Bar graph color dependent on value in Matplotlib

Question

I've created a bar graph, as follows:

from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
import matplotlib.pyplot as plt

#self.Data1 is an array containing all the data points, inherited from a separate class

DataSet = range(46)
self.Figure1 = plt.figure()
self.Figure1.patch.set_alpha(0)
self.Canvas1 = FigureCanvas(self.Figure1)

#Add canvas to pre-existing Widget#
self.Widget.addWidget(self.Canvas1)
self.Ax1 = plt.subplot(1, 1, 1, axisbg='black')
self.Ax1.bar(DataSet, self.Data1, width=1, color='r')
self.Ax1.tick_params(axis='y', colors='white')
plt.title('GRAPH TITLE', color='w', fontsize=30, fontname='Sans Serif', fontweight='bold')
self.Figure1.tight_layout()

This is working nicely, producing the following graph:

What I'd like to do is set the bar color depending on the value. Ie blue if the value is positive and red if the value is negative. What's the easiest way to do so? Do I need to create a Color Map?

Answer 1

You can also specify an arraylike as the color kwarg as such:

x = np.arange(1,100)
y = np.sin(np.arange(1,100))
colors = np.array([(1,0,0)]*len(y))
colors[y >= 0] = (0,0,1)
plt.bar(x,y,color = colors)

So long as colors is the same length as y, you can specify the colors however you want.

Or for something a little fancier:

x = np.arange(1,100)
y = np.sin(3*np.arange(1,100))
colors = np.array([(1,0,0)]*len(y))
colors[y >= 0] = (0,0,1)
mult = np.reshape(np.repeat(np.abs(y)/np.max(np.abs(y)),3),(len(y),3))
colors =  mult*colors
plt.bar(x,y,color = colors)

Answer 2

This is by far not the best solution in terms of reusability and/or scalability, but if you only want to have red bars for negative numbers and blue bars for positive number, you can call the barplot twice, by filtering the values before hand. Here is a minimal example of what I mean:

import numpy as np
import matplotlib.pylab as pl

array = np.random.randn(100)
greater_than_zero = array > 0
lesser_than_zero = array < 0
cax = pl.subplot(111)
cax.bar(np.arange(len(array))[greater_than_zero], array[greater_than_zero], color='b')
cax.bar(np.arange(len(array))[lesser_than_zero], array[lesser_than_zero], color='r')

result http://img11.hostingpics.net/pics/547091download.png