In [2]:
cars = pd.read_csv("http://web.pdx.edu/~gerbing/data/cars.csv")
In [3]:
cars.columns = ["model","mpg","cyl","engine","hp","weight","accelerate","year","origin"]
In [4]:
cars.head()
Out[4]:
Joint plot¶
It is used to visualise bivariate distribution
In [5]:
sns.jointplot(x='hp', y='mpg', data=cars, size = 8)
Out[5]:
'kind' parameter in joint plot¶
scatter, reg, resid, kde, hex
In [6]:
sns.jointplot(x='hp', y='mpg', data=cars, kind='hex')
Out[6]:
In [7]:
sns.jointplot(x='hp', y='mpg', data=cars, kind='reg')
Out[7]:
pairplot( )¶
In [8]:
sns.pairplot(cars)
Out[8]:
In [9]:
sns.pairplot(cars, hue='origin', kind='reg')
Out[9]: