title: Plot two histograms on the same graph and have their columns sum to 100
body: <p>I have two sets of different sizes that I'd like to plot on the same histogram. However, since one set has ~330,000 values and the other has about ~16,000 values, their frequency histograms are hard to compare. I'd like to plot a histogram comparing the two sets such that the y-axis is the % of occurrences in that bin. My code below gets close to this, except that rather than having the individual bin values sum to 1.0, the integral of the histogram sums to 1.0 (this is because of the normed=True parameter). </p>
  
  <p>How can I achieve my goal? I've already tried manually calculating the % frequency and using plt.bar() but rather than overlaying the plots, the plots are compared side by side. I want to keep the effect of having the alpha=0.5</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  import matplotlib.pyplot as plt
  
  if plt.get_fignums():
      plt.close('all')
  
  electric = pd.read_csv('electric.tsv', sep='\t')
  gas = pd.read_csv('gas.tsv', sep='\t')
  
  electric_df = pd.DataFrame(electric)
  gas_df = pd.DataFrame(ngma_nonheat)
  
  electric = electric_df['avg_daily']*30
  gas = gas_df['avg_daily']*30
  
  
  ## Create a plot for NGMA gas usage
  plt.figure("Usage Comparison")
  
  weights_electric = np.ones_like(electric)/float(len(electric))
  weights_gas = np.ones_like(gas)/float(len(gas))
  
  bins=np.linspace(0, 200, num=50)
  
  n, bins, rectangles = plt.hist(electric, bins, alpha=0.5, label='electric usage', normed=True, weights=weights_electric)
  plt.hist(gas, bins, alpha=0.5, label='gas usage', normed=True, weights=weights_gas)
  
  plt.legend(loc='upper right')
  plt.xlabel('Average 30 day use in therms')
  plt.ylabel('% of customers')
  plt.title('NGMA Customer Usage Comparison')
  plt.show()
  </code></pre>