Contents

Regression Plots

Seaborn has many built-in capabilities for regression plots, however we won’t really discuss regression until the machine learning section of the course, so we will only cover the lmplot() function for now.

lmplot allows you to display linear models, but it also conveniently allows you to split up those plots based off of features, as well as coloring the hue based off of features.

Let’s explore how this works:

import seaborn as sns
%matplotlib inline

tips = sns.load_dataset('tips')

tips.head()
total_bill tip sex smoker day time size
0 16.99 1.01 Female No Sun Dinner 2
1 10.34 1.66 Male No Sun Dinner 3
2 21.01 3.50 Male No Sun Dinner 3
3 23.68 3.31 Male No Sun Dinner 2
4 24.59 3.61 Female No Sun Dinner 4

lmplot()

sns.lmplot(x='total_bill',y='tip',data=tips)

<seaborn.axisgrid.FacetGrid at 0x7f239679aed0>
../_images/SB05-Regression Plots_5_1.png 
sns.lmplot(x='total_bill',y='tip',data=tips,hue='sex')

<seaborn.axisgrid.FacetGrid at 0x7f23785346d0>
../_images/SB05-Regression Plots_6_1.png 
sns.lmplot(x='total_bill',y='tip',data=tips,hue='sex',palette='coolwarm')

<seaborn.axisgrid.FacetGrid at 0x7f2377fd6950>
../_images/SB05-Regression Plots_7_1.png

Working with Markers

lmplot kwargs get passed through to regplot which is a more general form of lmplot(). regplot has a scatter_kws parameter that gets passed to plt.scatter. So you want to set the s parameter in that dictionary, which corresponds (a bit confusingly) to the squared markersize. In other words you end up passing a dictionary with the base matplotlib arguments, in this case, s for size of a scatter plot. In general, you probably won’t remember this off the top of your head, but instead reference the documentation.

# http://matplotlib.org/api/markers_api.html
sns.lmplot(x='total_bill',y='tip',data=tips,hue='sex',palette='coolwarm',
           markers=['o','v'],scatter_kws={'s':100})

<seaborn.axisgrid.FacetGrid at 0x7f2354cc1990>
../_images/SB05-Regression Plots_9_1.png

Using a Grid

We can add more variable separation through columns and rows with the use of a grid. Just indicate this with the col or row arguments:

sns.lmplot(x='total_bill',y='tip',data=tips,col='sex')

<seaborn.axisgrid.FacetGrid at 0x7f2354bcfc50>
../_images/SB05-Regression Plots_11_1.png 
sns.lmplot(x="total_bill", y="tip", row="sex", col="time",data=tips)

<seaborn.axisgrid.FacetGrid at 0x7f2354b7c510>
../_images/SB05-Regression Plots_12_1.png 
sns.lmplot(x='total_bill',y='tip',data=tips,col='day',hue='sex',palette='coolwarm')

<seaborn.axisgrid.FacetGrid at 0x7f2377f90810>
../_images/SB05-Regression Plots_13_1.png

Aspect and Size

Seaborn figures can have their size and aspect ratio adjusted with the size and aspect parameters:

sns.lmplot(x='total_bill',y='tip',data=tips,col='day',hue='sex',palette='coolwarm',
          aspect=0.6,height=8)

<seaborn.axisgrid.FacetGrid at 0x7f2351ed7a90>
../_images/SB05-Regression Plots_15_1.png
Grids Style and Color