pyplot/matplotlib Bar chart with fill color depending on value

Question

I want to produce in python with matplotlib/pyplot

• a bar chart with a fill depending on the value.
• legend color bar

while keeping module dependencies at a minimum.

Is there something simpler than:

import matplotlib.pyplot as plt

def color_gradient ( val, beg_rgb, end_rgb, val_min = 0, val_max = 1):
    val_scale = (1.0 * val - val_min) / (val_max - val_min)
    return ( beg_rgb[0] + val_scale * (end_rgb[0] - beg_rgb[0]),
             beg_rgb[1] + val_scale * (end_rgb[1] - beg_rgb[1]),
             beg_rgb[2] + val_scale * (end_rgb[2] - beg_rgb[2]))

# -----------------------------------------------
x_lbls = [ "09:00", "09:15", "10:10"]
y_vals = [       7,       9,       5]

plt_idx = np.arange( len( x_lbls))
bar_wd  = 0.35

grad_beg, grad_end = ( 0.5, 0.5, 0.5), (1, 1, 0)
col_list = [ color_gradient( val,
                             grad_beg,
                             grad_end,
                             min( y_vals),
                             max( y_vals)) for val in y_vals]

plt.bar( plt_idx, y_vals, color = col_list)
plt.xticks( plt_idx + bar_wd, x_lbls)
plt.show()

this is still missing the legend color bar

my solution in R with ggplot would be:

library(ggplot2)
df = data.frame( time = 1:10, vals = abs(rnorm( n = 10)))
ggplot( df, aes( x = time, y = vals, fill = vals)) + 
  geom_bar(stat = "identity") + 
  scale_fill_gradient(low="#888888",high="#FFFF00")

and produces the desired output:

Answer 1

You can use Normalize and ScalarMappable without plotting a scatter. For example:

import matplotlib mpl
import matplotlib.pyplot as plt
from matplotlib import cm

f,(ax1,ax2) = plt.subplots(2)

#ax1 --> plot here your bar chart

norm = mpl.colors.Normalize(vmin=0, vmax=1)

mpl.colorbar.ColorbarBase(ax2, cmap=cm.RdBu,
                                norm=norm,
                                orientation='horizontal')

Finally, add the desired format to the colorbar.

Answer 2

I couldn't figure out how to get the colorbar to work without plotting something else and then clearing it, so it's not the most elegant solution.

import matplotlib.pyplot as plt
from matplotlib import cm
import numpy as np

y = np.array([1, 4, 3, 2, 7, 11])
colors = cm.hsv(y / float(max(y)))
plot = plt.scatter(y, y, c = y, cmap = 'hsv')
plt.clf()
plt.colorbar(plot)
plt.bar(range(len(y)), y, color = colors)
plt.show()