old_contents: #! /usr/bin/env python
  
  # Load Libraries
  import matplotlib as mpl
  mpl.use('SVG')
  import matplotlib.pyplot as plt
  # %matplotlib inline
  
  import seaborn as sns
  sns.set(style='ticks',context='talk')
  import bootstrap_contrast as bs
  
  import pandas as pd
  import numpy as np
  import scipy as sp
  
  # Dummy dataset
  dataset=list()
  for seed in [10,11,12,13,14,15]:
      np.random.seed(seed) # fix the seed so we get the same numbers each time.
      dataset.append(np.random.randn(40))
  df=pd.DataFrame(dataset).T
  cols=['Control','Group1','Group2','Group3','Group4','Group5']
  df.columns=cols
  # Create some upwards/downwards shifts.
  df['Group2']=df['Group2']-0.1
  df['Group3']=df['Group3']+0.2
  df['Group4']=(df['Group4']*1.1)+4
  df['Group5']=(df['Group5']*1.1)-1
  # Add gender column.
  df['Gender']=np.concatenate([np.repeat('Male',20),np.repeat('Female',20)])
  
  f,c=bs.contrastplot(data=df,
                  idx=(('Group1','Group3','Group2'),
                      ('Control','Group4')),
                  color_col='Gender',
                  float_contrast=True,
  
                  show_means='bars',
                  means_width=0.5,
  
                  fig_size=(10,8))
  
  f.savefig('testfig.svg',format='svg')
  
new_contents: #! /usr/bin/env python
  
  # Load Libraries
  import matplotlib as mpl
  mpl.use('SVG')
  import matplotlib.pyplot as plt
  # %matplotlib inline
  
  import seaborn as sns
  sns.set(style='ticks',context='talk')
  import bootstrap_contrast as bsc
  
  import pandas as pd
  import numpy as np
  import scipy as sp
  
  # Dummy dataset
  dataset=list()
  for seed in [10,11,12,13,14,15]:
      np.random.seed(seed) # fix the seed so we get the same numbers each time.
      dataset.append(np.random.randn(40))
  df=pd.DataFrame(dataset).T
  cols=['Control','Group1','Group2','Group3','Group4','Group5']
  df.columns=cols
  # Create some upwards/downwards shifts.
  df['Group2']=df['Group2']-0.1
  df['Group3']=df['Group3']+0.2
  df['Group4']=(df['Group4']*1.1)+4
  df['Group5']=(df['Group5']*1.1)-1
  # Add gender column.
  df['Gender']=np.concatenate([np.repeat('Male',20),np.repeat('Female',20)])
  
  # bsc.__version__
  
  f,c=bsc.contrastplot(data=df,
                       idx=(('Group1','Group3','Group2'),
                            ('Control','Group4')),
                       color_col='Gender',
                       custom_palette={'Male':'blue',
                                       'Female':'red'},
                       float_contrast=True,
                       show_means='bars',
                       means_width=0.5,
                       fig_size=(10,8))
  
  f.savefig('testfig.svg',format='svg')
  
subject: update to include palette checking.