#50 Basic violinplot and input formats

This post aims to describe how to realize a basic violinplot. It explains how your input must be formated and which function of seaborn you need to use. Three input formats exist to draw a violinplot:

One numerical variable only

If you have only one numerical variable, you probably better have to make an histogram or a density plot. But you can still use the violinplot function to describe the distribution of this variable, as follow:

# library & dataset
import seaborn as sns
df = sns.load_dataset('iris')

# Make boxplot for one group only
sns.violinplot( y=df["sepal_length"] )
#sns.plt.show()

One variable and several groups

Usually, violinplots are made on the same situation than boxplots: when you have one numerical variable and several groups. It allows to compare values from one group to another. Usually you have 2 columns: one gives the value of the variable, the other the group:

# library & dataset
import seaborn as sns
df = sns.load_dataset('iris')

# plot
sns.violinplot( x=df["species"], y=df["sepal_length"] )
#sns.plt.show()

Several variables

Violinplot are also useful to compare several variables.  In the iris dataset, we can compare the first 2 numerical variables:

# library & dataset
import seaborn as sns
df = sns.load_dataset('iris')

# plot
sns.violinplot(data=df.ix[:,0:2])
#sns.plt.show()