One single numerical variable
The simplest form of boxplot: analysis of the overall distribution of a single numerical variable in an entire dataset.
# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background (use sns.set_theme() if seaborn version 0.11.0 or above)
sns.set(style="darkgrid")
df = sns.load_dataset('iris')
sns.boxplot(y=df["sepal_length"])
plt.show()
Several numerical variables
If you intend to add more information in a single figure, you can also visualize several numerical variables distributions by setting the data argument and specifying a dataset with several numerical columns.
# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background (use sns.set_theme() if seaborn version 0.11.0 or above)
sns.set(style="darkgrid")
df = sns.load_dataset('iris')
sns.boxplot(data=df.loc[:, ['sepal_length', 'sepal_width']])
plt.show()
One numerical variable and several groups
Depending on your data, you may want to have a better understanding of the distribution of a given variable between two or more groups. You can do so by specifying the 'x' parameter in the boxplot() function.
# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background (use sns.set_theme() if seaborn version 0.11.0 or above)
sns.set(style="darkgrid")
df = sns.load_dataset('iris')
sns.boxplot(x=df["species"], y=df["sepal_length"])
plt.show()
