In [1]:

    

import numpy as np
from numpy.random import randn
import pandas as pd

from scipy import stats

import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns

%matplotlib inline


    

In [2]:

    

tips = sns.load_dataset('tips')


    

In [3]:

    

sns.lmplot('total_bill', 'tip', tips)


    

    
Out[3]:





<seaborn.axisgrid.FacetGrid at 0x107108dd0>






    

In [4]:

    

sns.lmplot('total_bill', 'tip', 
           tips, scatter_kws={'marker':'o', 'color': 'red'},
          line_kws={'linewidth':1, 'color': 'blue'})


    

    
Out[4]:





<seaborn.axisgrid.FacetGrid at 0x107108f90>






    

In [5]:

    

sns.lmplot('total_bill', 'tip', tips, order='4', 
          scatter_kws={'marker':'o', 'color': 'red'},
          line_kws={'linewidth':1, 'color': 'blue'})


    

    
Out[5]:





<seaborn.axisgrid.FacetGrid at 0x11c646490>






    

In [6]:

    

sns.lmplot('total_bill', 'tip', tips, fit_reg=False)


    

    
Out[6]:





<seaborn.axisgrid.FacetGrid at 0x11c67d0d0>






    

In [7]:

    

tips['tip_pect'] = 100* (tips['tip']/tips['total_bill'])


    

In [8]:

    

tips.head()


    

    
Out[8]:






  

    

      

      
total_bill
      
tip
      
sex
      
smoker
      
day
      
time
      
size
      
tip_pect
    
  
  

    

      
0
      
16.99
      
1.01
      
Female
      
No
      
Sun
      
Dinner
      
2
      
5.944673
    
    

      
1
      
10.34
      
1.66
      
Male
      
No
      
Sun
      
Dinner
      
3
      
16.054159
    
    

      
2
      
21.01
      
3.50
      
Male
      
No
      
Sun
      
Dinner
      
3
      
16.658734
    
    

      
3
      
23.68
      
3.31
      
Male
      
No
      
Sun
      
Dinner
      
2
      
13.978041
    
    

      
4
      
24.59
      
3.61
      
Female
      
No
      
Sun
      
Dinner
      
4
      
14.680765
    
  

In [9]:

    

sns.lmplot('size', 'tip_pect', tips)


    

    
Out[9]:





<seaborn.axisgrid.FacetGrid at 0x11cf81050>






    

In [10]:

    

sns.lmplot('size', 'tip_pect', tips, x_jitter=.1)


    

    
Out[10]:





<seaborn.axisgrid.FacetGrid at 0x11d4cfc50>






    

In [11]:

    

sns.lmplot('size', 'tip_pect', tips, x_estimator=np.mean)


    

    
Out[11]:





<seaborn.axisgrid.FacetGrid at 0x11d4cf690>






    

In [12]:

    

sns.lmplot('total_bill', 'tip_pect', tips, hue='sex', markers=['x', 'o'])


    

    
Out[12]:





<seaborn.axisgrid.FacetGrid at 0x11d6e6310>






    

In [13]:

    

sns.lmplot('total_bill', 'tip_pect', tips, hue='day')


    

    
Out[13]:





<seaborn.axisgrid.FacetGrid at 0x11d8abcd0>






    

In [14]:

    

sns.lmplot('total_bill', 'tip_pect', tips, lowess=True, line_kws={'color': 'black'})


    

    
Out[14]:





<seaborn.axisgrid.FacetGrid at 0x11dfd0850>






    

In [15]:

    

sns.regplot('total_bill', 'tip_pect', tips)


    

    
Out[15]:





<matplotlib.axes._subplots.AxesSubplot at 0x11e041950>






    

In [19]:

    

fig, (axis1, axis2) = plt.subplots(1, 2, sharey=True)

sns.regplot('total_bill', 'tip_pect', tips, ax=axis1)
sns.violinplot(x = tips['tip_pect'], y = tips['size'])


    

    
Out[19]:





<matplotlib.axes._subplots.AxesSubplot at 0x11fa80a90>






    

In [ ]: