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Pandas 1.x Cookbook

You're reading from   Pandas 1.x Cookbook Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781839213106
Length 626 pages
Edition 2nd Edition
Languages
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Authors (2):
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Theodore Petrou Theodore Petrou
Author Profile Icon Theodore Petrou
Theodore Petrou
Matthew Harrison Matthew Harrison
Author Profile Icon Matthew Harrison
Matthew Harrison
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Toc

Table of Contents (17) Chapters Close

Preface 1. Pandas Foundations 2. Essential DataFrame Operations FREE CHAPTER 3. Creating and Persisting DataFrames 4. Beginning Data Analysis 5. Exploratory Data Analysis 6. Selecting Subsets of Data 7. Filtering Rows 8. Index Alignment 9. Grouping for Aggregation, Filtration, and Transformation 10. Restructuring Data into a Tidy Form 11. Combining Pandas Objects 12. Time Series Analysis 13. Visualization with Matplotlib, Pandas, and Seaborn 14. Debugging and Testing Pandas 15. Other Books You May Enjoy
16. Index

Multivariate analysis with seaborn Grids

Seaborn has the ability to facet multiple plots in a grid. Certain functions in seaborn do not work at the matplotlib axis level, but rather at the figure level. These include catplot, lmplot, pairplot, jointplot, and clustermap.

The figure or grid functions, for the most part, use the axes functions to build the grid. The final objects returned from the grid functions are of grid type, of which there are four different kinds. Advanced use cases necessitate the use of grid types, but the vast majority of the time, you will call the underlying grid functions to produce the actual Grid and not the constructor itself.

In this recipe, we will examine the relationship between years of experience and salary by gender and race. We will begin by creating a regression plot with a seaborn Axes function and then add more dimensions to the plot with grid functions.

How to do it…

  1. Read in the employee dataset, and...
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