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import pandas as pd

import numpy as np

from pandas import DataFrame

import scipy

my_series = pd.Series([1,2,2,3,3,3, "fred", 1.8, 1.8])

k1 = my_series.value_counts()

k2 = DataFrame(k1)

#print k2.to_html()

#.value_counts()

#df = pd.DataFrame({'a' : [1, 2, 3, 4, 5], 'b' : ['yes', 'no', 'yes', 'no', 'absent']})

#df['b'] = pd.Categorical.from_array(df.b).labels

#print df['b']

df = pd.read_csv("E:/Default_On_Payment_CHAID.csv")

fit = pd.crosstab(df.Status_Checking_Acc,df.Default_On_Payment)

#print type(fit)

#scipy.stats.chi2_contingency(fit)

#chi2_contingency(data)

s = scipy.stats.chi2_contingency(fit)

scipy.stats.chi2_contingency

#if(s[1]<0.05):

#print s[1]

chi_key= list()

#chi_key.append()

var = "upl1"

if(not(var=='upl')):

print "hi"