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Numerical Computing with Python

You're reading from   Numerical Computing with Python Harness the power of Python to analyze and find hidden patterns in the data

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Product type Course
Published in Dec 2018
Publisher Packt
ISBN-13 9781789953633
Length 682 pages
Edition 1st Edition
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Authors (5):
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Pratap Dangeti Pratap Dangeti
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Pratap Dangeti
Theodore Petrou Theodore Petrou
Author Profile Icon Theodore Petrou
Theodore Petrou
Allen Yu Allen Yu
Author Profile Icon Allen Yu
Allen Yu
Aldrin Yim Aldrin Yim
Author Profile Icon Aldrin Yim
Aldrin Yim
Claire Chung Claire Chung
Author Profile Icon Claire Chung
Claire Chung
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Table of Contents (21) Chapters Close

Title Page
Contributors
About Packt
Preface
1. Journey from Statistics to Machine Learning FREE CHAPTER 2. Tree-Based Machine Learning Models 3. K-Nearest Neighbors and Naive Bayes 4. Unsupervised Learning 5. Reinforcement Learning 6. Hello Plotting World! 7. Visualizing Online Data 8. Visualizing Multivariate Data 9. Adding Interactivity and Animating Plots 10. Selecting Subsets of Data 11. Boolean Indexing 12. Index Alignment 13. Grouping for Aggregation, Filtration, and Transformation 14. Restructuring Data into a Tidy Form 15. Combining Pandas Objects 1. Other Books You May Enjoy Index

Other two-dimensional multivariate plots


FacetGrid, factor plot, and pair plot may take up a lot of space when we need to visualize more variables or samples. There are two special plot types that come in handy if you want the maximize space efficiency - Heatmaps and Candlestick plots.

Heatmap in Seaborn

A heatmap is an extremely compact way to display a large amount of data. In the finance world, color-coded blocks can give investors a quick glance at which stocks are up or down. In the scientific world, heatmaps allow researchers to visualize the expression level of thousands of genes.

The seaborn.heatmap() function expects a 2D list, 2D Numpy array, or pandas DataFrame as input. If a list or array is supplied, we can supply column and row labels via xticklabels and yticklabels respectively. On the other hand, if a DataFrame is supplied, the column labels and index values will be used to label the columns and rows respectively.

To get started, we will plot an overview of the performance of...

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