Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Seaborn helps resolve the two major problems faced by Matplotlib; the problems are ?
- Default Matplotlib parameters
- Working with data frames
As Seaborn compliments and extends Matplotlib, the learning curve is quite gradual. If you know Matplotlib, you are already half-way through Seaborn.
seaborn.jointplot() :
Draw a plot of two variables with bivariate and univariate graphs. This function provides a convenient interface to the ‘JointGrid’ class, with several canned plot kinds. This is intended to be a fairly lightweight wrapper; if you need more flexibility, you should use :class:’JointGrid’ directly.
Syntax: seaborn.jointplot(x, y, data=None, kind=’scatter’, stat_func=None, color=None, height=6, ratio=5, space=0.2, dropna=True, xlim=None, ylim=None, joint_kws=None, marginal_kws=None, annot_kws=None, **kwargs)
Parameters: The description of some main parameters are given below:
x, y: These parameters take Data or names of variables in “data”.
data: (optional) This parameter take DataFrame when “x” and “y” are variable names.
kind: (optional) This parameter take Kind of plot to draw.
color: (optional) This parameter take Color used for the plot elements.
dropna: (optional) This parameter take boolean value, If True, remove observations that are missing from “x” and “y”.
Return: jointgrid object with the plot on it.
Below is the implementation of above method:
Example 1:
# importing required packages import seaborn as sns
import matplotlib.pyplot as plt
# loading dataset data = sns.load_dataset( "attention" )
# draw jointplot with # hex kind sns.jointplot(x = "solutions" , y = "score" ,
kind = "hex" , data = data)
# show the plot plt.show() # This code is contributed # by Deepanshu Rustagi. |
Output:
Example 2:
# importing required packages import seaborn as sns
import matplotlib.pyplot as plt
# loading dataset data = sns.load_dataset( "mpg" )
# draw jointplot with # scatter kind sns.jointplot(x = "mpg" , y = "acceleration" ,
kind = "scatter" , data = data)
# show the plot plt.show() # This code is contributed # by Deepanshu Rustagi. |
Output:
Example 3:
# importing required packages import seaborn as sns
import matplotlib.pyplot as plt
# loading dataset data = sns.load_dataset( "exercise" )
# draw jointplot with # kde kind sns.jointplot(x = "id" , y = "pulse" ,
kind = "kde" , data = data)
# Show the plot plt.show() # This code is contributed # by Deepanshu Rustagi. |
Output:
Example 4:
# importing required packages import seaborn as sns
import matplotlib.pyplot as plt
# loading dataset data = sns.load_dataset( "titanic" )
# draw jointplot with # reg kind sns.jointplot(x = "age" , y = "fare" ,
kind = "reg" , data = data,
dropna = True )
# show the plot plt.show() # This code is contributed # by Deepanshu Rustagi. |
Output: