How do you create a boxplot in seaborn with pre-calculated values for mean, median, percentile, etc?

I would like to create a boxplot in seaborn or matplotlib where I can manually enter the values for a boxplot instead of having those values calculated from a data set.

I am trying to compare actual data to target values so I'd like to show those targets as a box plot and then overlay a swarmplot of actual data points. For example. I have a data frame with a different compensation classes with these desired targets:

    Grade                                GN23
    MINIMUM (Start of 1st Quartile)     94603
    1st Q (End of 1st Quartile)        113524
    MIDPOINT (End of 2nd Quartile)     132444
    3rd Q (End of 3rd Quartile)        151365
    MAXIMUM (End of 4th Quartile)      170285

I'd like to create boxplot with those parameters. Is that possible?

Solution

You can probably just input those values as the data like this:

import matplotlib.pyplot as plt
import seaborn as sns

sns.boxplot(data=[94603, 113524, 132444, 151365, 170285])

plt.show()

Since there are only 5 values, the first one would be the minimum, the second one would be Q1, etc.