text: import matplotlib.pyplot as plt
  import string
  def dataframe_stats(desired_feature,statistics, countries, dtype, datasetList):
      columns = ["views","likes","dislikes","comment_count"]
      ca_graph = datasetList[0].describe(include = [dtype])[columns]
      usa_graph = datasetList[1].describe(include = [dtype])[columns]
      gb_graph = datasetList[2].describe(include = [dtype])[columns]
      fr_graph = datasetList[3].describe(include = [dtype])[columns]
      de_graph = datasetList[4].describe(include = [dtype])[columns]
  
      temp_list = [ca_graph, usa_graph, gb_graph, fr_graph, de_graph]
      means = []
      std = []
      
      for stats in statistics:
          for i in range(0,5):
              if stats is "mean":
                  means.append(temp_list[i].loc[stats,desired_feature])
              else:
                  std.append(temp_list[i].loc[stats,desired_feature])
                  
      max_ofMeans = max(means)
      max_ofStd = max(std)
      
      maxIndex_means = means.index(max_ofMeans)
      maxIndex_std = std.index(max_ofStd)
      
      li = list(ca_graph.columns)
      
      indexes_ofRegion = range(0,5)
      for stat in statistics:
          
          plt.xticks(indexes_ofRegion, countries )
          plt.title("%s of Youtube %s for each Country" % (stat.upper(), string.capwords(desired_feature) ))
          if stat is "mean":
              visualization = plt.bar(indexes_ofRegion, means, color='blue')
              visualization[maxIndex_means].set_color('r')
          else:
              visualization = plt.bar(indexes_ofRegion,std,color='blue')
              visualization[maxIndex_std].set_color('r')
          plt.show()
  