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Python Data Analysis - Third Edition

You're reading from  Python Data Analysis - Third Edition

Product type Book
Published in Feb 2021
Publisher Packt
ISBN-13 9781789955248
Pages 478 pages
Edition 3rd Edition
Languages
Authors (2):
Avinash Navlani Avinash Navlani
Profile icon Avinash Navlani
Ivan Idris Ivan Idris
Profile icon Ivan Idris
View More author details
Toc

Table of Contents (20) Chapters close

Preface 1. Section 1: Foundation for Data Analysis
2. Getting Started with Python Libraries 3. NumPy and pandas 4. Statistics 5. Linear Algebra 6. Section 2: Exploratory Data Analysis and Data Cleaning
7. Data Visualization 8. Retrieving, Processing, and Storing Data 9. Cleaning Messy Data 10. Signal Processing and Time Series 11. Section 3: Deep Dive into Machine Learning
12. Supervised Learning - Regression Analysis 13. Supervised Learning - Classification Techniques 14. Unsupervised Learning - PCA and Clustering 15. Section 4: NLP, Image Analytics, and Parallel Computing
16. Analyzing Textual Data 17. Analyzing Image Data 18. Parallel Computing Using Dask 19. Other Books You May Enjoy

Advanced visualization using the Seaborn package

Visualization can be helpful to easily understand complex patterns and concepts. It represents the insights in pictorial format. In the preceding sections, we have learned about Matplotlib for visualization. Now, we will explore the new Seaborn library for high-level and advanced statistical plots. Seaborn is an open source Python library for high-level interactive and attractive statistical visualization. Seaborn uses Matplotlib as a base library and offers more simple, easy-to-understand, interactive, and attractive visualizations.

In the Anaconda software suite, you can install the Seaborn library in the following way:

Install Seaborn with pip:

pip install seaborn

For Python 3, use the following command:

pip3 install seaborn

You can simply install Seaborn from your terminal or Command Prompt using the following:

conda install seaborn

If you are installing it into the Jupyter Notebook, then you need to put the ! sign before the pip command...

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