Data visualization with Matplotlib and Seaborn.

Format:

Video

Contributor:

Guimaraes, Monica Estela, presenter.

Koul, Nimrita, presenter.

Manning Publications, publisher.

Language:

English

Subjects (All):

Python (Computer program language).

Information visualization.

Physical Description:

1 online resource (1 video file (3 hr., 2 min.)) : sound, color

Edition:

[First edition].

Place of Publication:

[Place of publication not identified] : Manning Publications, [2025]

Summary:

Data visualization is a vital skill for aspiring and veteran data scientists alike. In this unique series, you'll follow a data visualization expert uncover important insights from company data. Manning's bestselling liveProject series Data Visualization with Matplotlib and Seaborn challenges learners to create attractive visualizations with Python. Now, you can follow along as experienced data scientist Monica Guimaraes guides you through the entire series, showing you how an expert would tackle each project and problem with ease. Monica reveals how to create 2D and 3D plots with Matplotlib to reveal vital business insights for a bike rental service, and explores using the Python Seaborn library to create visually appealing charts for U.S. Census Bureau data. As you watch Monica work, you'll develop your skills in quickly and creatively visualizing data - all with the Python data ecosystem. Nimrita Koul, series author Nimrita Koul is an assistant professor of Computer Science and Machine Learning from Bangalore, India. She holds a Phd in Computer Science with 16 years of experience in teaching Computer Science courses to University undergraduates. Nimrita is a principal investigator for three funded research projects in machine learning. She has designed and demonstrated about 20 data science and machine learning projects to more than 650 students. Nimrita has spoken at multiple international conferences and events. Monica Guimaraes, video presenter Monica Guimaraes has more than fifteen years of experience organizing and teaching undergraduate courses in automata theory, numerical analysis, programming languages, and statistics. Her passion for artificial intelligence goes back to her college years, having done her thesis in automatic-theorem-proving and working later as an AI researcher. She also has extensive experience in software development in corporations.

Notes:

OCLC-licensed vendor bibliographic record.

OCLC:

1517527316

Publisher Number:

10000MNLW202502