In [6]:

    

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline


    

In [7]:

    

info = {'VAR': ['1,25(OH)D3', 'Site', 'Race'],
        'ES_IND': [0.06705342, 0.02470355, 0.02282282],
        'ES_CUL': [0.02674177, 0.02175614, 0.01713566]}
dat = pd.DataFrame(info, columns=['VAR', 'ES_IND', 'ES_CUL'])


    

In [8]:

    

dat


    

    
Out[8]:







  

    

      

      
VAR
      
ES_IND
      
ES_CUL
    
  
  

    

      
0
      
1,25(OH)D3
      
0.067053
      
0.026742
    
    

      
1
      
Site
      
0.024704
      
0.021756
    
    

      
2
      
Race
      
0.022823
      
0.017136
    
  

In [9]:

    

sns.set(style="whitegrid")

# Plot cumulative effect size
sns.set_color_codes("muted")
ax = sns.barplot(x="ES_CUL", y="VAR", data=dat,
            label="Dependent", color="b")
ax.set_xlabel('Effect Size', fontsize=16)
ax.set_ylabel('Non-redundant Covariates', fontsize=16)

ax = ax.get_figure()
ax.tight_layout()
ax.savefig('../figures/RDA_Shannon_alpha.pdf')
ax.savefig('../figures/RDA_Shannon_alpha.png')


    

In [ ]: