Violin Plot in Seaborn is used to draw a combination of boxplot and kernel density estimate. The seaborn.violinplot() is used for this. Set explicit order using the order parameter of the violinplot().
Let’s say the following is our dataset in the form of a CSV file − Cricketers.csv
At first, import the required libraries −
import seaborn as sb import pandas as pd import matplotlib.pyplot as plt
Load data from a CSV file into a Pandas DataFrame −
dataFrame = pd.read_csv("C:\\Users\\amit_\\Desktop\\Cricketers.csv")
Plotting violin plot with Role and Age. Control order by passing an explicit order i.e. ordering on the basis of "Role".
sb.violinplot(x = 'Role', y = "Age", order=["Batsman", "Bowler"], data = dataFrame)
Example
Following is the code
import seaborn as sb import pandas as pd import matplotlib.pyplot as plt # Load data from a CSV file into a Pandas DataFrame dataFrame = pd.read_csv("C:\\Users\\amit_\\Desktop\\Cricketers.csv") # plotting violin plot with Role and Age # Control order by passing an explicit order i.e. ordering on the basis of "Role" # ordering set using the order parameter sb.violinplot(x = 'Role', y = "Age", order=["Batsman", "Bowler"], data = dataFrame) # display plt.show()
Output
This will produce the following output −