You're reading from Interactive Data Visualization with Python - Second Edition

Product typeBook

Published inApr 2020

Reading LevelIntermediate

Publisher

ISBN-139781800200944

Edition2nd Edition

Languages

Python

Tools

Matplotlib

Concepts

Data Visualization

Authors (4):

Abha Belorkar

Sharath Chandra Guntuku

Shubhangi Hora

Anshu Kumar

View More author details

Creating Plots that Present Global Patterns in Data

In this section, we will study the context of plots that present global patterns in data, such as:

Plots that show the variance in individual features in data, such as histograms
Plots that show how different features present in data vary with respect to each other, such as scatter plots, line plots, and heatmaps

Most data scientists prefer to see such plots because they give an idea of the entire spectrum of values taken by the features of interest. Plots depicting global patterns are also useful because they make it easier to spot anomalies in data.

We will work with a dataset called mpg. It was published by the StatLib library, maintained at Carnegie Mellon University, and is available in the seaborn library. It was originally used to study the relationship of mileage – Miles Per Gallon (MPG) – with other features in the dataset; hence the name mpg. Since the dataset contains 3 discrete features...

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Interactive Data Visualization with Python - Second Edition

Published in: Apr 2020Publisher: ISBN-13: 9781800200944

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Authors (4)

Abha Belorkar

Abha Belorkar is an educator and researcher in computer science. She received her bachelor's degree in computer science from Birla Institute of Technology and Science Pilani, India and her Ph.D. from the National University of Singapore. Her current research work involves the development of methods powered by statistics, machine learning, and data visualization techniques to derive insights from heterogeneous genomics data on neurodegenerative diseases.
Read more about Abha Belorkar

Sharath Chandra Guntuku

Sharath Chandra Guntuku is a researcher in natural language processing and multimedia computing. He received his bachelor's degree in computer science from Birla Institute of Technology and Science, Pilani, India and his Ph.D. from Nanyang Technological University, Singapore. His research aims to leverage large-scale social media image and text data to model social health outcomes and psychological traits. He uses machine learning, statistical analysis, natural language processing, and computer vision to answer questions pertaining to health and psychology in individuals and communities.
Read more about Sharath Chandra Guntuku

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

Anshu Kumar

Anshu Kumar is a data scientist with over 5 years of experience in solving complex problems in natural language processing and recommendation systems. He has an M.Tech. from IIT Madras in computer science. He is also a mentor at SpringBoard. His current interests are building semantic search, text summarization, and content recommendations for large-scale multilingual datasets.
Read more about Anshu Kumar

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