Python Exploratory Data Analysis (EDA) - Insurance Charges

In this video, we will explore an insurance charges dataset using Python libraries such as pandas, numpy, seaborn, and matplotlib. Through this exploratory data analysis, we will gain insights into factors that affect insurance charges such as age, BMI, smoking habits, and more. We will use various visualizations and statistical measures to understand the distribution of the data and the relationships between different variables. By the end of this video, you will have a better understanding of how to use Python to explore and analyze datasets, and you will be able to apply these techniques to your own data analysis projects. Thanks for watching my video.

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My website: https://www.onurbaltaci.com

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