credit-scoring / constants.py
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countries_dict = {
"United-States": 0,
"Cambodia": 1,
"England": 2,
"Puerto-Rico": 3,
"Canada": 4,
"Germany": 5,
"Outlying-US (Guam - USVI - etc.)": 6,
"India": 7,
"Japan": 8,
"Greece": 9,
"South": 10,
"China": 11,
"Cuba": 12,
"Iran": 13,
"Honduras": 14,
"Philippines": 15,
"Italy": 16,
"Poland": 17,
"Jamaica": 18,
"Vietnam": 19,
"Mexico": 20,
"Portugal": 21,
"Ireland": 22,
"France": 23,
"Dominican Republic": 24,
"Laos": 25,
"Ecuador": 26,
"Taiwan": 27,
"Haiti": 28,
"Columbia": 29,
"Hungary": 30,
"Guatemala": 31,
"Nicaragua": 32,
"Scotland": 33,
"Thailand": 34,
"Yugoslavia": 35,
"El Salvador": 36,
"Trinadad & Tobago": 37,
"Peru": 38,
"Hong": 39,
"Holland - Netherlands": 40,
}
relationship_dict = {
"Unmarried": 5,
"Wife": 0,
"Husband": 2,
"Single parent": 1,
"Other dependant": 4,
}
occupation_dict = {
"Prof Specialty": 5,
"Tech Support": 0,
"Craft Repair": 1,
"Other Service": 2,
"Sales": 3,
"Executive Managerial": 4,
"Handlers Cleaners": 6,
"Machine Op Inspect": 7,
"Adm Clerical": 8,
"Farming Fishing": 9,
"Transport Moving": 10,
"Priv House Serv": 11,
"Protective Serv": 12,
"Armed Forces": 13,
}
education_dict = {
"Associate Academic": 5,
"Associate Vocational": 6,
"Prof School": 4,
"Doctorate": 13,
"Masters": 10,
"Bachelors": 0,
"Some College": 1,
"High School Graduate": 3,
"12th Grade": 9,
"11th Grade": 2,
"10th Grade": 12,
"9th Grade": 7,
"7th-8th Grade": 8,
"5th-6th Grade": 14,
"1st-4th Grade": 11,
"Preschool": 15,
}
type_of_work_dict = {
"Private": 0,
"Self Employed Not Incorporated": 1,
"Self Employed Incorporated": 2,
"Federal Government": 3,
"Local Government": 4,
"State Government": 5,
"Without Pay": 6,
"Never Worked": 7,
}
marital_status_dict = {
"Single": 2,
"Married": 0,
"Divorced": 1,
"Widowed": 4,
}