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reformat for python3 #1

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reformat for python3 #1

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13 changes: 1 addition & 12 deletions woe/config.py
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Original file line number Diff line number Diff line change
Expand Up @@ -45,15 +45,4 @@ def change_config_var_dtype(self,var_name,type,inplace_file=True):
if type in ['object','string','int64','uint8','float64','bool1','bool2','dates','category']:
self.variable_type.loc[var_name,'v_type'] = type
else:
raise KeyError,"Invalid dtype specified! "











raise (KeyError,"Invalid dtype specified! ")
14 changes: 7 additions & 7 deletions woe/feature_process.py
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Original file line number Diff line number Diff line change
Expand Up @@ -67,16 +67,16 @@ def change_feature_dtype(df,variable_type):
:return: None
'''
s = 'Changing Feature Dtypes'
print s.center(60,'-')
print (s.center(60,'-'))
for vname in df.columns:
try:
df[vname] = df[vname].astype(variable_type.loc[vname,'v_type'])
print vname,' '*(40-len(vname)),'{0: >10}'.format(variable_type.loc[vname,'v_type'])
print( vname,' '*(40-len(vname)),'{0: >10}'.format(variable_type.loc[vname,'v_type']))
except Exception:
print '[error]',vname
print( '[error]',vname)

s = 'Variable Dtypes Have Been Specified'
print s.center(60,'-')
print (s.center(60,'-'))

return

Expand Down Expand Up @@ -250,7 +250,7 @@ def binning_data_split(df,var,global_bt,global_gt,min_sample,alpha=0.01):
#remove max value and min value in case dataset_r or dataset_l will be null
for point in percent_value[0:len(percent_value)-1]:
# If there is only a sample or a negative sample, skip
if len(set(df[df[var] > point]['target'])) == 1 or len(set(df[df[var] <= point]['target'])) == 1\
if len(set(df[df[var] > point]['target'])) == 1 or len(set(df[df[var] <= point]['target'])) == 1 \
or len(df[df[var] > point]) < min_sample or len(df[df[var] <= point]) < min_sample :
continue

Expand Down Expand Up @@ -399,7 +399,7 @@ def proc_woe_discrete(df,var,global_bt,global_gt,min_sample,alpha=0.01):
:return:
'''
s = 'process discrete variable:'+str(var)
print s.center(60, '-')
print (s.center(60, '-'))
div = DisInfoValue()
div.var_name = var
rdict = {}
Expand Down Expand Up @@ -463,7 +463,7 @@ def proc_woe_continuous(df,var,global_bt,global_gt,min_sample,alpha=0.01):
:return:
'''
s = 'process continuous variable:'+str(var)
print s.center(60, '-')
print( s.center(60, '-'))
iv_tree = binning_data_split(df, var,global_bt,global_gt,min_sample,alpha)

# Traversal tree, get the segmentation point
Expand Down