title: Plot curves instead of bar plot using python
body: <p>I have a dataframe <code>df</code> that I use to produce two bar plots on the same x-axis. Instead of displaying these values as bar plots, I'd like a curve that fits the shape of the bars. I.e. it should sort of be like a gaussian or normal distribution fit, but I want to keep the x-axis and y-axis the same, and not show frequency. I also need the fit to start at 0 and be for any negative values. How can I do this? I imagine the scipy <code>curve_fit</code> function might be useful or <code>sns.distplot</code>?</p>
  
  <pre><code>df
      size    a           b
      0       0.000000    6.20405
      1       0.000000    9.262046
      2       2.51524     14.28944
      3       6.750392    12.756672
      4       9.893210    9.733124
      5       10.302983   6.690388
      6       11.302383   4.86942
      7       8.024279    8.32051
      8       4.39434     7.228450
      9       2.05516     3.767661
  
  x = df['a']
  y = df['b']
  
  n = 10
  
  fig, ax = plt.subplots(1)
  
  bar_width = 0.4  # default: 0.8
  bar_locations = np.arange(n)
  
  ax.bar(bar_locations, x, bar_width)
  ax.bar(bar_locations - bar_width, y, bar_width, color='r') 
  
  fig.show()
  </code></pre>
  
  <p><strong>Update:</strong></p>
  
  <pre><code>fig, ax = plt.subplots()
  for a in [x, y]:
      sns.distplot(a, bins=range(1, 25, 1), ax=ax, kde=True, fit=stats.gamma)
  </code></pre>
  
  <p>How do I clean this figure to a) force the kde fit to not be for any negative numbers (the data start at 0!) and b) remove the black lines and green/blue bars?</p>
  
  <p><a href="https://i.stack.imgur.com/W7Zux.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/W7Zux.png" alt="enter image description here"></a></p>