analysis example with pandas and seaborn

pdsns.py

import matplotlib.pylab as plt
import seaborn as sns
import pandas as pd

nosoi = pd.read_csv('roc3.txt', names = ['file','name','score'],na_values = ['None','no_persons_found']  )
nosoi.assign(truth=False) # create a column of "false"

soi = pd.read_csv('roc_known.txt', names = ['file','name','score'], na_values = ['None','no_persons_found'] )
soi.assign(truth=True) # create a column of Truth = True

allface = pd.concat([soi.assign(true=True),nosoi.assign(true=False)])
allface.assign(rank=allface.rank(0)['score']
afr = allface.assign(rank=allface.rank(0,ascending=False)['score'])
sns.lmplot('score','rank',data=afr,fit_reg=False,hue='true')