Seaborn - RxJS, ggplot2, Python Data Persistence, Caffe2 ...

Seaborn

i

Seaborn

About the Tutorial

Seaborn is an open source, BSD -licensed Python library providing high level API for

visualizing the data using Python programming language.

Audience

This tutorial takes you through the basics and various functions of Seaborn. I t is

specifically useful for people working on data analysis. After com pleting this tutorial, you

will find yourself at a m oderate level of expertise from where you can take yourself to

higher levels of expertise.

Prerequisites

You should have a basic understanding of com puter program ming term inologies. A basic

understanding of Python and any of the program ming languages is a plus. Seaborn

library is built on top of Matplotlib. Having basic idea of Matplotlib will help you

understand this tutorial in a better way.

Copyright & Disclaimer

? C opyright 2017 by Tutorials Point (I ) Pvt. Ltd.

All the content and graphics published in this e -book are the property of Tutorials Point

(I ) Pvt. Ltd. The user of this e -book is prohibited to reuse, retain, copy, distribute or

republish any contents or a part of contents of this e -book in any m anner without written

consent of the publisher.

W e strive to update the contents of our website and tutorials as tim ely and as precisely

as possible, howe ver, the contents m ay contain inaccuracies or errors. Tutorials Point (I )

Pvt. Ltd. provides no guarantee regarding the accuracy, tim eliness or com pleteness of

our website or its contents including this tutorial. I f you discover any errors on our

website or in this tutorial, please notify us at contact@

ii

Seaborn

Table of Contents

About the Tutorial ........................................................................................................................................................... ii

Audience............................................................................................................................................................................ ii

Prerequisites ..................................................................................................................................................................... ii

Copyright & Disclaimer ................................................................................................................................................... ii

Table of Contents ............................................................................................................................................................ iii

1.

Seaborn �C Introduction ...................................................................................................................................................6

Seaborn Vs Matplotlib .....................................................................................................................................................6

2.

Seaborn �C Environment Setup.......................................................................................................................................8

Installing Seaborn and getting started ..........................................................................................................................8

3.

Seaborn �C Importing Dat asets and Libraries ........................................................................................................... 10

Importing Libraries ........................................................................................................................................................ 10

Importing Datasets ........................................................................................................................................................ 10

4.

Seaborn �C Figure Aesthetic ......................................................................................................................................... 13

Seaborn Figure Styles .................................................................................................................................................... 16

Removing Axes Spines................................................................................................................................................... 17

Overriding the Elements ............................................................................................................................................... 18

Scaling Plot Elements .................................................................................................................................................... 21

5.

Seaborn �C Color Palette ............................................................................................................................................... 23

Building Color Palette.................................................................................................................................................... 23

Qualitative Color Palettes............................................................................................................................................. 24

Sequential Color Palettes ............................................................................................................................................. 25

Diverging Color Palette ................................................................................................................................................. 25

iii

Seaborn

Setting the Default Color Palette ................................................................................................................................ 26

Plotting Univariate Distribution .................................................................................................................................. 27

6.

Seaborn �C Histogram .................................................................................................................................................... 29

7.

Seaborn �C Kernel Density Estimates ......................................................................................................................... 31

Fitting Parametric Distribution .................................................................................................................................... 31

Plotting Bivariate Distribution ..................................................................................................................................... 32

Scatter Plot...................................................................................................................................................................... 33

Hexbin Plot...................................................................................................................................................................... 34

Kernel Density Estimation ............................................................................................................................................ 35

8.

Seaborn �C Visualizing Pairwise Relationship........................................................................................................... 37

Axes .................................................................................................................................................................................. 37

9.

Seaborn �C Plotting Categorical Data ............................................................................................................................1

Categorical Scatter Plots..................................................................................................................................................1

10. Seaborn �C Distribution of Observations......................................................................................................................6

Box Plots .............................................................................................................................................................................6

Violin Plots..........................................................................................................................................................................7

11. Seaborn �C Statistical Estim ation ................................................................................................................................ 12

Bar Plot ............................................................................................................................................................................ 12

Point Plots ....................................................................................................................................................................... 14

12. Seaborn �C Plotting Wide Form Data.......................................................................................................................... 16

13. Seaborn �C Multi Panel Categorical Plots .................................................................................................................. 20

Factorplot ........................................................................................................................................................................ 20

What is Facet Grid? ....................................................................................................................................................... 22

iv

Seaborn

14. Seaborn �C Linear Relationships .................................................................................................................................. 28

Functions to Draw Linear Regression Models .......................................................................................................... 28

Fitting Different Kinds of Models ................................................................................................................................ 31

15. Seaborn �C Facet Grid .................................................................................................................................................... 35

Plotting Small Multiples of Data Subsets................................................................................................................... 35

16. Seaborn �C Pair Grid ....................................................................................................................................................... 40

v

 ................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download