You're reading from The Data Analysis Workshop

Product typeBook

Published inJul 2020

Reading LevelIntermediate

PublisherPackt

ISBN-139781839211386

Edition1st Edition

Languages

Python

Tools

Jupyter

Concepts

Data Science

Authors (3):

Gururajan Govindan

Shubhangi Hora

Konstantin Palagachev

View More author details

Summary

In this chapter, we applied univariate EDA to a given dataset to plot the distribution of individual features and implemented bivariate analysis to understand the relationship between two features. We also used a correlation heatmap to determine the correlation of the features of the DataFrame. Drawing conclusions from the results of our analyses, we were able to build a statistically probable profile of a high-risk customer most likely to default on a loan.

In the next chapter, we will analyze the medical data of 303 patients and link the data features with the diagnosis of heart disease.

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The Data Analysis Workshop

Published in: Jul 2020Publisher: PacktISBN-13: 9781839211386

Authors (3)

Gururajan Govindan

Gururajan Govindan is a data scientist, intrapreneur, and trainer with more than seven years of experience working across domains such as finance and insurance. He is also an author of The Data Analysis Workshop, a book focusing on data analytics. He is well known for his expertise in data-driven decision-making and machine learning with Python.
Read more about Gururajan Govindan

Shubhangi Hora

Shubhangi Hora is a data scientist, Python developer, and published writer. With a background in computer science and psychology, she is particularly passionate about healthcare-related AI, including mental health. Shubhangi is also a trained musician.
Read more about Shubhangi Hora

Konstantin Palagachev

Konstantin Palagachev holds a Ph.D. in applied mathematics and optimization, with an interest in operations research and data analysis. He is recognized for his passion for delivering data-driven solutions and expertise in the area of urban mobility, autonomous driving, insurance, and finance. He is also a devoted coach and mentor, dedicated to sharing his knowledge and passion for data science.
Read more about Konstantin Palagachev

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