python - How to fix bar width in this matplotlib plot

Question

Could someone please tell me how to modify this Python code that uses matplotlib such that the width of the bars will stay constant regardless of how many scores are plotted? Thank you in advance!

# data to plot
  n_groups = len(math_scores)
  ###print "im here", math_scores,verbal_scores
  scores_readingwriting = verbal_scores
  scores_math = math_scores

# create plot
  fig, ax = plot.subplots()
  index = np.arange(n_groups)
  bar_width = 0.35
  opacity = 0.8

  rects1 = plot.bar(index, scores_readingwriting, bar_width,
                 alpha=opacity,
                 color='black',
                 label='R/W')

  rects2 = plot.bar(index + bar_width, scores_math, bar_width,
                 alpha=opacity,
                 color='grey',
                 label='Math')

  plot.xlabel('Date',size='14')
  plot.ylabel('Scores',size='14')

  plot.title(str(first_names[i])+' '+str(last_names[i])+"'s History",size='17')
  num=len(scores)
  ###print datesofinterest
  plot.xticks(index + bar_width/2, datesofinterest,size='12')
  plot.yticks(size='12')
  axes = plot.gca()
  axes.set_ylim([200,800])
  plot.legend()

  plot.tight_layout()
  fig.savefig('img'+str(student_ids[i])+'.png')

Answer 1

The bars are the same width! The reason they don't look the same is because you are using this line:

index = np.arange(n_groups)

This will change your x-values and hence the scale of your x-axis. To counteract this effect you can either change the limits of your x-axis, or make the bar width depend on the number of scores, so for example if a width of 0.35 works for 10 scores then if you double the number of scores you would half the bar width (and vice versa). You can see how either changing the axis limits or bar width gives bars that look the same width:

import numpy as np
import matplotlib.pyplot as plt

# make some dummy data
scores_reading = np.random.randint(50,100,10)
scores_math = np.random.randint(50,100,10)

fig = plt.figure(figsize=(16,5))
bar_width = 0.35
index = np.arange(10)

ax1 = fig.add_subplot(1,4,1)
ax1.bar(index, scores_reading, bar_width, fc='b', edgecolor='none')
ax1.bar(index+bar_width, scores_math, bar_width, fc='r', edgecolor='none')
ax1.set_xlim(0,10)
ax1.set_title('Original - 10 scores')

ax2 = fig.add_subplot(1,4,2)
ax2.bar(index[:5], scores_reading[:5], bar_width, fc='b', edgecolor='none')
ax2.bar(index[:5]+bar_width, scores_math[:5], bar_width, fc='r', edgecolor='none')
ax2.set_title('Original - 5 scores')

ax3 = fig.add_subplot(1,4,3)
ax3.bar(index[:5], scores_reading[:5], bar_width, fc='b', edgecolor='none')
ax3.bar(index[:5]+bar_width, scores_math[:5], bar_width, fc='r', edgecolor='none')
ax3.set_xlim(0,10)
ax3.set_title('Changed limit - 5 scores')

ax4 = fig.add_subplot(1,4,4)
ax4.bar(index[:5], scores_reading[:5], bar_width/2., fc='b', edgecolor='none')
ax4.bar(index[:5]+bar_width, scores_math[:5], bar_width/2., fc='r', edgecolor='none')
ax4.set_title('Changed width - 5 scores')

fig.show()