I have values with extreme outliers and want to visualize that. But the box plot doesn't seem a good choice for my data as you can see here.
Most of the values are less than 50,000. But some them are over 1 million. .
What type of graph/figure is a good choice for data like this?
Here is an MWE creating that data
#!/usr/bin/env python3
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
np.random.seed(0)
sns.set_theme()
# 40.000 values from 500 to 10.000
vals = np.random.choice(range(500, 10000), 40000, replace=True)
# 2.000 values from 20.000 to 100.000
vals = np.append(vals, np.random.choice(range(20000, 100000), 2000, replace=True))
# 300 values (extrem outliners) from 1 to 4 Mio.
vals = np.append(vals, np.random.choice(range(1000000, 4000000), 300, replace=True))
sns.boxplot(vals)
plt.show()
EDIT: The example data is not contrived. This distribution is very near to a real data set.
EDIT 2: The values are currencies (in €); costs. And of course I will dive deeper into the data to find out why some persons cause so much more costs then others.