Regression Plots



In [1]:

    
import seaborn as sns
%matplotlib inline



In [2]:

    
tips = sns.load_dataset('tips')



In [3]:

    
tips.head()









    Out[3]:






  
    
      
      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()



In [5]:

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









    Out[5]:





<seaborn.axisgrid.FacetGrid at 0x117c81048>



In [6]:

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









    Out[6]:





<seaborn.axisgrid.FacetGrid at 0x11bf59f98>



In [13]:

    
sns.lmplot(x='total_bill',y='tip',data=tips,hue='sex',palette='coolwarm')









    Out[13]:





<seaborn.axisgrid.FacetGrid at 0x11d0ca080>

Working with Markers



In [16]:

    
# 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})









    Out[16]:





<seaborn.axisgrid.FacetGrid at 0x11d8ab748>

Using a Grid

We can add more variable separation through columns and rows with the use of a grid



In [28]:

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









    Out[28]:





<seaborn.axisgrid.FacetGrid at 0x1215cd048>



In [30]:

    
sns.lmplot(x="total_bill", y="tip", row="sex", col="time",data=tips)









    Out[30]:





<seaborn.axisgrid.FacetGrid at 0x1226144e0>



In [24]:

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









    Out[24]:





<seaborn.axisgrid.FacetGrid at 0x11cbb02e8>

Aspect and Size

We can ajust the figure aspect and size by setting size and aspect parameters



In [36]:

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









    Out[36]:





<seaborn.axisgrid.FacetGrid at 0x12420e5c0>

	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