Tornado Chart using broken_barh()

I have found this example of how to create a tornado plot using a broken barchart on matplotlib (copy and pasted below).
My question is if anyone knows how to make each variable (cancers in this case) a different color?

using the “facecolor=()” command can be used to set different colors within the same bar, but not to irrerate through variables and set each one as a different color.
(e.g. https://matplotlib.org/3.1.0/gallery/lines_bars_and_markers/broken_barh.html)

thanks!

EXAMPLE:

And here is a modified example a little closer visually

# tornado chart example; inspired by
# http://www.nytimes.com/imagepages/2007/07/29/health/29cancer.graph.web.html 27
# and sample code from Tony Yu
import numpy as np
import matplotlib.pyplot as plt

cancers = [
    'Kidney cancer',
    'Bladder cancer',
    'Esophageal cancer',
    'Ovarian cancer',
    'Liver cancer',
    "Non-Hodgkin's\nlymphoma",
    'Leukemia',
    'Prostate cancer',
    'Pancreatic cancer',
    'Breast cancer',
    'Colorectal cancer',
    'Lung cancer',
    ]

num_cancers = len(cancers)

# generate some random data for the graphs (TODO; put real data here)
new_cases_men = np.random.uniform(low=20e3, high=200e3, size=num_cancers)
new_cases_women = np.random.uniform(low=20e3, high=200e3, size=num_cancers)
deaths_women = np.random.rand(num_cancers)*new_cases_women
deaths_men = np.random.rand(num_cancers)*new_cases_men

# force these values where the labels happen to make sure they are
# positioned nicely
new_cases_men[-1] = 120e3
new_cases_men[-2] = 55e3
deaths_men[-1] = 80e3

# bars centered on the y axis
pos = np.arange(num_cancers) + .5

# make the left and right axes for women and men
fig = plt.figure(facecolor='white', edgecolor='none')
ax_women = fig.add_axes([0.05, 0.1, 0.35, 0.8])
ax_men = fig.add_axes([0.6, 0.1, 0.35, 0.8])

ax_men.set_xticks(np.arange(50e3, 201e3, 50e3))
ax_women.set_xticks(np.arange(50e3, 201e3, 50e3))

# turn off the axes spines except on the inside y-axis
for loc, spine in ax_women.spines.iteritems():
    if loc!='right':
        spine.set_color('none') # don't draw spine

for loc, spine in ax_men.spines.iteritems():
    if loc!='left':
        spine.set_color('none') # don't draw spine

# just tick on the top
ax_women.xaxis.set_ticks_position('top')
ax_men.xaxis.set_ticks_position('top')

# make the women's graphs
ax_women.barh(pos, new_cases_women, align='center',
facecolor='#DBE3C2', edgecolor='None')
ax_women.barh(pos, deaths_women, align='center', facecolor='#7E895F',
height=0.5, edgecolor='None')
ax_women.set_yticks([])
ax_women.invert_xaxis()

# make the men's graphs
ax_men.barh(pos, new_cases_men, align='center', facecolor='#D8E2E1',
edgecolor='None')
ax_men.barh(pos, deaths_men, align='center', facecolor='#6D7D72',
height=0.5, edgecolor='None')
ax_men.set_yticks([])

# we want the cancer labels to be centered in the fig coord system and
# centered w/ respect to the bars so we use a custom transform
import matplotlib.transforms as transforms
transform = transforms.blended_transform_factory(
    fig.transFigure, ax_men.transData)
for i, label in enumerate(cancers):
    ax_men.text(0.5, i+0.5, label, ha='center', va='center',
transform=transform)

# the axes titles are in axes coords, so x=0, y=1.025 is on the left
# side of the axes, just above, x=1.0, y=1.025 is the right side of the
# axes, just above
ax_men.set_title('MEN', x=0.0, y=1.025, fontsize=12)
ax_women.set_title('WOMEN', x=1.0, y=1.025, fontsize=12)

# the fig suptile is in fig coords, so 0.98 is the far right; we right
align the text
fig.suptitle('July 29, 2007', x=0.98, ha='right')

# now add the annotations
ax_men.annotate('New Cases', xy=(0.95*new_cases_men[-1], num_cancers-0.5),
                xycoords='data',
                xytext=(20, 0), textcoords='offset points',
                size=12,
                va='center',
                arrowprops=dict(arrowstyle="->"),
                )

# a curved arrow for the deaths annotation
ax_men.annotate('Deaths', xy=(0.95*deaths_men[-1], num_cancers-0.5),
                xycoords='data',
                xytext=(40, -20), textcoords='offset points',
                size=12,
                va='center',
                arrowprops=dict(arrowstyle="->",

connectionstyle="angle,angleA=0,angleB=90,rad=3"),

                )

plt.show()

[Edited by @tacaswell to add markup]