Matplotlib boxplot using precalculated (summary) statistics

Question

I need to do a boxplot (in Python and matplotlib) but I do not have the original \"raw\" data. What I have are precalculated values for max, min, mean, median and IQR (norma

Answer 1

Thanks to the comment of @tacaswell I was able to find the required documentation and come up with an example using Matplotlib 1.4.3. However, this example does not automatically scale the figure to the correct size.

import matplotlib.pyplot as plt

item = {}

item["label"] = 'box' # not required
item["mean"] = 5 # not required
item["med"] = 5.5
item["q1"] = 3.5
item["q3"] = 7.5
#item["cilo"] = 5.3 # not required
#item["cihi"] = 5.7 # not required
item["whislo"] = 2.0 # required
item["whishi"] = 8.0 # required
item["fliers"] = [] # required if showfliers=True

stats = [item]

fig, axes = plt.subplots(1, 1)
axes.bxp(stats)
axes.set_title('Default')
y_axis = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
y_values = ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"]
plt.yticks(y_axis, y_values)

Relevant links to the documentation:

• Axes.bxp() function
• boxplot_stats datastructure
• other examples using Axes.bxp