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Asked: 2026-05-13T15:21:07+00:00

Here’s a plot I made using matplotlib . It uses the bar and scatter

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Here’s a plot I made using matplotlib. It uses the bar and scatter methods from pylab.
I have 3 issues:

How to make the error bars fatter? No API in bar for this that I can see.
How to specify the axes properly?
How to stop the x-axis labels from showing?

The first is most important, as I have no idea. I guess one more thing would be, how to display the image here in SO? I’ve seen it done but don’t know how.

Here is the code:

import numpy as np
from pylab import *

data1 = np.linspace(12,22,7)
data2 = np.random.normal(loc=15,scale=5,size=10)
data3 = [11,12,18,19,20,26,27]
data = [data1,np.abs(data2),data3]

# n = number of groups
def layout(n,r=7):
    s = r**2   # r = radius of each data point
    #layout from 1 to 100
    margin = 5
    spacer = 10
    group_width = (100 - 2*margin - (n-1)*spacer)*1.0/n
    dot_width = r
    bar_width = group_width - dot_width
    current = margin
    rL = list()
    for i in range(n):
        rL.append(current)        # x for point
        rL.append(current + 3)    # x for bar
        current += group_width + spacer
    return s, bar_width, rL   

s, w, xlocs = layout(len(data))
for group in data:
    x = xlocs.pop(0)
    for e in group:
        scatter(x,e,s=s,color='k')
    m = np.mean(group)
    e = np.std(group)
    x = xlocs.pop(0)
    o = bar(x,m,width=w,color='0.6',
        yerr=e, ecolor='k')

show()

alt text http://img210.imageshack.us/img210/8503/screenshot20100206at703.png

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1 Answer

  1. Editorial Team

    The error bars are drawn with the errorbar method from within the bar method. It accepts an elinewidth argument but it doesn’t look like you can pass it through the bar method call. I would just draw them manually.

    o, = bar(x,m,width=w,color='0.6', yerr=None) # note the comma after the o
eBarX = o.get_x()+o.get_width()/2.0
eBarY = o.get_height()
errorbar(eBarX,eBarY,e,capsize=7,elinewidth=6,ecolor='k')

    To turn the XAxis off use this before you call show:

    axes().xaxis.set_visible(False)

    These changes make your plot look like this:
    alt text http://img690.imageshack.us/img690/5141/testfs.png

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