bug fix with documentation
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@ -39,10 +39,10 @@ The framework will depend on pandas and numpy (for now). Below is a basic sample
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import numpy as np
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import pandas as pd
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from pandas_risk import *
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import risk
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mydf = pd.DataFrame({"x":np.random.choice( np.random.randint(1,10),50),"y":np.random.choice( np.random.randint(1,10),50),"z":np.random.choice( np.random.randint(1,10),50),"r":np.random.choice( np.random.randint(1,10),50) })
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print mydf.risk.evaluate()
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print (mydf.risk.evaluate())
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@ -52,7 +52,7 @@ The framework will depend on pandas and numpy (for now). Below is a basic sample
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# - Insure the fields are identical in both sample and population
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#
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pop = pd.DataFrame({"x":np.random.choice( np.random.randint(1,10),150),"y":np.random.choice( np.random.randint(1,10),150) ,"z":np.random.choice( np.random.randint(1,10),150),"r":np.random.choice( np.random.randint(1,10),150)})
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mydf.risk.evaluate(pop=pop)
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print (mydf.risk.evaluate(pop=pop))
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@TODO:
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@ -43,10 +43,10 @@ The framework will depend on pandas and numpy (for now). Below is a basic sample
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import numpy as np
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import pandas as pd
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from pandas_risk import *
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import risk
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mydf = pd.DataFrame({"x":np.random.choice( np.random.randint(1,10),50),"y":np.random.choice( np.random.randint(1,10),50),"z":np.random.choice( np.random.randint(1,10),50),"r":np.random.choice( np.random.randint(1,10),50) })
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print mydf.risk.evaluate()
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print (mydf.risk.evaluate())
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@ -56,7 +56,7 @@ The framework will depend on pandas and numpy (for now). Below is a basic sample
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# - Insure the fields are identical in both sample and population
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#
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pop = pd.DataFrame({"x":np.random.choice( np.random.randint(1,10),150),"y":np.random.choice( np.random.randint(1,10),150) ,"z":np.random.choice( np.random.randint(1,10),150),"r":np.random.choice( np.random.randint(1,10),150)})
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mydf.risk.evaluate(pop=pop)
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print (mydf.risk.evaluate(pop=pop))
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@TODO:
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