old_contents: import pandas as pd
  import matplotlib.pyplot as plt
  
  
  def read_exp_estimates(path_or_buffer):
      est = pd.read_table(path_or_buffer, index_col=[0, 1])
      est.sort_index(inplace=True)
      return est
  
  
  def read_diffexp_estimates(path_or_buffer):
      est = pd.read_table(path_or_buffer, index_col=0)
      est.sort_index(inplace=True)
      return est
  
  
  def plot_estimate(ylim, map_value=None, credible_interval=None, legend=True):
      if credible_interval is not None:
          ci_lower, ci_upper = credible_interval
          plt.fill([ci_lower, ci_upper, ci_upper, ci_lower], [0, 0, ylim[1], ylim[1]], "red", lw=0, label="95% credible interval", alpha=0.5)
      if map_value is not None:
          plt.vlines([map_value], *ylim, colors="red", linestyles="-", label="expected value")
      if legend:
          plt.legend(loc="best")
      plt.ylim(ylim)
  
new_contents: import pandas as pd
  import matplotlib.pyplot as plt
  
  
  def read_exp_estimates(path_or_buffer):
      est = pd.read_table(path_or_buffer, index_col=[0, 1])
      est.sort_index(inplace=True)
      return est
  
  
  def read_diffexp_estimates(path_or_buffer):
      est = pd.read_table(path_or_buffer, index_col=0)
      est.sort_index(inplace=True)
      return est
  
  
  def plot_estimate(ylim, map_value=None, credible_interval=None, legend=True):
      if credible_interval is not None:
          ci_lower, ci_upper = credible_interval
          plt.fill([ci_lower, ci_upper, ci_upper, ci_lower], [0, 0, ylim[1], ylim[1]], "red", lw=0, label="95% credible interval", alpha=0.5)
      if map_value is not None:
          plt.vlines([map_value], *ylim, colors="red", linestyles="-", label="MAP")
      if legend:
          plt.legend(loc="best")
      plt.ylim(ylim)
  
subject: Fix label.