title: How to plot barchart with errorbars when standard deviation is more than mean in python?
body: <p>Suppose I have three randomly generated normal distribution data of the form:</p>
  
  <pre><code>df = pd.DataFrame([np.random.normal(32000,200000,3650), 
                     np.random.normal(43000,100000,3650), 
                     np.random.normal(43500,140000,3650), 
                     np.random.normal(48000,70000,3650)], 
                    index=[1992,1993,1994,1995])
  </code></pre>
  
  <p>I have to plot barcharts with errorbars at 95% confidence interval, so I use the following code: </p>
  
  <pre><code>Mean = df.mean(axis=1)
  STD = df.std(axis=1)
  Year = df.index.tolist()
  x_pos = np.arange(len(Year))
  fig, axs = plt.subplots()
  axs.bar(x_pos, Mean, yerr=2*STD, width=0.3, align='center',
          alpha=0.5, ecolor='black', capsize=10)
  axs.set_xticks(x_pos)
  axs.set_xticklabels(Year)
  </code></pre>
  
  <p>But, I get the following graph:</p>
  
  <p><img src="https://i.stack.imgur.com/x57lv.png" alt="I get the following graph"></p>
  
  <p>How can I have the bars till the bottom ?</p>