations and create visualizations to present your findings to stakeholders.

Exploratory data analysis is an important part of defending your model to business stakeholders and proving that it can produce the desired results.

Exploratory data analysis essentials

Learn about the fundamentals of exploratory data analysis and how it can be used to generate meaningful information.

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Commonly used tools

There are plenty of tools that can facilitate the exploratory data analysis process, from tools built into programming languages such as Python and R to tools supported by vendors such as SAS and KNIME.

Python exploratory data analysis is common among data scientists as Python is one of the most-used programming languages in the field. Available programming libraries such as pandas and Matplotlib can easily summarize and create visualizations for your data. Additionally, there are libraries in the language that can facilitate hypothesis testing and identify correlations between factors.

Learning to use Python for exploratory data analysis

By understanding your data set with exploratory data analysis, it is possible to determine the effectiveness of your model and better determine the correct machine learning model to reach your defined business goals. Learning Python exploratory data analysis can help you easily pull the most meaningful insights from your data using a tool you're already familiar with.

In their new book, Hands-On Exploratory Data Analysis with Python, published by Packt Publishing, authors Suresh Kumar Mukhiya and Usman Ahmed talked about useful techniques and Python tools for exploratory data analysis. The book includes links to sample code with step-by-step instruction on how to perform each process.

Here's a preview of the book. Click here to read Chapter 1: Exploratory Data Analysis Fundamentals.