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 will see how to make Violinplot and plot data points.
Method 1#: Using Inner attributes of violinplot
Example 1: Creating violinplot and use inner attributes. Inner Representation of the datapoints in the violin interior, If point or stick, show each underlying datapoint.
Syntax: seaborn.violinplot( x, y, data, inner = “points”)
Python3
# Python program to illustrate# violinplot using inbuilt data-set# given in seaborn # importing the required moduleimport seaborn # use to set style of background of plotseaborn.set(style = 'whitegrid') # loading data-settip = seaborn.load_dataset('tips')plt.figure(figsize=(4,7))seaborn.violinplot(x ='day', y ='tip', data = tip, inner="points") |
Output:
Example 2:
We see the above implementation, let’s do the same thing for the “stick”. This option show data as lines on violin plot.
Python3
# Python program to illustrate# violinplot using inbuilt data-set# given in seaborn # importing the required moduleimport seaborn # use to set style of background of plotseaborn.set(style = 'whitegrid') # loading data-settip = seaborn.load_dataset('tips')plt.figure(figsize=(4,7))seaborn.violinplot(x ='day', y ='tip', data = tip, inner="stick") |
Output:
Example 3:
Using quartile draw the quartiles of the distribution.
Python3
# Python program to illustrate# violinplot using inbuilt data-set# given in seaborn # importing the required moduleimport seaborn # use to set style of background of plotseaborn.set(style = 'whitegrid') # loading data-settip = seaborn.load_dataset('tips')plt.figure(figsize=(4,7))seaborn.violinplot(x ='day', y ='tip', data = tip, inner="quartile") |
Output:
Method 2#: Using swarmplot().
Using swarmplot we can show the data point inside in a violinplot.
Python3
# Python program to illustrate# violinplot using inbuilt data-set# given in seaborn # importing the required moduleimport seaborn # use to set style of background of plotseaborn.set(style = 'whitegrid') # loading data-settip = seaborn.load_dataset('tips')plt.figure(figsize=(4,7))seaborn.violinplot(x ='day', y ='tip', data = tip)seaborn.swarmplot(x ='day', y ='tip', data = tip,color= "white") |
Output:
