A violin plot plays a similar activity that is pursued through whisker or box plot do. As it shows several quantitative data across one or more categorical variables. It can be an effective and attractive way to show multiple data at several units. A “wide-form” Data Frame helps to maintain each numeric column which can be plotted on the graph. It is possible to use NumPy or Python objects, but pandas objects are preferable because the associated names will be used to annotate the axes. In this article, we are going to see how to make violinplot with data points.
Syntax: seaborn.violinplot(x=None, y=None, hue=None, data=None, **kwargs)
Parameters:
x, y, hue: Inputs for plotting long-form data.
data: Dataset for plotting.
scale: The method used to scale the width of each violin.Returns: This method returns the Axes object with the plot drawn onto it.
Let’s create first a simple violinpot:
Python3
# Python program to illustrate # violinplot using inbuilt data-set # given in seaborn # importing the required module import seaborn # use to set style of background of plot seaborn.set(style = 'whitegrid') # loading data-set tip = seaborn.load_dataset('tips') seaborn.violinplot(x='day', y='tip', data=tip) |
Output:
Method 1: Using Strip plot.
Python3
# Python program to illustrate # violinplot using inbuilt data-set # given in seaborn # importing the required module import seaborn # use to set style of background of plot seaborn.set(style = 'whitegrid') # loading data-set tip = seaborn.load_dataset('tips') seaborn.violinplot(x ='day', y ='tip', data = tip) seaborn.stripplot(x = "day", y = "tip", color = 'black', data = tip) |
Output:
Method 2: Using swarmplot.
Python3
# Python program to illustrate # violinplot using inbuilt data-set # given in seaborn # importing the required module import seaborn # use to set style of background of plot seaborn.set(style = 'whitegrid') # loading data-set tip = seaborn.load_dataset('tips') seaborn.violinplot(x ='day', y ='tip', data = tip) seaborn.swarmplot(x ='day', y ='tip', data = tip, color = "white") |
Output:
Method 3: using inner point argument.
Python3
# Python program to illustrate # violinplot using inbuilt data-set # given in seaborn # importing the required module import seaborn # use to set style of background of plot seaborn.set(style = 'whitegrid') # loading data-set tip = seaborn.load_dataset('tips') seaborn.violinplot(x ='day', y ='tip', data = tip, inner = "points") |
Output:
