Upload 12 files
Browse files- new_data/german-fewshot-2.csv +151 -0
- new_data/german-fewshot-4.csv +301 -0
- new_data/german-fewshot-6.csv +451 -0
- new_data/german-fewshot-8.csv +601 -0
- new_data/ghana-fewshot-2.csv +121 -0
- new_data/ghana-fewshot-4.csv +241 -0
- new_data/ghana-fewshot-6.csv +361 -0
- new_data/ghana-fewshot-8.csv +481 -0
- new_data/loan_pred-fewshot-2.csv +97 -0
- new_data/loan_pred-fewshot-4.csv +193 -0
- new_data/loan_pred-fewshot-6.csv +289 -0
- new_data/loan_pred-fewshot-8.csv +385 -0
new_data/german-fewshot-2.csv
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Unnamed: 0,gender,checking_status,duration,credit_history,purpose,credit_amount,savings_status,employment,installment_commitment,other_parties,residence_since,property_magnitude,age,other_payment_plans,housing,existing_credits,job,num_dependents,own_telephone,foreign_worker,class,great,list,text,html,latex,json,LIFT
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0,male,'<0',60,'delayed previously',business,6836,'<100','>=7',3,none,4,'no known property',63,none,own,2,skilled,1,yes,yes,bad,"gender is male, checking_status is '<0', duration is 60, credit_history is 'delayed previously', purpose is business, credit_amount is 6836, savings_status is '<100', employment is '>=7', installment_commitment is 3, other_parties is none, residence_since is 4, property_magnitude is 'no known property', age is 63, other_payment_plans is none, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : male
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- checking_status : '<0'
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- duration : 60
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- credit_history : 'delayed previously'
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- purpose : business
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- credit_amount : 6836
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- savings_status : '<100'
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- employment : '>=7'
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- installment_commitment : 3
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- other_parties : none
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- residence_since : 4
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- property_magnitude : 'no known property'
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- age : 63
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- other_payment_plans : none
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- housing : own
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- existing_credits : 2
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- job : skilled
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- num_dependents : 1
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- own_telephone : yes
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- foreign_worker : yes",The gender is male. The checking_status is '<0'. The duration is 60. The credit_history is 'delayed previously'. The purpose is business. The credit_amount is 6836. The savings_status is '<100'. The employment is '>=7'. The installment_commitment is 3. The other_parties is none. The residence_since is 4. The property_magnitude is 'no known property'. The age is 63. The other_payment_plans is none. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
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<thead>
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<tr style=""text-align: right;"">
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<th></th>
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<th>gender</th>
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<th>checking_status</th>
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<th>duration</th>
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<th>credit_history</th>
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<th>purpose</th>
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<th>credit_amount</th>
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<th>savings_status</th>
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<th>employment</th>
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<th>installment_commitment</th>
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<th>other_parties</th>
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<th>residence_since</th>
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<th>property_magnitude</th>
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<th>age</th>
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<th>other_payment_plans</th>
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<th>housing</th>
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<th>existing_credits</th>
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<th>job</th>
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<th>num_dependents</th>
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<th>own_telephone</th>
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<th>foreign_worker</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<th>0</th>
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<td>male</td>
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<td>'<0'</td>
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<td>60</td>
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<td>'delayed previously'</td>
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<td>business</td>
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<td>6836</td>
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<td>'<100'</td>
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<td>'>=7'</td>
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<td>3</td>
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<td>none</td>
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<td>4</td>
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<td>'no known property'</td>
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<td>63</td>
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<td>none</td>
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<td>own</td>
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<td>2</td>
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<td>skilled</td>
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<td>1</td>
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<td>yes</td>
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<td>yes</td>
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</tr>
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</tbody>
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</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
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& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
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0 & male & '<0' & 60 & 'delayed previously' & business & 6836 & '<100' & '>=7' & 3 & none & 4 & 'no known property' & 63 & none & own & 2 & skilled & 1 & yes & yes \\
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\end{tabular}
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","{'age': 63, 'checking_status': ""'<0'"", 'credit_amount': 6836, 'credit_history': ""'delayed previously'"", 'duration': 60, 'employment': ""'>=7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'own', 'installment_commitment': 3, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': ""'no known property'"", 'purpose': 'business', 'residence_since': 4, 'savings_status': ""'<100'""}",A 63-year-old male German Foreigner is applying for a loan of 6836 credits for 60 months for business purposes. He has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. He has delayed paying back credits received from this bank in the past. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 3%. He has no other installment plans and 2 credits at this bank. He is employed for more than seven years. He has lived in a self-owned house for 4 years. He owns no known property. He owns a telephone and has 1 person that he is liable to provide maintenance for.
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3,female,'no checking',21,'no credits/all paid','new car',5003,'no known savings','1<=X<4',1,none,4,'life insurance',29,bank,own,2,skilled,1,yes,yes,bad,"gender is female, checking_status is 'no checking', duration is 21, credit_history is 'no credits/all paid', purpose is 'new car', credit_amount is 5003, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 1, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 29, other_payment_plans is bank, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : female
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- checking_status : 'no checking'
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- duration : 21
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- credit_history : 'no credits/all paid'
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- purpose : 'new car'
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- credit_amount : 5003
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- savings_status : 'no known savings'
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| 84 |
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- employment : '1<=X<4'
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- installment_commitment : 1
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- other_parties : none
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- residence_since : 4
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- property_magnitude : 'life insurance'
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- age : 29
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- other_payment_plans : bank
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| 91 |
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- housing : own
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- existing_credits : 2
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- job : skilled
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- num_dependents : 1
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- own_telephone : yes
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- foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 21. The credit_history is 'no credits/all paid'. The purpose is 'new car'. The credit_amount is 5003. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 1. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 29. The other_payment_plans is bank. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
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<thead>
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<tr style=""text-align: right;"">
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<th></th>
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<th>gender</th>
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| 101 |
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<th>checking_status</th>
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| 102 |
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<th>duration</th>
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| 103 |
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<th>credit_history</th>
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| 104 |
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<th>purpose</th>
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| 105 |
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<th>credit_amount</th>
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| 106 |
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<th>savings_status</th>
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| 107 |
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<th>employment</th>
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| 108 |
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<th>installment_commitment</th>
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| 109 |
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<th>other_parties</th>
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| 110 |
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<th>residence_since</th>
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| 111 |
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<th>property_magnitude</th>
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| 112 |
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<th>age</th>
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| 113 |
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<th>other_payment_plans</th>
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| 114 |
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<th>housing</th>
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| 115 |
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<th>existing_credits</th>
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| 116 |
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<th>job</th>
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| 117 |
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<th>num_dependents</th>
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| 118 |
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<th>own_telephone</th>
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| 119 |
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<th>foreign_worker</th>
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| 120 |
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</tr>
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| 121 |
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</thead>
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| 122 |
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<tbody>
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| 123 |
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<tr>
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| 124 |
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<th>0</th>
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| 125 |
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<td>female</td>
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| 126 |
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<td>'no checking'</td>
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| 127 |
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<td>21</td>
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| 128 |
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<td>'no credits/all paid'</td>
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| 129 |
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<td>'new car'</td>
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| 130 |
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<td>5003</td>
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| 131 |
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<td>'no known savings'</td>
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| 132 |
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<td>'1<=X<4'</td>
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| 133 |
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<td>1</td>
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| 134 |
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<td>none</td>
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| 135 |
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<td>4</td>
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| 136 |
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<td>'life insurance'</td>
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| 137 |
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<td>29</td>
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| 138 |
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<td>bank</td>
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| 139 |
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<td>own</td>
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| 140 |
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<td>2</td>
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| 141 |
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<td>skilled</td>
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| 142 |
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<td>1</td>
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| 143 |
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<td>yes</td>
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| 144 |
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<td>yes</td>
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| 145 |
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</tr>
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| 146 |
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</tbody>
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| 147 |
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</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
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& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
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0 & female & 'no checking' & 21 & 'no credits/all paid' & 'new car' & 5003 & 'no known savings' & '1<=X<4' & 1 & none & 4 & 'life insurance' & 29 & bank & own & 2 & skilled & 1 & yes & yes \\
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\end{tabular}
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| 151 |
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","{'age': 29, 'checking_status': ""'no checking'"", 'credit_amount': 5003, 'credit_history': ""'no credits/all paid'"", 'duration': 21, 'employment': ""'1<=X<4'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 1, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'bank', 'own_telephone': 'yes', 'property_magnitude': ""'life insurance'"", 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'no known savings'""}",A 29-year-old female German Foreigner is applying for a loan of 5003 credits for 21 months for new car purposes. She has no checking account and no known savings. She did not take any credits at this bank or has duly paid back all credits at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 1%. She has other installment plans with a bank and 2 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 4 years. She owns life insurance property. She owns a telephone and has 1 person that she is liable to provide maintenance for.
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new_data/german-fewshot-4.csv
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| 1 |
+
Unnamed: 0,gender,checking_status,duration,credit_history,purpose,credit_amount,savings_status,employment,installment_commitment,other_parties,residence_since,property_magnitude,age,other_payment_plans,housing,existing_credits,job,num_dependents,own_telephone,foreign_worker,class,great,list,text,html,latex,json,LIFT
|
| 2 |
+
0,male,'<0',60,'delayed previously',business,6836,'<100','>=7',3,none,4,'no known property',63,none,own,2,skilled,1,yes,yes,bad,"gender is male, checking_status is '<0', duration is 60, credit_history is 'delayed previously', purpose is business, credit_amount is 6836, savings_status is '<100', employment is '>=7', installment_commitment is 3, other_parties is none, residence_since is 4, property_magnitude is 'no known property', age is 63, other_payment_plans is none, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : male
|
| 3 |
+
- checking_status : '<0'
|
| 4 |
+
- duration : 60
|
| 5 |
+
- credit_history : 'delayed previously'
|
| 6 |
+
- purpose : business
|
| 7 |
+
- credit_amount : 6836
|
| 8 |
+
- savings_status : '<100'
|
| 9 |
+
- employment : '>=7'
|
| 10 |
+
- installment_commitment : 3
|
| 11 |
+
- other_parties : none
|
| 12 |
+
- residence_since : 4
|
| 13 |
+
- property_magnitude : 'no known property'
|
| 14 |
+
- age : 63
|
| 15 |
+
- other_payment_plans : none
|
| 16 |
+
- housing : own
|
| 17 |
+
- existing_credits : 2
|
| 18 |
+
- job : skilled
|
| 19 |
+
- num_dependents : 1
|
| 20 |
+
- own_telephone : yes
|
| 21 |
+
- foreign_worker : yes",The gender is male. The checking_status is '<0'. The duration is 60. The credit_history is 'delayed previously'. The purpose is business. The credit_amount is 6836. The savings_status is '<100'. The employment is '>=7'. The installment_commitment is 3. The other_parties is none. The residence_since is 4. The property_magnitude is 'no known property'. The age is 63. The other_payment_plans is none. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 22 |
+
<thead>
|
| 23 |
+
<tr style=""text-align: right;"">
|
| 24 |
+
<th></th>
|
| 25 |
+
<th>gender</th>
|
| 26 |
+
<th>checking_status</th>
|
| 27 |
+
<th>duration</th>
|
| 28 |
+
<th>credit_history</th>
|
| 29 |
+
<th>purpose</th>
|
| 30 |
+
<th>credit_amount</th>
|
| 31 |
+
<th>savings_status</th>
|
| 32 |
+
<th>employment</th>
|
| 33 |
+
<th>installment_commitment</th>
|
| 34 |
+
<th>other_parties</th>
|
| 35 |
+
<th>residence_since</th>
|
| 36 |
+
<th>property_magnitude</th>
|
| 37 |
+
<th>age</th>
|
| 38 |
+
<th>other_payment_plans</th>
|
| 39 |
+
<th>housing</th>
|
| 40 |
+
<th>existing_credits</th>
|
| 41 |
+
<th>job</th>
|
| 42 |
+
<th>num_dependents</th>
|
| 43 |
+
<th>own_telephone</th>
|
| 44 |
+
<th>foreign_worker</th>
|
| 45 |
+
</tr>
|
| 46 |
+
</thead>
|
| 47 |
+
<tbody>
|
| 48 |
+
<tr>
|
| 49 |
+
<th>0</th>
|
| 50 |
+
<td>male</td>
|
| 51 |
+
<td>'<0'</td>
|
| 52 |
+
<td>60</td>
|
| 53 |
+
<td>'delayed previously'</td>
|
| 54 |
+
<td>business</td>
|
| 55 |
+
<td>6836</td>
|
| 56 |
+
<td>'<100'</td>
|
| 57 |
+
<td>'>=7'</td>
|
| 58 |
+
<td>3</td>
|
| 59 |
+
<td>none</td>
|
| 60 |
+
<td>4</td>
|
| 61 |
+
<td>'no known property'</td>
|
| 62 |
+
<td>63</td>
|
| 63 |
+
<td>none</td>
|
| 64 |
+
<td>own</td>
|
| 65 |
+
<td>2</td>
|
| 66 |
+
<td>skilled</td>
|
| 67 |
+
<td>1</td>
|
| 68 |
+
<td>yes</td>
|
| 69 |
+
<td>yes</td>
|
| 70 |
+
</tr>
|
| 71 |
+
</tbody>
|
| 72 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 73 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 74 |
+
0 & male & '<0' & 60 & 'delayed previously' & business & 6836 & '<100' & '>=7' & 3 & none & 4 & 'no known property' & 63 & none & own & 2 & skilled & 1 & yes & yes \\
|
| 75 |
+
\end{tabular}
|
| 76 |
+
","{'age': 63, 'checking_status': ""'<0'"", 'credit_amount': 6836, 'credit_history': ""'delayed previously'"", 'duration': 60, 'employment': ""'>=7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'own', 'installment_commitment': 3, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': ""'no known property'"", 'purpose': 'business', 'residence_since': 4, 'savings_status': ""'<100'""}",A 63-year-old male German Foreigner is applying for a loan of 6836 credits for 60 months for business purposes. He has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. He has delayed paying back credits received from this bank in the past. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 3%. He has no other installment plans and 2 credits at this bank. He is employed for more than seven years. He has lived in a self-owned house for 4 years. He owns no known property. He owns a telephone and has 1 person that he is liable to provide maintenance for.
|
| 77 |
+
3,female,'no checking',21,'no credits/all paid','new car',5003,'no known savings','1<=X<4',1,none,4,'life insurance',29,bank,own,2,skilled,1,yes,yes,bad,"gender is female, checking_status is 'no checking', duration is 21, credit_history is 'no credits/all paid', purpose is 'new car', credit_amount is 5003, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 1, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 29, other_payment_plans is bank, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : female
|
| 78 |
+
- checking_status : 'no checking'
|
| 79 |
+
- duration : 21
|
| 80 |
+
- credit_history : 'no credits/all paid'
|
| 81 |
+
- purpose : 'new car'
|
| 82 |
+
- credit_amount : 5003
|
| 83 |
+
- savings_status : 'no known savings'
|
| 84 |
+
- employment : '1<=X<4'
|
| 85 |
+
- installment_commitment : 1
|
| 86 |
+
- other_parties : none
|
| 87 |
+
- residence_since : 4
|
| 88 |
+
- property_magnitude : 'life insurance'
|
| 89 |
+
- age : 29
|
| 90 |
+
- other_payment_plans : bank
|
| 91 |
+
- housing : own
|
| 92 |
+
- existing_credits : 2
|
| 93 |
+
- job : skilled
|
| 94 |
+
- num_dependents : 1
|
| 95 |
+
- own_telephone : yes
|
| 96 |
+
- foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 21. The credit_history is 'no credits/all paid'. The purpose is 'new car'. The credit_amount is 5003. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 1. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 29. The other_payment_plans is bank. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 97 |
+
<thead>
|
| 98 |
+
<tr style=""text-align: right;"">
|
| 99 |
+
<th></th>
|
| 100 |
+
<th>gender</th>
|
| 101 |
+
<th>checking_status</th>
|
| 102 |
+
<th>duration</th>
|
| 103 |
+
<th>credit_history</th>
|
| 104 |
+
<th>purpose</th>
|
| 105 |
+
<th>credit_amount</th>
|
| 106 |
+
<th>savings_status</th>
|
| 107 |
+
<th>employment</th>
|
| 108 |
+
<th>installment_commitment</th>
|
| 109 |
+
<th>other_parties</th>
|
| 110 |
+
<th>residence_since</th>
|
| 111 |
+
<th>property_magnitude</th>
|
| 112 |
+
<th>age</th>
|
| 113 |
+
<th>other_payment_plans</th>
|
| 114 |
+
<th>housing</th>
|
| 115 |
+
<th>existing_credits</th>
|
| 116 |
+
<th>job</th>
|
| 117 |
+
<th>num_dependents</th>
|
| 118 |
+
<th>own_telephone</th>
|
| 119 |
+
<th>foreign_worker</th>
|
| 120 |
+
</tr>
|
| 121 |
+
</thead>
|
| 122 |
+
<tbody>
|
| 123 |
+
<tr>
|
| 124 |
+
<th>0</th>
|
| 125 |
+
<td>female</td>
|
| 126 |
+
<td>'no checking'</td>
|
| 127 |
+
<td>21</td>
|
| 128 |
+
<td>'no credits/all paid'</td>
|
| 129 |
+
<td>'new car'</td>
|
| 130 |
+
<td>5003</td>
|
| 131 |
+
<td>'no known savings'</td>
|
| 132 |
+
<td>'1<=X<4'</td>
|
| 133 |
+
<td>1</td>
|
| 134 |
+
<td>none</td>
|
| 135 |
+
<td>4</td>
|
| 136 |
+
<td>'life insurance'</td>
|
| 137 |
+
<td>29</td>
|
| 138 |
+
<td>bank</td>
|
| 139 |
+
<td>own</td>
|
| 140 |
+
<td>2</td>
|
| 141 |
+
<td>skilled</td>
|
| 142 |
+
<td>1</td>
|
| 143 |
+
<td>yes</td>
|
| 144 |
+
<td>yes</td>
|
| 145 |
+
</tr>
|
| 146 |
+
</tbody>
|
| 147 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 148 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 149 |
+
0 & female & 'no checking' & 21 & 'no credits/all paid' & 'new car' & 5003 & 'no known savings' & '1<=X<4' & 1 & none & 4 & 'life insurance' & 29 & bank & own & 2 & skilled & 1 & yes & yes \\
|
| 150 |
+
\end{tabular}
|
| 151 |
+
","{'age': 29, 'checking_status': ""'no checking'"", 'credit_amount': 5003, 'credit_history': ""'no credits/all paid'"", 'duration': 21, 'employment': ""'1<=X<4'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 1, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'bank', 'own_telephone': 'yes', 'property_magnitude': ""'life insurance'"", 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'no known savings'""}",A 29-year-old female German Foreigner is applying for a loan of 5003 credits for 21 months for new car purposes. She has no checking account and no known savings. She did not take any credits at this bank or has duly paid back all credits at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 1%. She has other installment plans with a bank and 2 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 4 years. She owns life insurance property. She owns a telephone and has 1 person that she is liable to provide maintenance for.
|
| 152 |
+
1,male,'>=200',21,'critical/other existing credit',education,2319,'<100','<1',2,none,1,car,33,none,rent,1,skilled,1,none,yes,bad,"gender is male, checking_status is '>=200', duration is 21, credit_history is 'critical/other existing credit', purpose is education, credit_amount is 2319, savings_status is '<100', employment is '<1', installment_commitment is 2, other_parties is none, residence_since is 1, property_magnitude is car, age is 33, other_payment_plans is none, housing is rent, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : male
|
| 153 |
+
- checking_status : '>=200'
|
| 154 |
+
- duration : 21
|
| 155 |
+
- credit_history : 'critical/other existing credit'
|
| 156 |
+
- purpose : education
|
| 157 |
+
- credit_amount : 2319
|
| 158 |
+
- savings_status : '<100'
|
| 159 |
+
- employment : '<1'
|
| 160 |
+
- installment_commitment : 2
|
| 161 |
+
- other_parties : none
|
| 162 |
+
- residence_since : 1
|
| 163 |
+
- property_magnitude : car
|
| 164 |
+
- age : 33
|
| 165 |
+
- other_payment_plans : none
|
| 166 |
+
- housing : rent
|
| 167 |
+
- existing_credits : 1
|
| 168 |
+
- job : skilled
|
| 169 |
+
- num_dependents : 1
|
| 170 |
+
- own_telephone : none
|
| 171 |
+
- foreign_worker : yes",The gender is male. The checking_status is '>=200'. The duration is 21. The credit_history is 'critical/other existing credit'. The purpose is education. The credit_amount is 2319. The savings_status is '<100'. The employment is '<1'. The installment_commitment is 2. The other_parties is none. The residence_since is 1. The property_magnitude is car. The age is 33. The other_payment_plans is none. The housing is rent. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 172 |
+
<thead>
|
| 173 |
+
<tr style=""text-align: right;"">
|
| 174 |
+
<th></th>
|
| 175 |
+
<th>gender</th>
|
| 176 |
+
<th>checking_status</th>
|
| 177 |
+
<th>duration</th>
|
| 178 |
+
<th>credit_history</th>
|
| 179 |
+
<th>purpose</th>
|
| 180 |
+
<th>credit_amount</th>
|
| 181 |
+
<th>savings_status</th>
|
| 182 |
+
<th>employment</th>
|
| 183 |
+
<th>installment_commitment</th>
|
| 184 |
+
<th>other_parties</th>
|
| 185 |
+
<th>residence_since</th>
|
| 186 |
+
<th>property_magnitude</th>
|
| 187 |
+
<th>age</th>
|
| 188 |
+
<th>other_payment_plans</th>
|
| 189 |
+
<th>housing</th>
|
| 190 |
+
<th>existing_credits</th>
|
| 191 |
+
<th>job</th>
|
| 192 |
+
<th>num_dependents</th>
|
| 193 |
+
<th>own_telephone</th>
|
| 194 |
+
<th>foreign_worker</th>
|
| 195 |
+
</tr>
|
| 196 |
+
</thead>
|
| 197 |
+
<tbody>
|
| 198 |
+
<tr>
|
| 199 |
+
<th>0</th>
|
| 200 |
+
<td>male</td>
|
| 201 |
+
<td>'>=200'</td>
|
| 202 |
+
<td>21</td>
|
| 203 |
+
<td>'critical/other existing credit'</td>
|
| 204 |
+
<td>education</td>
|
| 205 |
+
<td>2319</td>
|
| 206 |
+
<td>'<100'</td>
|
| 207 |
+
<td>'<1'</td>
|
| 208 |
+
<td>2</td>
|
| 209 |
+
<td>none</td>
|
| 210 |
+
<td>1</td>
|
| 211 |
+
<td>car</td>
|
| 212 |
+
<td>33</td>
|
| 213 |
+
<td>none</td>
|
| 214 |
+
<td>rent</td>
|
| 215 |
+
<td>1</td>
|
| 216 |
+
<td>skilled</td>
|
| 217 |
+
<td>1</td>
|
| 218 |
+
<td>none</td>
|
| 219 |
+
<td>yes</td>
|
| 220 |
+
</tr>
|
| 221 |
+
</tbody>
|
| 222 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 223 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 224 |
+
0 & male & '>=200' & 21 & 'critical/other existing credit' & education & 2319 & '<100' & '<1' & 2 & none & 1 & car & 33 & none & rent & 1 & skilled & 1 & none & yes \\
|
| 225 |
+
\end{tabular}
|
| 226 |
+
","{'age': 33, 'checking_status': ""'>=200'"", 'credit_amount': 2319, 'credit_history': ""'critical/other existing credit'"", 'duration': 21, 'employment': ""'<1'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'rent', 'installment_commitment': 2, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'education', 'residence_since': 1, 'savings_status': ""'<100'""}",A 33-year-old male German Foreigner is applying for a loan of 2319 credits for 21 months for education purposes. He has a checking account with 200 Deutsche Mark or more and a savings acccount with less than 100 Deutsche Mark. He has critical account or has other credits existing but not at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 2%. He has no other installment plans and 1 credits at this bank. He is employed for less than one years. He has lived in a rented apartment for 1 years. He owns a car. He does not own a telephone and has 1 person that he is liable to provide maintenance for.
|
| 227 |
+
4,female,'no checking',12,'existing paid',radio/tv,886,'no known savings','1<=X<4',4,none,2,car,21,none,own,1,skilled,1,none,yes,good,"gender is female, checking_status is 'no checking', duration is 12, credit_history is 'existing paid', purpose is radio/tv, credit_amount is 886, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 4, other_parties is none, residence_since is 2, property_magnitude is car, age is 21, other_payment_plans is none, housing is own, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : female
|
| 228 |
+
- checking_status : 'no checking'
|
| 229 |
+
- duration : 12
|
| 230 |
+
- credit_history : 'existing paid'
|
| 231 |
+
- purpose : radio/tv
|
| 232 |
+
- credit_amount : 886
|
| 233 |
+
- savings_status : 'no known savings'
|
| 234 |
+
- employment : '1<=X<4'
|
| 235 |
+
- installment_commitment : 4
|
| 236 |
+
- other_parties : none
|
| 237 |
+
- residence_since : 2
|
| 238 |
+
- property_magnitude : car
|
| 239 |
+
- age : 21
|
| 240 |
+
- other_payment_plans : none
|
| 241 |
+
- housing : own
|
| 242 |
+
- existing_credits : 1
|
| 243 |
+
- job : skilled
|
| 244 |
+
- num_dependents : 1
|
| 245 |
+
- own_telephone : none
|
| 246 |
+
- foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 12. The credit_history is 'existing paid'. The purpose is radio/tv. The credit_amount is 886. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 4. The other_parties is none. The residence_since is 2. The property_magnitude is car. The age is 21. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 247 |
+
<thead>
|
| 248 |
+
<tr style=""text-align: right;"">
|
| 249 |
+
<th></th>
|
| 250 |
+
<th>gender</th>
|
| 251 |
+
<th>checking_status</th>
|
| 252 |
+
<th>duration</th>
|
| 253 |
+
<th>credit_history</th>
|
| 254 |
+
<th>purpose</th>
|
| 255 |
+
<th>credit_amount</th>
|
| 256 |
+
<th>savings_status</th>
|
| 257 |
+
<th>employment</th>
|
| 258 |
+
<th>installment_commitment</th>
|
| 259 |
+
<th>other_parties</th>
|
| 260 |
+
<th>residence_since</th>
|
| 261 |
+
<th>property_magnitude</th>
|
| 262 |
+
<th>age</th>
|
| 263 |
+
<th>other_payment_plans</th>
|
| 264 |
+
<th>housing</th>
|
| 265 |
+
<th>existing_credits</th>
|
| 266 |
+
<th>job</th>
|
| 267 |
+
<th>num_dependents</th>
|
| 268 |
+
<th>own_telephone</th>
|
| 269 |
+
<th>foreign_worker</th>
|
| 270 |
+
</tr>
|
| 271 |
+
</thead>
|
| 272 |
+
<tbody>
|
| 273 |
+
<tr>
|
| 274 |
+
<th>0</th>
|
| 275 |
+
<td>female</td>
|
| 276 |
+
<td>'no checking'</td>
|
| 277 |
+
<td>12</td>
|
| 278 |
+
<td>'existing paid'</td>
|
| 279 |
+
<td>radio/tv</td>
|
| 280 |
+
<td>886</td>
|
| 281 |
+
<td>'no known savings'</td>
|
| 282 |
+
<td>'1<=X<4'</td>
|
| 283 |
+
<td>4</td>
|
| 284 |
+
<td>none</td>
|
| 285 |
+
<td>2</td>
|
| 286 |
+
<td>car</td>
|
| 287 |
+
<td>21</td>
|
| 288 |
+
<td>none</td>
|
| 289 |
+
<td>own</td>
|
| 290 |
+
<td>1</td>
|
| 291 |
+
<td>skilled</td>
|
| 292 |
+
<td>1</td>
|
| 293 |
+
<td>none</td>
|
| 294 |
+
<td>yes</td>
|
| 295 |
+
</tr>
|
| 296 |
+
</tbody>
|
| 297 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 298 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 299 |
+
0 & female & 'no checking' & 12 & 'existing paid' & radio/tv & 886 & 'no known savings' & '1<=X<4' & 4 & none & 2 & car & 21 & none & own & 1 & skilled & 1 & none & yes \\
|
| 300 |
+
\end{tabular}
|
| 301 |
+
","{'age': 21, 'checking_status': ""'no checking'"", 'credit_amount': 886, 'credit_history': ""'existing paid'"", 'duration': 12, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 4, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'radio/tv', 'residence_since': 2, 'savings_status': ""'no known savings'""}",A 21-year-old female German Foreigner is applying for a loan of 886 credits for 12 months for radio or tv purposes. She has no checking account and no known savings. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 1 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 2 years. She owns a car. She does not own a telephone and has 1 person that she is liable to provide maintenance for.
|
new_data/german-fewshot-6.csv
ADDED
|
@@ -0,0 +1,451 @@
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|
| 1 |
+
Unnamed: 0,gender,checking_status,duration,credit_history,purpose,credit_amount,savings_status,employment,installment_commitment,other_parties,residence_since,property_magnitude,age,other_payment_plans,housing,existing_credits,job,num_dependents,own_telephone,foreign_worker,class,great,list,text,html,latex,json,LIFT
|
| 2 |
+
0,male,'<0',60,'delayed previously',business,6836,'<100','>=7',3,none,4,'no known property',63,none,own,2,skilled,1,yes,yes,bad,"gender is male, checking_status is '<0', duration is 60, credit_history is 'delayed previously', purpose is business, credit_amount is 6836, savings_status is '<100', employment is '>=7', installment_commitment is 3, other_parties is none, residence_since is 4, property_magnitude is 'no known property', age is 63, other_payment_plans is none, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : male
|
| 3 |
+
- checking_status : '<0'
|
| 4 |
+
- duration : 60
|
| 5 |
+
- credit_history : 'delayed previously'
|
| 6 |
+
- purpose : business
|
| 7 |
+
- credit_amount : 6836
|
| 8 |
+
- savings_status : '<100'
|
| 9 |
+
- employment : '>=7'
|
| 10 |
+
- installment_commitment : 3
|
| 11 |
+
- other_parties : none
|
| 12 |
+
- residence_since : 4
|
| 13 |
+
- property_magnitude : 'no known property'
|
| 14 |
+
- age : 63
|
| 15 |
+
- other_payment_plans : none
|
| 16 |
+
- housing : own
|
| 17 |
+
- existing_credits : 2
|
| 18 |
+
- job : skilled
|
| 19 |
+
- num_dependents : 1
|
| 20 |
+
- own_telephone : yes
|
| 21 |
+
- foreign_worker : yes",The gender is male. The checking_status is '<0'. The duration is 60. The credit_history is 'delayed previously'. The purpose is business. The credit_amount is 6836. The savings_status is '<100'. The employment is '>=7'. The installment_commitment is 3. The other_parties is none. The residence_since is 4. The property_magnitude is 'no known property'. The age is 63. The other_payment_plans is none. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 22 |
+
<thead>
|
| 23 |
+
<tr style=""text-align: right;"">
|
| 24 |
+
<th></th>
|
| 25 |
+
<th>gender</th>
|
| 26 |
+
<th>checking_status</th>
|
| 27 |
+
<th>duration</th>
|
| 28 |
+
<th>credit_history</th>
|
| 29 |
+
<th>purpose</th>
|
| 30 |
+
<th>credit_amount</th>
|
| 31 |
+
<th>savings_status</th>
|
| 32 |
+
<th>employment</th>
|
| 33 |
+
<th>installment_commitment</th>
|
| 34 |
+
<th>other_parties</th>
|
| 35 |
+
<th>residence_since</th>
|
| 36 |
+
<th>property_magnitude</th>
|
| 37 |
+
<th>age</th>
|
| 38 |
+
<th>other_payment_plans</th>
|
| 39 |
+
<th>housing</th>
|
| 40 |
+
<th>existing_credits</th>
|
| 41 |
+
<th>job</th>
|
| 42 |
+
<th>num_dependents</th>
|
| 43 |
+
<th>own_telephone</th>
|
| 44 |
+
<th>foreign_worker</th>
|
| 45 |
+
</tr>
|
| 46 |
+
</thead>
|
| 47 |
+
<tbody>
|
| 48 |
+
<tr>
|
| 49 |
+
<th>0</th>
|
| 50 |
+
<td>male</td>
|
| 51 |
+
<td>'<0'</td>
|
| 52 |
+
<td>60</td>
|
| 53 |
+
<td>'delayed previously'</td>
|
| 54 |
+
<td>business</td>
|
| 55 |
+
<td>6836</td>
|
| 56 |
+
<td>'<100'</td>
|
| 57 |
+
<td>'>=7'</td>
|
| 58 |
+
<td>3</td>
|
| 59 |
+
<td>none</td>
|
| 60 |
+
<td>4</td>
|
| 61 |
+
<td>'no known property'</td>
|
| 62 |
+
<td>63</td>
|
| 63 |
+
<td>none</td>
|
| 64 |
+
<td>own</td>
|
| 65 |
+
<td>2</td>
|
| 66 |
+
<td>skilled</td>
|
| 67 |
+
<td>1</td>
|
| 68 |
+
<td>yes</td>
|
| 69 |
+
<td>yes</td>
|
| 70 |
+
</tr>
|
| 71 |
+
</tbody>
|
| 72 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 73 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 74 |
+
0 & male & '<0' & 60 & 'delayed previously' & business & 6836 & '<100' & '>=7' & 3 & none & 4 & 'no known property' & 63 & none & own & 2 & skilled & 1 & yes & yes \\
|
| 75 |
+
\end{tabular}
|
| 76 |
+
","{'age': 63, 'checking_status': ""'<0'"", 'credit_amount': 6836, 'credit_history': ""'delayed previously'"", 'duration': 60, 'employment': ""'>=7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'own', 'installment_commitment': 3, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': ""'no known property'"", 'purpose': 'business', 'residence_since': 4, 'savings_status': ""'<100'""}",A 63-year-old male German Foreigner is applying for a loan of 6836 credits for 60 months for business purposes. He has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. He has delayed paying back credits received from this bank in the past. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 3%. He has no other installment plans and 2 credits at this bank. He is employed for more than seven years. He has lived in a self-owned house for 4 years. He owns no known property. He owns a telephone and has 1 person that he is liable to provide maintenance for.
|
| 77 |
+
3,female,'no checking',21,'no credits/all paid','new car',5003,'no known savings','1<=X<4',1,none,4,'life insurance',29,bank,own,2,skilled,1,yes,yes,bad,"gender is female, checking_status is 'no checking', duration is 21, credit_history is 'no credits/all paid', purpose is 'new car', credit_amount is 5003, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 1, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 29, other_payment_plans is bank, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : female
|
| 78 |
+
- checking_status : 'no checking'
|
| 79 |
+
- duration : 21
|
| 80 |
+
- credit_history : 'no credits/all paid'
|
| 81 |
+
- purpose : 'new car'
|
| 82 |
+
- credit_amount : 5003
|
| 83 |
+
- savings_status : 'no known savings'
|
| 84 |
+
- employment : '1<=X<4'
|
| 85 |
+
- installment_commitment : 1
|
| 86 |
+
- other_parties : none
|
| 87 |
+
- residence_since : 4
|
| 88 |
+
- property_magnitude : 'life insurance'
|
| 89 |
+
- age : 29
|
| 90 |
+
- other_payment_plans : bank
|
| 91 |
+
- housing : own
|
| 92 |
+
- existing_credits : 2
|
| 93 |
+
- job : skilled
|
| 94 |
+
- num_dependents : 1
|
| 95 |
+
- own_telephone : yes
|
| 96 |
+
- foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 21. The credit_history is 'no credits/all paid'. The purpose is 'new car'. The credit_amount is 5003. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 1. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 29. The other_payment_plans is bank. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 97 |
+
<thead>
|
| 98 |
+
<tr style=""text-align: right;"">
|
| 99 |
+
<th></th>
|
| 100 |
+
<th>gender</th>
|
| 101 |
+
<th>checking_status</th>
|
| 102 |
+
<th>duration</th>
|
| 103 |
+
<th>credit_history</th>
|
| 104 |
+
<th>purpose</th>
|
| 105 |
+
<th>credit_amount</th>
|
| 106 |
+
<th>savings_status</th>
|
| 107 |
+
<th>employment</th>
|
| 108 |
+
<th>installment_commitment</th>
|
| 109 |
+
<th>other_parties</th>
|
| 110 |
+
<th>residence_since</th>
|
| 111 |
+
<th>property_magnitude</th>
|
| 112 |
+
<th>age</th>
|
| 113 |
+
<th>other_payment_plans</th>
|
| 114 |
+
<th>housing</th>
|
| 115 |
+
<th>existing_credits</th>
|
| 116 |
+
<th>job</th>
|
| 117 |
+
<th>num_dependents</th>
|
| 118 |
+
<th>own_telephone</th>
|
| 119 |
+
<th>foreign_worker</th>
|
| 120 |
+
</tr>
|
| 121 |
+
</thead>
|
| 122 |
+
<tbody>
|
| 123 |
+
<tr>
|
| 124 |
+
<th>0</th>
|
| 125 |
+
<td>female</td>
|
| 126 |
+
<td>'no checking'</td>
|
| 127 |
+
<td>21</td>
|
| 128 |
+
<td>'no credits/all paid'</td>
|
| 129 |
+
<td>'new car'</td>
|
| 130 |
+
<td>5003</td>
|
| 131 |
+
<td>'no known savings'</td>
|
| 132 |
+
<td>'1<=X<4'</td>
|
| 133 |
+
<td>1</td>
|
| 134 |
+
<td>none</td>
|
| 135 |
+
<td>4</td>
|
| 136 |
+
<td>'life insurance'</td>
|
| 137 |
+
<td>29</td>
|
| 138 |
+
<td>bank</td>
|
| 139 |
+
<td>own</td>
|
| 140 |
+
<td>2</td>
|
| 141 |
+
<td>skilled</td>
|
| 142 |
+
<td>1</td>
|
| 143 |
+
<td>yes</td>
|
| 144 |
+
<td>yes</td>
|
| 145 |
+
</tr>
|
| 146 |
+
</tbody>
|
| 147 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 148 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 149 |
+
0 & female & 'no checking' & 21 & 'no credits/all paid' & 'new car' & 5003 & 'no known savings' & '1<=X<4' & 1 & none & 4 & 'life insurance' & 29 & bank & own & 2 & skilled & 1 & yes & yes \\
|
| 150 |
+
\end{tabular}
|
| 151 |
+
","{'age': 29, 'checking_status': ""'no checking'"", 'credit_amount': 5003, 'credit_history': ""'no credits/all paid'"", 'duration': 21, 'employment': ""'1<=X<4'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 1, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'bank', 'own_telephone': 'yes', 'property_magnitude': ""'life insurance'"", 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'no known savings'""}",A 29-year-old female German Foreigner is applying for a loan of 5003 credits for 21 months for new car purposes. She has no checking account and no known savings. She did not take any credits at this bank or has duly paid back all credits at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 1%. She has other installment plans with a bank and 2 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 4 years. She owns life insurance property. She owns a telephone and has 1 person that she is liable to provide maintenance for.
|
| 152 |
+
1,male,'>=200',21,'critical/other existing credit',education,2319,'<100','<1',2,none,1,car,33,none,rent,1,skilled,1,none,yes,bad,"gender is male, checking_status is '>=200', duration is 21, credit_history is 'critical/other existing credit', purpose is education, credit_amount is 2319, savings_status is '<100', employment is '<1', installment_commitment is 2, other_parties is none, residence_since is 1, property_magnitude is car, age is 33, other_payment_plans is none, housing is rent, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : male
|
| 153 |
+
- checking_status : '>=200'
|
| 154 |
+
- duration : 21
|
| 155 |
+
- credit_history : 'critical/other existing credit'
|
| 156 |
+
- purpose : education
|
| 157 |
+
- credit_amount : 2319
|
| 158 |
+
- savings_status : '<100'
|
| 159 |
+
- employment : '<1'
|
| 160 |
+
- installment_commitment : 2
|
| 161 |
+
- other_parties : none
|
| 162 |
+
- residence_since : 1
|
| 163 |
+
- property_magnitude : car
|
| 164 |
+
- age : 33
|
| 165 |
+
- other_payment_plans : none
|
| 166 |
+
- housing : rent
|
| 167 |
+
- existing_credits : 1
|
| 168 |
+
- job : skilled
|
| 169 |
+
- num_dependents : 1
|
| 170 |
+
- own_telephone : none
|
| 171 |
+
- foreign_worker : yes",The gender is male. The checking_status is '>=200'. The duration is 21. The credit_history is 'critical/other existing credit'. The purpose is education. The credit_amount is 2319. The savings_status is '<100'. The employment is '<1'. The installment_commitment is 2. The other_parties is none. The residence_since is 1. The property_magnitude is car. The age is 33. The other_payment_plans is none. The housing is rent. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 172 |
+
<thead>
|
| 173 |
+
<tr style=""text-align: right;"">
|
| 174 |
+
<th></th>
|
| 175 |
+
<th>gender</th>
|
| 176 |
+
<th>checking_status</th>
|
| 177 |
+
<th>duration</th>
|
| 178 |
+
<th>credit_history</th>
|
| 179 |
+
<th>purpose</th>
|
| 180 |
+
<th>credit_amount</th>
|
| 181 |
+
<th>savings_status</th>
|
| 182 |
+
<th>employment</th>
|
| 183 |
+
<th>installment_commitment</th>
|
| 184 |
+
<th>other_parties</th>
|
| 185 |
+
<th>residence_since</th>
|
| 186 |
+
<th>property_magnitude</th>
|
| 187 |
+
<th>age</th>
|
| 188 |
+
<th>other_payment_plans</th>
|
| 189 |
+
<th>housing</th>
|
| 190 |
+
<th>existing_credits</th>
|
| 191 |
+
<th>job</th>
|
| 192 |
+
<th>num_dependents</th>
|
| 193 |
+
<th>own_telephone</th>
|
| 194 |
+
<th>foreign_worker</th>
|
| 195 |
+
</tr>
|
| 196 |
+
</thead>
|
| 197 |
+
<tbody>
|
| 198 |
+
<tr>
|
| 199 |
+
<th>0</th>
|
| 200 |
+
<td>male</td>
|
| 201 |
+
<td>'>=200'</td>
|
| 202 |
+
<td>21</td>
|
| 203 |
+
<td>'critical/other existing credit'</td>
|
| 204 |
+
<td>education</td>
|
| 205 |
+
<td>2319</td>
|
| 206 |
+
<td>'<100'</td>
|
| 207 |
+
<td>'<1'</td>
|
| 208 |
+
<td>2</td>
|
| 209 |
+
<td>none</td>
|
| 210 |
+
<td>1</td>
|
| 211 |
+
<td>car</td>
|
| 212 |
+
<td>33</td>
|
| 213 |
+
<td>none</td>
|
| 214 |
+
<td>rent</td>
|
| 215 |
+
<td>1</td>
|
| 216 |
+
<td>skilled</td>
|
| 217 |
+
<td>1</td>
|
| 218 |
+
<td>none</td>
|
| 219 |
+
<td>yes</td>
|
| 220 |
+
</tr>
|
| 221 |
+
</tbody>
|
| 222 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 223 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 224 |
+
0 & male & '>=200' & 21 & 'critical/other existing credit' & education & 2319 & '<100' & '<1' & 2 & none & 1 & car & 33 & none & rent & 1 & skilled & 1 & none & yes \\
|
| 225 |
+
\end{tabular}
|
| 226 |
+
","{'age': 33, 'checking_status': ""'>=200'"", 'credit_amount': 2319, 'credit_history': ""'critical/other existing credit'"", 'duration': 21, 'employment': ""'<1'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'rent', 'installment_commitment': 2, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'education', 'residence_since': 1, 'savings_status': ""'<100'""}",A 33-year-old male German Foreigner is applying for a loan of 2319 credits for 21 months for education purposes. He has a checking account with 200 Deutsche Mark or more and a savings acccount with less than 100 Deutsche Mark. He has critical account or has other credits existing but not at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 2%. He has no other installment plans and 1 credits at this bank. He is employed for less than one years. He has lived in a rented apartment for 1 years. He owns a car. He does not own a telephone and has 1 person that he is liable to provide maintenance for.
|
| 227 |
+
4,female,'no checking',12,'existing paid',radio/tv,886,'no known savings','1<=X<4',4,none,2,car,21,none,own,1,skilled,1,none,yes,good,"gender is female, checking_status is 'no checking', duration is 12, credit_history is 'existing paid', purpose is radio/tv, credit_amount is 886, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 4, other_parties is none, residence_since is 2, property_magnitude is car, age is 21, other_payment_plans is none, housing is own, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : female
|
| 228 |
+
- checking_status : 'no checking'
|
| 229 |
+
- duration : 12
|
| 230 |
+
- credit_history : 'existing paid'
|
| 231 |
+
- purpose : radio/tv
|
| 232 |
+
- credit_amount : 886
|
| 233 |
+
- savings_status : 'no known savings'
|
| 234 |
+
- employment : '1<=X<4'
|
| 235 |
+
- installment_commitment : 4
|
| 236 |
+
- other_parties : none
|
| 237 |
+
- residence_since : 2
|
| 238 |
+
- property_magnitude : car
|
| 239 |
+
- age : 21
|
| 240 |
+
- other_payment_plans : none
|
| 241 |
+
- housing : own
|
| 242 |
+
- existing_credits : 1
|
| 243 |
+
- job : skilled
|
| 244 |
+
- num_dependents : 1
|
| 245 |
+
- own_telephone : none
|
| 246 |
+
- foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 12. The credit_history is 'existing paid'. The purpose is radio/tv. The credit_amount is 886. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 4. The other_parties is none. The residence_since is 2. The property_magnitude is car. The age is 21. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 247 |
+
<thead>
|
| 248 |
+
<tr style=""text-align: right;"">
|
| 249 |
+
<th></th>
|
| 250 |
+
<th>gender</th>
|
| 251 |
+
<th>checking_status</th>
|
| 252 |
+
<th>duration</th>
|
| 253 |
+
<th>credit_history</th>
|
| 254 |
+
<th>purpose</th>
|
| 255 |
+
<th>credit_amount</th>
|
| 256 |
+
<th>savings_status</th>
|
| 257 |
+
<th>employment</th>
|
| 258 |
+
<th>installment_commitment</th>
|
| 259 |
+
<th>other_parties</th>
|
| 260 |
+
<th>residence_since</th>
|
| 261 |
+
<th>property_magnitude</th>
|
| 262 |
+
<th>age</th>
|
| 263 |
+
<th>other_payment_plans</th>
|
| 264 |
+
<th>housing</th>
|
| 265 |
+
<th>existing_credits</th>
|
| 266 |
+
<th>job</th>
|
| 267 |
+
<th>num_dependents</th>
|
| 268 |
+
<th>own_telephone</th>
|
| 269 |
+
<th>foreign_worker</th>
|
| 270 |
+
</tr>
|
| 271 |
+
</thead>
|
| 272 |
+
<tbody>
|
| 273 |
+
<tr>
|
| 274 |
+
<th>0</th>
|
| 275 |
+
<td>female</td>
|
| 276 |
+
<td>'no checking'</td>
|
| 277 |
+
<td>12</td>
|
| 278 |
+
<td>'existing paid'</td>
|
| 279 |
+
<td>radio/tv</td>
|
| 280 |
+
<td>886</td>
|
| 281 |
+
<td>'no known savings'</td>
|
| 282 |
+
<td>'1<=X<4'</td>
|
| 283 |
+
<td>4</td>
|
| 284 |
+
<td>none</td>
|
| 285 |
+
<td>2</td>
|
| 286 |
+
<td>car</td>
|
| 287 |
+
<td>21</td>
|
| 288 |
+
<td>none</td>
|
| 289 |
+
<td>own</td>
|
| 290 |
+
<td>1</td>
|
| 291 |
+
<td>skilled</td>
|
| 292 |
+
<td>1</td>
|
| 293 |
+
<td>none</td>
|
| 294 |
+
<td>yes</td>
|
| 295 |
+
</tr>
|
| 296 |
+
</tbody>
|
| 297 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 298 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 299 |
+
0 & female & 'no checking' & 12 & 'existing paid' & radio/tv & 886 & 'no known savings' & '1<=X<4' & 4 & none & 2 & car & 21 & none & own & 1 & skilled & 1 & none & yes \\
|
| 300 |
+
\end{tabular}
|
| 301 |
+
","{'age': 21, 'checking_status': ""'no checking'"", 'credit_amount': 886, 'credit_history': ""'existing paid'"", 'duration': 12, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 4, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'radio/tv', 'residence_since': 2, 'savings_status': ""'no known savings'""}",A 21-year-old female German Foreigner is applying for a loan of 886 credits for 12 months for radio or tv purposes. She has no checking account and no known savings. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 1 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 2 years. She owns a car. She does not own a telephone and has 1 person that she is liable to provide maintenance for.
|
| 302 |
+
2,male,'no checking',6,'existing paid','used car',1236,'500<=X<1000','1<=X<4',2,none,4,'life insurance',50,none,rent,1,skilled,1,none,yes,good,"gender is male, checking_status is 'no checking', duration is 6, credit_history is 'existing paid', purpose is 'used car', credit_amount is 1236, savings_status is '500<=X<1000', employment is '1<=X<4', installment_commitment is 2, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 50, other_payment_plans is none, housing is rent, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : male
|
| 303 |
+
- checking_status : 'no checking'
|
| 304 |
+
- duration : 6
|
| 305 |
+
- credit_history : 'existing paid'
|
| 306 |
+
- purpose : 'used car'
|
| 307 |
+
- credit_amount : 1236
|
| 308 |
+
- savings_status : '500<=X<1000'
|
| 309 |
+
- employment : '1<=X<4'
|
| 310 |
+
- installment_commitment : 2
|
| 311 |
+
- other_parties : none
|
| 312 |
+
- residence_since : 4
|
| 313 |
+
- property_magnitude : 'life insurance'
|
| 314 |
+
- age : 50
|
| 315 |
+
- other_payment_plans : none
|
| 316 |
+
- housing : rent
|
| 317 |
+
- existing_credits : 1
|
| 318 |
+
- job : skilled
|
| 319 |
+
- num_dependents : 1
|
| 320 |
+
- own_telephone : none
|
| 321 |
+
- foreign_worker : yes",The gender is male. The checking_status is 'no checking'. The duration is 6. The credit_history is 'existing paid'. The purpose is 'used car'. The credit_amount is 1236. The savings_status is '500<=X<1000'. The employment is '1<=X<4'. The installment_commitment is 2. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 50. The other_payment_plans is none. The housing is rent. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 322 |
+
<thead>
|
| 323 |
+
<tr style=""text-align: right;"">
|
| 324 |
+
<th></th>
|
| 325 |
+
<th>gender</th>
|
| 326 |
+
<th>checking_status</th>
|
| 327 |
+
<th>duration</th>
|
| 328 |
+
<th>credit_history</th>
|
| 329 |
+
<th>purpose</th>
|
| 330 |
+
<th>credit_amount</th>
|
| 331 |
+
<th>savings_status</th>
|
| 332 |
+
<th>employment</th>
|
| 333 |
+
<th>installment_commitment</th>
|
| 334 |
+
<th>other_parties</th>
|
| 335 |
+
<th>residence_since</th>
|
| 336 |
+
<th>property_magnitude</th>
|
| 337 |
+
<th>age</th>
|
| 338 |
+
<th>other_payment_plans</th>
|
| 339 |
+
<th>housing</th>
|
| 340 |
+
<th>existing_credits</th>
|
| 341 |
+
<th>job</th>
|
| 342 |
+
<th>num_dependents</th>
|
| 343 |
+
<th>own_telephone</th>
|
| 344 |
+
<th>foreign_worker</th>
|
| 345 |
+
</tr>
|
| 346 |
+
</thead>
|
| 347 |
+
<tbody>
|
| 348 |
+
<tr>
|
| 349 |
+
<th>0</th>
|
| 350 |
+
<td>male</td>
|
| 351 |
+
<td>'no checking'</td>
|
| 352 |
+
<td>6</td>
|
| 353 |
+
<td>'existing paid'</td>
|
| 354 |
+
<td>'used car'</td>
|
| 355 |
+
<td>1236</td>
|
| 356 |
+
<td>'500<=X<1000'</td>
|
| 357 |
+
<td>'1<=X<4'</td>
|
| 358 |
+
<td>2</td>
|
| 359 |
+
<td>none</td>
|
| 360 |
+
<td>4</td>
|
| 361 |
+
<td>'life insurance'</td>
|
| 362 |
+
<td>50</td>
|
| 363 |
+
<td>none</td>
|
| 364 |
+
<td>rent</td>
|
| 365 |
+
<td>1</td>
|
| 366 |
+
<td>skilled</td>
|
| 367 |
+
<td>1</td>
|
| 368 |
+
<td>none</td>
|
| 369 |
+
<td>yes</td>
|
| 370 |
+
</tr>
|
| 371 |
+
</tbody>
|
| 372 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 373 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 374 |
+
0 & male & 'no checking' & 6 & 'existing paid' & 'used car' & 1236 & '500<=X<1000' & '1<=X<4' & 2 & none & 4 & 'life insurance' & 50 & none & rent & 1 & skilled & 1 & none & yes \\
|
| 375 |
+
\end{tabular}
|
| 376 |
+
","{'age': 50, 'checking_status': ""'no checking'"", 'credit_amount': 1236, 'credit_history': ""'existing paid'"", 'duration': 6, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'rent', 'installment_commitment': 2, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': ""'life insurance'"", 'purpose': ""'used car'"", 'residence_since': 4, 'savings_status': ""'500<=X<1000'""}",A 50-year-old male German Foreigner is applying for a loan of 1236 credits for 6 months for used car purposes. He has no checking account and a savings with more than 500 Deutsche Mark but less than 1000 Deutsche Mark. He has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 2%. He has no other installment plans and 1 credits at this bank. He is employed for more than one year but less than four years. He has lived in a rented apartment for 4 years. He owns life insurance property. He does not own a telephone and has 1 person that he is liable to provide maintenance for.
|
| 377 |
+
5,female,'<0',24,'existing paid','new car',1442,'<100','4<=X<7',4,none,4,car,23,none,rent,2,skilled,1,none,yes,bad,"gender is female, checking_status is '<0', duration is 24, credit_history is 'existing paid', purpose is 'new car', credit_amount is 1442, savings_status is '<100', employment is '4<=X<7', installment_commitment is 4, other_parties is none, residence_since is 4, property_magnitude is car, age is 23, other_payment_plans is none, housing is rent, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : female
|
| 378 |
+
- checking_status : '<0'
|
| 379 |
+
- duration : 24
|
| 380 |
+
- credit_history : 'existing paid'
|
| 381 |
+
- purpose : 'new car'
|
| 382 |
+
- credit_amount : 1442
|
| 383 |
+
- savings_status : '<100'
|
| 384 |
+
- employment : '4<=X<7'
|
| 385 |
+
- installment_commitment : 4
|
| 386 |
+
- other_parties : none
|
| 387 |
+
- residence_since : 4
|
| 388 |
+
- property_magnitude : car
|
| 389 |
+
- age : 23
|
| 390 |
+
- other_payment_plans : none
|
| 391 |
+
- housing : rent
|
| 392 |
+
- existing_credits : 2
|
| 393 |
+
- job : skilled
|
| 394 |
+
- num_dependents : 1
|
| 395 |
+
- own_telephone : none
|
| 396 |
+
- foreign_worker : yes",The gender is female. The checking_status is '<0'. The duration is 24. The credit_history is 'existing paid'. The purpose is 'new car'. The credit_amount is 1442. The savings_status is '<100'. The employment is '4<=X<7'. The installment_commitment is 4. The other_parties is none. The residence_since is 4. The property_magnitude is car. The age is 23. The other_payment_plans is none. The housing is rent. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 397 |
+
<thead>
|
| 398 |
+
<tr style=""text-align: right;"">
|
| 399 |
+
<th></th>
|
| 400 |
+
<th>gender</th>
|
| 401 |
+
<th>checking_status</th>
|
| 402 |
+
<th>duration</th>
|
| 403 |
+
<th>credit_history</th>
|
| 404 |
+
<th>purpose</th>
|
| 405 |
+
<th>credit_amount</th>
|
| 406 |
+
<th>savings_status</th>
|
| 407 |
+
<th>employment</th>
|
| 408 |
+
<th>installment_commitment</th>
|
| 409 |
+
<th>other_parties</th>
|
| 410 |
+
<th>residence_since</th>
|
| 411 |
+
<th>property_magnitude</th>
|
| 412 |
+
<th>age</th>
|
| 413 |
+
<th>other_payment_plans</th>
|
| 414 |
+
<th>housing</th>
|
| 415 |
+
<th>existing_credits</th>
|
| 416 |
+
<th>job</th>
|
| 417 |
+
<th>num_dependents</th>
|
| 418 |
+
<th>own_telephone</th>
|
| 419 |
+
<th>foreign_worker</th>
|
| 420 |
+
</tr>
|
| 421 |
+
</thead>
|
| 422 |
+
<tbody>
|
| 423 |
+
<tr>
|
| 424 |
+
<th>0</th>
|
| 425 |
+
<td>female</td>
|
| 426 |
+
<td>'<0'</td>
|
| 427 |
+
<td>24</td>
|
| 428 |
+
<td>'existing paid'</td>
|
| 429 |
+
<td>'new car'</td>
|
| 430 |
+
<td>1442</td>
|
| 431 |
+
<td>'<100'</td>
|
| 432 |
+
<td>'4<=X<7'</td>
|
| 433 |
+
<td>4</td>
|
| 434 |
+
<td>none</td>
|
| 435 |
+
<td>4</td>
|
| 436 |
+
<td>car</td>
|
| 437 |
+
<td>23</td>
|
| 438 |
+
<td>none</td>
|
| 439 |
+
<td>rent</td>
|
| 440 |
+
<td>2</td>
|
| 441 |
+
<td>skilled</td>
|
| 442 |
+
<td>1</td>
|
| 443 |
+
<td>none</td>
|
| 444 |
+
<td>yes</td>
|
| 445 |
+
</tr>
|
| 446 |
+
</tbody>
|
| 447 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 448 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 449 |
+
0 & female & '<0' & 24 & 'existing paid' & 'new car' & 1442 & '<100' & '4<=X<7' & 4 & none & 4 & car & 23 & none & rent & 2 & skilled & 1 & none & yes \\
|
| 450 |
+
\end{tabular}
|
| 451 |
+
","{'age': 23, 'checking_status': ""'<0'"", 'credit_amount': 1442, 'credit_history': ""'existing paid'"", 'duration': 24, 'employment': ""'4<=X<7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'rent', 'installment_commitment': 4, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'<100'""}",A 23-year-old female German Foreigner is applying for a loan of 1442 credits for 24 months for new car purposes. She has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 2 credits at this bank. She is employed for more than four years but less than seven years. She has lived in a rented apartment for 4 years. She owns a car. She does not own a telephone and has 1 person that she is liable to provide maintenance for.
|
new_data/german-fewshot-8.csv
ADDED
|
@@ -0,0 +1,601 @@
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| 1 |
+
Unnamed: 0,gender,checking_status,duration,credit_history,purpose,credit_amount,savings_status,employment,installment_commitment,other_parties,residence_since,property_magnitude,age,other_payment_plans,housing,existing_credits,job,num_dependents,own_telephone,foreign_worker,class,great,list,text,html,latex,json,LIFT
|
| 2 |
+
0,male,'<0',60,'delayed previously',business,6836,'<100','>=7',3,none,4,'no known property',63,none,own,2,skilled,1,yes,yes,bad,"gender is male, checking_status is '<0', duration is 60, credit_history is 'delayed previously', purpose is business, credit_amount is 6836, savings_status is '<100', employment is '>=7', installment_commitment is 3, other_parties is none, residence_since is 4, property_magnitude is 'no known property', age is 63, other_payment_plans is none, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : male
|
| 3 |
+
- checking_status : '<0'
|
| 4 |
+
- duration : 60
|
| 5 |
+
- credit_history : 'delayed previously'
|
| 6 |
+
- purpose : business
|
| 7 |
+
- credit_amount : 6836
|
| 8 |
+
- savings_status : '<100'
|
| 9 |
+
- employment : '>=7'
|
| 10 |
+
- installment_commitment : 3
|
| 11 |
+
- other_parties : none
|
| 12 |
+
- residence_since : 4
|
| 13 |
+
- property_magnitude : 'no known property'
|
| 14 |
+
- age : 63
|
| 15 |
+
- other_payment_plans : none
|
| 16 |
+
- housing : own
|
| 17 |
+
- existing_credits : 2
|
| 18 |
+
- job : skilled
|
| 19 |
+
- num_dependents : 1
|
| 20 |
+
- own_telephone : yes
|
| 21 |
+
- foreign_worker : yes",The gender is male. The checking_status is '<0'. The duration is 60. The credit_history is 'delayed previously'. The purpose is business. The credit_amount is 6836. The savings_status is '<100'. The employment is '>=7'. The installment_commitment is 3. The other_parties is none. The residence_since is 4. The property_magnitude is 'no known property'. The age is 63. The other_payment_plans is none. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 22 |
+
<thead>
|
| 23 |
+
<tr style=""text-align: right;"">
|
| 24 |
+
<th></th>
|
| 25 |
+
<th>gender</th>
|
| 26 |
+
<th>checking_status</th>
|
| 27 |
+
<th>duration</th>
|
| 28 |
+
<th>credit_history</th>
|
| 29 |
+
<th>purpose</th>
|
| 30 |
+
<th>credit_amount</th>
|
| 31 |
+
<th>savings_status</th>
|
| 32 |
+
<th>employment</th>
|
| 33 |
+
<th>installment_commitment</th>
|
| 34 |
+
<th>other_parties</th>
|
| 35 |
+
<th>residence_since</th>
|
| 36 |
+
<th>property_magnitude</th>
|
| 37 |
+
<th>age</th>
|
| 38 |
+
<th>other_payment_plans</th>
|
| 39 |
+
<th>housing</th>
|
| 40 |
+
<th>existing_credits</th>
|
| 41 |
+
<th>job</th>
|
| 42 |
+
<th>num_dependents</th>
|
| 43 |
+
<th>own_telephone</th>
|
| 44 |
+
<th>foreign_worker</th>
|
| 45 |
+
</tr>
|
| 46 |
+
</thead>
|
| 47 |
+
<tbody>
|
| 48 |
+
<tr>
|
| 49 |
+
<th>0</th>
|
| 50 |
+
<td>male</td>
|
| 51 |
+
<td>'<0'</td>
|
| 52 |
+
<td>60</td>
|
| 53 |
+
<td>'delayed previously'</td>
|
| 54 |
+
<td>business</td>
|
| 55 |
+
<td>6836</td>
|
| 56 |
+
<td>'<100'</td>
|
| 57 |
+
<td>'>=7'</td>
|
| 58 |
+
<td>3</td>
|
| 59 |
+
<td>none</td>
|
| 60 |
+
<td>4</td>
|
| 61 |
+
<td>'no known property'</td>
|
| 62 |
+
<td>63</td>
|
| 63 |
+
<td>none</td>
|
| 64 |
+
<td>own</td>
|
| 65 |
+
<td>2</td>
|
| 66 |
+
<td>skilled</td>
|
| 67 |
+
<td>1</td>
|
| 68 |
+
<td>yes</td>
|
| 69 |
+
<td>yes</td>
|
| 70 |
+
</tr>
|
| 71 |
+
</tbody>
|
| 72 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 73 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 74 |
+
0 & male & '<0' & 60 & 'delayed previously' & business & 6836 & '<100' & '>=7' & 3 & none & 4 & 'no known property' & 63 & none & own & 2 & skilled & 1 & yes & yes \\
|
| 75 |
+
\end{tabular}
|
| 76 |
+
","{'age': 63, 'checking_status': ""'<0'"", 'credit_amount': 6836, 'credit_history': ""'delayed previously'"", 'duration': 60, 'employment': ""'>=7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'own', 'installment_commitment': 3, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': ""'no known property'"", 'purpose': 'business', 'residence_since': 4, 'savings_status': ""'<100'""}",A 63-year-old male German Foreigner is applying for a loan of 6836 credits for 60 months for business purposes. He has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. He has delayed paying back credits received from this bank in the past. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 3%. He has no other installment plans and 2 credits at this bank. He is employed for more than seven years. He has lived in a self-owned house for 4 years. He owns no known property. He owns a telephone and has 1 person that he is liable to provide maintenance for.
|
| 77 |
+
3,female,'no checking',21,'no credits/all paid','new car',5003,'no known savings','1<=X<4',1,none,4,'life insurance',29,bank,own,2,skilled,1,yes,yes,bad,"gender is female, checking_status is 'no checking', duration is 21, credit_history is 'no credits/all paid', purpose is 'new car', credit_amount is 5003, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 1, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 29, other_payment_plans is bank, housing is own, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : female
|
| 78 |
+
- checking_status : 'no checking'
|
| 79 |
+
- duration : 21
|
| 80 |
+
- credit_history : 'no credits/all paid'
|
| 81 |
+
- purpose : 'new car'
|
| 82 |
+
- credit_amount : 5003
|
| 83 |
+
- savings_status : 'no known savings'
|
| 84 |
+
- employment : '1<=X<4'
|
| 85 |
+
- installment_commitment : 1
|
| 86 |
+
- other_parties : none
|
| 87 |
+
- residence_since : 4
|
| 88 |
+
- property_magnitude : 'life insurance'
|
| 89 |
+
- age : 29
|
| 90 |
+
- other_payment_plans : bank
|
| 91 |
+
- housing : own
|
| 92 |
+
- existing_credits : 2
|
| 93 |
+
- job : skilled
|
| 94 |
+
- num_dependents : 1
|
| 95 |
+
- own_telephone : yes
|
| 96 |
+
- foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 21. The credit_history is 'no credits/all paid'. The purpose is 'new car'. The credit_amount is 5003. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 1. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 29. The other_payment_plans is bank. The housing is own. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 97 |
+
<thead>
|
| 98 |
+
<tr style=""text-align: right;"">
|
| 99 |
+
<th></th>
|
| 100 |
+
<th>gender</th>
|
| 101 |
+
<th>checking_status</th>
|
| 102 |
+
<th>duration</th>
|
| 103 |
+
<th>credit_history</th>
|
| 104 |
+
<th>purpose</th>
|
| 105 |
+
<th>credit_amount</th>
|
| 106 |
+
<th>savings_status</th>
|
| 107 |
+
<th>employment</th>
|
| 108 |
+
<th>installment_commitment</th>
|
| 109 |
+
<th>other_parties</th>
|
| 110 |
+
<th>residence_since</th>
|
| 111 |
+
<th>property_magnitude</th>
|
| 112 |
+
<th>age</th>
|
| 113 |
+
<th>other_payment_plans</th>
|
| 114 |
+
<th>housing</th>
|
| 115 |
+
<th>existing_credits</th>
|
| 116 |
+
<th>job</th>
|
| 117 |
+
<th>num_dependents</th>
|
| 118 |
+
<th>own_telephone</th>
|
| 119 |
+
<th>foreign_worker</th>
|
| 120 |
+
</tr>
|
| 121 |
+
</thead>
|
| 122 |
+
<tbody>
|
| 123 |
+
<tr>
|
| 124 |
+
<th>0</th>
|
| 125 |
+
<td>female</td>
|
| 126 |
+
<td>'no checking'</td>
|
| 127 |
+
<td>21</td>
|
| 128 |
+
<td>'no credits/all paid'</td>
|
| 129 |
+
<td>'new car'</td>
|
| 130 |
+
<td>5003</td>
|
| 131 |
+
<td>'no known savings'</td>
|
| 132 |
+
<td>'1<=X<4'</td>
|
| 133 |
+
<td>1</td>
|
| 134 |
+
<td>none</td>
|
| 135 |
+
<td>4</td>
|
| 136 |
+
<td>'life insurance'</td>
|
| 137 |
+
<td>29</td>
|
| 138 |
+
<td>bank</td>
|
| 139 |
+
<td>own</td>
|
| 140 |
+
<td>2</td>
|
| 141 |
+
<td>skilled</td>
|
| 142 |
+
<td>1</td>
|
| 143 |
+
<td>yes</td>
|
| 144 |
+
<td>yes</td>
|
| 145 |
+
</tr>
|
| 146 |
+
</tbody>
|
| 147 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 148 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 149 |
+
0 & female & 'no checking' & 21 & 'no credits/all paid' & 'new car' & 5003 & 'no known savings' & '1<=X<4' & 1 & none & 4 & 'life insurance' & 29 & bank & own & 2 & skilled & 1 & yes & yes \\
|
| 150 |
+
\end{tabular}
|
| 151 |
+
","{'age': 29, 'checking_status': ""'no checking'"", 'credit_amount': 5003, 'credit_history': ""'no credits/all paid'"", 'duration': 21, 'employment': ""'1<=X<4'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 1, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'bank', 'own_telephone': 'yes', 'property_magnitude': ""'life insurance'"", 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'no known savings'""}",A 29-year-old female German Foreigner is applying for a loan of 5003 credits for 21 months for new car purposes. She has no checking account and no known savings. She did not take any credits at this bank or has duly paid back all credits at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 1%. She has other installment plans with a bank and 2 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 4 years. She owns life insurance property. She owns a telephone and has 1 person that she is liable to provide maintenance for.
|
| 152 |
+
1,male,'>=200',21,'critical/other existing credit',education,2319,'<100','<1',2,none,1,car,33,none,rent,1,skilled,1,none,yes,bad,"gender is male, checking_status is '>=200', duration is 21, credit_history is 'critical/other existing credit', purpose is education, credit_amount is 2319, savings_status is '<100', employment is '<1', installment_commitment is 2, other_parties is none, residence_since is 1, property_magnitude is car, age is 33, other_payment_plans is none, housing is rent, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : male
|
| 153 |
+
- checking_status : '>=200'
|
| 154 |
+
- duration : 21
|
| 155 |
+
- credit_history : 'critical/other existing credit'
|
| 156 |
+
- purpose : education
|
| 157 |
+
- credit_amount : 2319
|
| 158 |
+
- savings_status : '<100'
|
| 159 |
+
- employment : '<1'
|
| 160 |
+
- installment_commitment : 2
|
| 161 |
+
- other_parties : none
|
| 162 |
+
- residence_since : 1
|
| 163 |
+
- property_magnitude : car
|
| 164 |
+
- age : 33
|
| 165 |
+
- other_payment_plans : none
|
| 166 |
+
- housing : rent
|
| 167 |
+
- existing_credits : 1
|
| 168 |
+
- job : skilled
|
| 169 |
+
- num_dependents : 1
|
| 170 |
+
- own_telephone : none
|
| 171 |
+
- foreign_worker : yes",The gender is male. The checking_status is '>=200'. The duration is 21. The credit_history is 'critical/other existing credit'. The purpose is education. The credit_amount is 2319. The savings_status is '<100'. The employment is '<1'. The installment_commitment is 2. The other_parties is none. The residence_since is 1. The property_magnitude is car. The age is 33. The other_payment_plans is none. The housing is rent. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 172 |
+
<thead>
|
| 173 |
+
<tr style=""text-align: right;"">
|
| 174 |
+
<th></th>
|
| 175 |
+
<th>gender</th>
|
| 176 |
+
<th>checking_status</th>
|
| 177 |
+
<th>duration</th>
|
| 178 |
+
<th>credit_history</th>
|
| 179 |
+
<th>purpose</th>
|
| 180 |
+
<th>credit_amount</th>
|
| 181 |
+
<th>savings_status</th>
|
| 182 |
+
<th>employment</th>
|
| 183 |
+
<th>installment_commitment</th>
|
| 184 |
+
<th>other_parties</th>
|
| 185 |
+
<th>residence_since</th>
|
| 186 |
+
<th>property_magnitude</th>
|
| 187 |
+
<th>age</th>
|
| 188 |
+
<th>other_payment_plans</th>
|
| 189 |
+
<th>housing</th>
|
| 190 |
+
<th>existing_credits</th>
|
| 191 |
+
<th>job</th>
|
| 192 |
+
<th>num_dependents</th>
|
| 193 |
+
<th>own_telephone</th>
|
| 194 |
+
<th>foreign_worker</th>
|
| 195 |
+
</tr>
|
| 196 |
+
</thead>
|
| 197 |
+
<tbody>
|
| 198 |
+
<tr>
|
| 199 |
+
<th>0</th>
|
| 200 |
+
<td>male</td>
|
| 201 |
+
<td>'>=200'</td>
|
| 202 |
+
<td>21</td>
|
| 203 |
+
<td>'critical/other existing credit'</td>
|
| 204 |
+
<td>education</td>
|
| 205 |
+
<td>2319</td>
|
| 206 |
+
<td>'<100'</td>
|
| 207 |
+
<td>'<1'</td>
|
| 208 |
+
<td>2</td>
|
| 209 |
+
<td>none</td>
|
| 210 |
+
<td>1</td>
|
| 211 |
+
<td>car</td>
|
| 212 |
+
<td>33</td>
|
| 213 |
+
<td>none</td>
|
| 214 |
+
<td>rent</td>
|
| 215 |
+
<td>1</td>
|
| 216 |
+
<td>skilled</td>
|
| 217 |
+
<td>1</td>
|
| 218 |
+
<td>none</td>
|
| 219 |
+
<td>yes</td>
|
| 220 |
+
</tr>
|
| 221 |
+
</tbody>
|
| 222 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 223 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 224 |
+
0 & male & '>=200' & 21 & 'critical/other existing credit' & education & 2319 & '<100' & '<1' & 2 & none & 1 & car & 33 & none & rent & 1 & skilled & 1 & none & yes \\
|
| 225 |
+
\end{tabular}
|
| 226 |
+
","{'age': 33, 'checking_status': ""'>=200'"", 'credit_amount': 2319, 'credit_history': ""'critical/other existing credit'"", 'duration': 21, 'employment': ""'<1'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'rent', 'installment_commitment': 2, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'education', 'residence_since': 1, 'savings_status': ""'<100'""}",A 33-year-old male German Foreigner is applying for a loan of 2319 credits for 21 months for education purposes. He has a checking account with 200 Deutsche Mark or more and a savings acccount with less than 100 Deutsche Mark. He has critical account or has other credits existing but not at this bank. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 2%. He has no other installment plans and 1 credits at this bank. He is employed for less than one years. He has lived in a rented apartment for 1 years. He owns a car. He does not own a telephone and has 1 person that he is liable to provide maintenance for.
|
| 227 |
+
4,female,'no checking',12,'existing paid',radio/tv,886,'no known savings','1<=X<4',4,none,2,car,21,none,own,1,skilled,1,none,yes,good,"gender is female, checking_status is 'no checking', duration is 12, credit_history is 'existing paid', purpose is radio/tv, credit_amount is 886, savings_status is 'no known savings', employment is '1<=X<4', installment_commitment is 4, other_parties is none, residence_since is 2, property_magnitude is car, age is 21, other_payment_plans is none, housing is own, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : female
|
| 228 |
+
- checking_status : 'no checking'
|
| 229 |
+
- duration : 12
|
| 230 |
+
- credit_history : 'existing paid'
|
| 231 |
+
- purpose : radio/tv
|
| 232 |
+
- credit_amount : 886
|
| 233 |
+
- savings_status : 'no known savings'
|
| 234 |
+
- employment : '1<=X<4'
|
| 235 |
+
- installment_commitment : 4
|
| 236 |
+
- other_parties : none
|
| 237 |
+
- residence_since : 2
|
| 238 |
+
- property_magnitude : car
|
| 239 |
+
- age : 21
|
| 240 |
+
- other_payment_plans : none
|
| 241 |
+
- housing : own
|
| 242 |
+
- existing_credits : 1
|
| 243 |
+
- job : skilled
|
| 244 |
+
- num_dependents : 1
|
| 245 |
+
- own_telephone : none
|
| 246 |
+
- foreign_worker : yes",The gender is female. The checking_status is 'no checking'. The duration is 12. The credit_history is 'existing paid'. The purpose is radio/tv. The credit_amount is 886. The savings_status is 'no known savings'. The employment is '1<=X<4'. The installment_commitment is 4. The other_parties is none. The residence_since is 2. The property_magnitude is car. The age is 21. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 247 |
+
<thead>
|
| 248 |
+
<tr style=""text-align: right;"">
|
| 249 |
+
<th></th>
|
| 250 |
+
<th>gender</th>
|
| 251 |
+
<th>checking_status</th>
|
| 252 |
+
<th>duration</th>
|
| 253 |
+
<th>credit_history</th>
|
| 254 |
+
<th>purpose</th>
|
| 255 |
+
<th>credit_amount</th>
|
| 256 |
+
<th>savings_status</th>
|
| 257 |
+
<th>employment</th>
|
| 258 |
+
<th>installment_commitment</th>
|
| 259 |
+
<th>other_parties</th>
|
| 260 |
+
<th>residence_since</th>
|
| 261 |
+
<th>property_magnitude</th>
|
| 262 |
+
<th>age</th>
|
| 263 |
+
<th>other_payment_plans</th>
|
| 264 |
+
<th>housing</th>
|
| 265 |
+
<th>existing_credits</th>
|
| 266 |
+
<th>job</th>
|
| 267 |
+
<th>num_dependents</th>
|
| 268 |
+
<th>own_telephone</th>
|
| 269 |
+
<th>foreign_worker</th>
|
| 270 |
+
</tr>
|
| 271 |
+
</thead>
|
| 272 |
+
<tbody>
|
| 273 |
+
<tr>
|
| 274 |
+
<th>0</th>
|
| 275 |
+
<td>female</td>
|
| 276 |
+
<td>'no checking'</td>
|
| 277 |
+
<td>12</td>
|
| 278 |
+
<td>'existing paid'</td>
|
| 279 |
+
<td>radio/tv</td>
|
| 280 |
+
<td>886</td>
|
| 281 |
+
<td>'no known savings'</td>
|
| 282 |
+
<td>'1<=X<4'</td>
|
| 283 |
+
<td>4</td>
|
| 284 |
+
<td>none</td>
|
| 285 |
+
<td>2</td>
|
| 286 |
+
<td>car</td>
|
| 287 |
+
<td>21</td>
|
| 288 |
+
<td>none</td>
|
| 289 |
+
<td>own</td>
|
| 290 |
+
<td>1</td>
|
| 291 |
+
<td>skilled</td>
|
| 292 |
+
<td>1</td>
|
| 293 |
+
<td>none</td>
|
| 294 |
+
<td>yes</td>
|
| 295 |
+
</tr>
|
| 296 |
+
</tbody>
|
| 297 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 298 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 299 |
+
0 & female & 'no checking' & 12 & 'existing paid' & radio/tv & 886 & 'no known savings' & '1<=X<4' & 4 & none & 2 & car & 21 & none & own & 1 & skilled & 1 & none & yes \\
|
| 300 |
+
\end{tabular}
|
| 301 |
+
","{'age': 21, 'checking_status': ""'no checking'"", 'credit_amount': 886, 'credit_history': ""'existing paid'"", 'duration': 12, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 4, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': 'radio/tv', 'residence_since': 2, 'savings_status': ""'no known savings'""}",A 21-year-old female German Foreigner is applying for a loan of 886 credits for 12 months for radio or tv purposes. She has no checking account and no known savings. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 1 credits at this bank. She is employed for more than one year but less than four years. She has lived in a self-owned house for 2 years. She owns a car. She does not own a telephone and has 1 person that she is liable to provide maintenance for.
|
| 302 |
+
2,male,'no checking',6,'existing paid','used car',1236,'500<=X<1000','1<=X<4',2,none,4,'life insurance',50,none,rent,1,skilled,1,none,yes,good,"gender is male, checking_status is 'no checking', duration is 6, credit_history is 'existing paid', purpose is 'used car', credit_amount is 1236, savings_status is '500<=X<1000', employment is '1<=X<4', installment_commitment is 2, other_parties is none, residence_since is 4, property_magnitude is 'life insurance', age is 50, other_payment_plans is none, housing is rent, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : male
|
| 303 |
+
- checking_status : 'no checking'
|
| 304 |
+
- duration : 6
|
| 305 |
+
- credit_history : 'existing paid'
|
| 306 |
+
- purpose : 'used car'
|
| 307 |
+
- credit_amount : 1236
|
| 308 |
+
- savings_status : '500<=X<1000'
|
| 309 |
+
- employment : '1<=X<4'
|
| 310 |
+
- installment_commitment : 2
|
| 311 |
+
- other_parties : none
|
| 312 |
+
- residence_since : 4
|
| 313 |
+
- property_magnitude : 'life insurance'
|
| 314 |
+
- age : 50
|
| 315 |
+
- other_payment_plans : none
|
| 316 |
+
- housing : rent
|
| 317 |
+
- existing_credits : 1
|
| 318 |
+
- job : skilled
|
| 319 |
+
- num_dependents : 1
|
| 320 |
+
- own_telephone : none
|
| 321 |
+
- foreign_worker : yes",The gender is male. The checking_status is 'no checking'. The duration is 6. The credit_history is 'existing paid'. The purpose is 'used car'. The credit_amount is 1236. The savings_status is '500<=X<1000'. The employment is '1<=X<4'. The installment_commitment is 2. The other_parties is none. The residence_since is 4. The property_magnitude is 'life insurance'. The age is 50. The other_payment_plans is none. The housing is rent. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 322 |
+
<thead>
|
| 323 |
+
<tr style=""text-align: right;"">
|
| 324 |
+
<th></th>
|
| 325 |
+
<th>gender</th>
|
| 326 |
+
<th>checking_status</th>
|
| 327 |
+
<th>duration</th>
|
| 328 |
+
<th>credit_history</th>
|
| 329 |
+
<th>purpose</th>
|
| 330 |
+
<th>credit_amount</th>
|
| 331 |
+
<th>savings_status</th>
|
| 332 |
+
<th>employment</th>
|
| 333 |
+
<th>installment_commitment</th>
|
| 334 |
+
<th>other_parties</th>
|
| 335 |
+
<th>residence_since</th>
|
| 336 |
+
<th>property_magnitude</th>
|
| 337 |
+
<th>age</th>
|
| 338 |
+
<th>other_payment_plans</th>
|
| 339 |
+
<th>housing</th>
|
| 340 |
+
<th>existing_credits</th>
|
| 341 |
+
<th>job</th>
|
| 342 |
+
<th>num_dependents</th>
|
| 343 |
+
<th>own_telephone</th>
|
| 344 |
+
<th>foreign_worker</th>
|
| 345 |
+
</tr>
|
| 346 |
+
</thead>
|
| 347 |
+
<tbody>
|
| 348 |
+
<tr>
|
| 349 |
+
<th>0</th>
|
| 350 |
+
<td>male</td>
|
| 351 |
+
<td>'no checking'</td>
|
| 352 |
+
<td>6</td>
|
| 353 |
+
<td>'existing paid'</td>
|
| 354 |
+
<td>'used car'</td>
|
| 355 |
+
<td>1236</td>
|
| 356 |
+
<td>'500<=X<1000'</td>
|
| 357 |
+
<td>'1<=X<4'</td>
|
| 358 |
+
<td>2</td>
|
| 359 |
+
<td>none</td>
|
| 360 |
+
<td>4</td>
|
| 361 |
+
<td>'life insurance'</td>
|
| 362 |
+
<td>50</td>
|
| 363 |
+
<td>none</td>
|
| 364 |
+
<td>rent</td>
|
| 365 |
+
<td>1</td>
|
| 366 |
+
<td>skilled</td>
|
| 367 |
+
<td>1</td>
|
| 368 |
+
<td>none</td>
|
| 369 |
+
<td>yes</td>
|
| 370 |
+
</tr>
|
| 371 |
+
</tbody>
|
| 372 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 373 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 374 |
+
0 & male & 'no checking' & 6 & 'existing paid' & 'used car' & 1236 & '500<=X<1000' & '1<=X<4' & 2 & none & 4 & 'life insurance' & 50 & none & rent & 1 & skilled & 1 & none & yes \\
|
| 375 |
+
\end{tabular}
|
| 376 |
+
","{'age': 50, 'checking_status': ""'no checking'"", 'credit_amount': 1236, 'credit_history': ""'existing paid'"", 'duration': 6, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'rent', 'installment_commitment': 2, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': ""'life insurance'"", 'purpose': ""'used car'"", 'residence_since': 4, 'savings_status': ""'500<=X<1000'""}",A 50-year-old male German Foreigner is applying for a loan of 1236 credits for 6 months for used car purposes. He has no checking account and a savings with more than 500 Deutsche Mark but less than 1000 Deutsche Mark. He has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 2%. He has no other installment plans and 1 credits at this bank. He is employed for more than one year but less than four years. He has lived in a rented apartment for 4 years. He owns life insurance property. He does not own a telephone and has 1 person that he is liable to provide maintenance for.
|
| 377 |
+
5,female,'<0',24,'existing paid','new car',1442,'<100','4<=X<7',4,none,4,car,23,none,rent,2,skilled,1,none,yes,bad,"gender is female, checking_status is '<0', duration is 24, credit_history is 'existing paid', purpose is 'new car', credit_amount is 1442, savings_status is '<100', employment is '4<=X<7', installment_commitment is 4, other_parties is none, residence_since is 4, property_magnitude is car, age is 23, other_payment_plans is none, housing is rent, existing_credits is 2, job is skilled, num_dependents is 1, own_telephone is none, foreign_worker is yes","- gender : female
|
| 378 |
+
- checking_status : '<0'
|
| 379 |
+
- duration : 24
|
| 380 |
+
- credit_history : 'existing paid'
|
| 381 |
+
- purpose : 'new car'
|
| 382 |
+
- credit_amount : 1442
|
| 383 |
+
- savings_status : '<100'
|
| 384 |
+
- employment : '4<=X<7'
|
| 385 |
+
- installment_commitment : 4
|
| 386 |
+
- other_parties : none
|
| 387 |
+
- residence_since : 4
|
| 388 |
+
- property_magnitude : car
|
| 389 |
+
- age : 23
|
| 390 |
+
- other_payment_plans : none
|
| 391 |
+
- housing : rent
|
| 392 |
+
- existing_credits : 2
|
| 393 |
+
- job : skilled
|
| 394 |
+
- num_dependents : 1
|
| 395 |
+
- own_telephone : none
|
| 396 |
+
- foreign_worker : yes",The gender is female. The checking_status is '<0'. The duration is 24. The credit_history is 'existing paid'. The purpose is 'new car'. The credit_amount is 1442. The savings_status is '<100'. The employment is '4<=X<7'. The installment_commitment is 4. The other_parties is none. The residence_since is 4. The property_magnitude is car. The age is 23. The other_payment_plans is none. The housing is rent. The existing_credits is 2. The job is skilled. The num_dependents is 1. The own_telephone is none. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 397 |
+
<thead>
|
| 398 |
+
<tr style=""text-align: right;"">
|
| 399 |
+
<th></th>
|
| 400 |
+
<th>gender</th>
|
| 401 |
+
<th>checking_status</th>
|
| 402 |
+
<th>duration</th>
|
| 403 |
+
<th>credit_history</th>
|
| 404 |
+
<th>purpose</th>
|
| 405 |
+
<th>credit_amount</th>
|
| 406 |
+
<th>savings_status</th>
|
| 407 |
+
<th>employment</th>
|
| 408 |
+
<th>installment_commitment</th>
|
| 409 |
+
<th>other_parties</th>
|
| 410 |
+
<th>residence_since</th>
|
| 411 |
+
<th>property_magnitude</th>
|
| 412 |
+
<th>age</th>
|
| 413 |
+
<th>other_payment_plans</th>
|
| 414 |
+
<th>housing</th>
|
| 415 |
+
<th>existing_credits</th>
|
| 416 |
+
<th>job</th>
|
| 417 |
+
<th>num_dependents</th>
|
| 418 |
+
<th>own_telephone</th>
|
| 419 |
+
<th>foreign_worker</th>
|
| 420 |
+
</tr>
|
| 421 |
+
</thead>
|
| 422 |
+
<tbody>
|
| 423 |
+
<tr>
|
| 424 |
+
<th>0</th>
|
| 425 |
+
<td>female</td>
|
| 426 |
+
<td>'<0'</td>
|
| 427 |
+
<td>24</td>
|
| 428 |
+
<td>'existing paid'</td>
|
| 429 |
+
<td>'new car'</td>
|
| 430 |
+
<td>1442</td>
|
| 431 |
+
<td>'<100'</td>
|
| 432 |
+
<td>'4<=X<7'</td>
|
| 433 |
+
<td>4</td>
|
| 434 |
+
<td>none</td>
|
| 435 |
+
<td>4</td>
|
| 436 |
+
<td>car</td>
|
| 437 |
+
<td>23</td>
|
| 438 |
+
<td>none</td>
|
| 439 |
+
<td>rent</td>
|
| 440 |
+
<td>2</td>
|
| 441 |
+
<td>skilled</td>
|
| 442 |
+
<td>1</td>
|
| 443 |
+
<td>none</td>
|
| 444 |
+
<td>yes</td>
|
| 445 |
+
</tr>
|
| 446 |
+
</tbody>
|
| 447 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 448 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 449 |
+
0 & female & '<0' & 24 & 'existing paid' & 'new car' & 1442 & '<100' & '4<=X<7' & 4 & none & 4 & car & 23 & none & rent & 2 & skilled & 1 & none & yes \\
|
| 450 |
+
\end{tabular}
|
| 451 |
+
","{'age': 23, 'checking_status': ""'<0'"", 'credit_amount': 1442, 'credit_history': ""'existing paid'"", 'duration': 24, 'employment': ""'4<=X<7'"", 'existing_credits': 2, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'rent', 'installment_commitment': 4, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'none', 'property_magnitude': 'car', 'purpose': ""'new car'"", 'residence_since': 4, 'savings_status': ""'<100'""}",A 23-year-old female German Foreigner is applying for a loan of 1442 credits for 24 months for new car purposes. She has a checking account with 0 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 2 credits at this bank. She is employed for more than four years but less than seven years. She has lived in a rented apartment for 4 years. She owns a car. She does not own a telephone and has 1 person that she is liable to provide maintenance for.
|
| 452 |
+
6,male,'no checking',6,'existing paid',furniture/equipment,2978,'500<=X<1000','1<=X<4',1,none,2,car,32,none,own,1,skilled,1,yes,yes,good,"gender is male, checking_status is 'no checking', duration is 6, credit_history is 'existing paid', purpose is furniture/equipment, credit_amount is 2978, savings_status is '500<=X<1000', employment is '1<=X<4', installment_commitment is 1, other_parties is none, residence_since is 2, property_magnitude is car, age is 32, other_payment_plans is none, housing is own, existing_credits is 1, job is skilled, num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : male
|
| 453 |
+
- checking_status : 'no checking'
|
| 454 |
+
- duration : 6
|
| 455 |
+
- credit_history : 'existing paid'
|
| 456 |
+
- purpose : furniture/equipment
|
| 457 |
+
- credit_amount : 2978
|
| 458 |
+
- savings_status : '500<=X<1000'
|
| 459 |
+
- employment : '1<=X<4'
|
| 460 |
+
- installment_commitment : 1
|
| 461 |
+
- other_parties : none
|
| 462 |
+
- residence_since : 2
|
| 463 |
+
- property_magnitude : car
|
| 464 |
+
- age : 32
|
| 465 |
+
- other_payment_plans : none
|
| 466 |
+
- housing : own
|
| 467 |
+
- existing_credits : 1
|
| 468 |
+
- job : skilled
|
| 469 |
+
- num_dependents : 1
|
| 470 |
+
- own_telephone : yes
|
| 471 |
+
- foreign_worker : yes",The gender is male. The checking_status is 'no checking'. The duration is 6. The credit_history is 'existing paid'. The purpose is furniture/equipment. The credit_amount is 2978. The savings_status is '500<=X<1000'. The employment is '1<=X<4'. The installment_commitment is 1. The other_parties is none. The residence_since is 2. The property_magnitude is car. The age is 32. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is skilled. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 472 |
+
<thead>
|
| 473 |
+
<tr style=""text-align: right;"">
|
| 474 |
+
<th></th>
|
| 475 |
+
<th>gender</th>
|
| 476 |
+
<th>checking_status</th>
|
| 477 |
+
<th>duration</th>
|
| 478 |
+
<th>credit_history</th>
|
| 479 |
+
<th>purpose</th>
|
| 480 |
+
<th>credit_amount</th>
|
| 481 |
+
<th>savings_status</th>
|
| 482 |
+
<th>employment</th>
|
| 483 |
+
<th>installment_commitment</th>
|
| 484 |
+
<th>other_parties</th>
|
| 485 |
+
<th>residence_since</th>
|
| 486 |
+
<th>property_magnitude</th>
|
| 487 |
+
<th>age</th>
|
| 488 |
+
<th>other_payment_plans</th>
|
| 489 |
+
<th>housing</th>
|
| 490 |
+
<th>existing_credits</th>
|
| 491 |
+
<th>job</th>
|
| 492 |
+
<th>num_dependents</th>
|
| 493 |
+
<th>own_telephone</th>
|
| 494 |
+
<th>foreign_worker</th>
|
| 495 |
+
</tr>
|
| 496 |
+
</thead>
|
| 497 |
+
<tbody>
|
| 498 |
+
<tr>
|
| 499 |
+
<th>0</th>
|
| 500 |
+
<td>male</td>
|
| 501 |
+
<td>'no checking'</td>
|
| 502 |
+
<td>6</td>
|
| 503 |
+
<td>'existing paid'</td>
|
| 504 |
+
<td>furniture/equipment</td>
|
| 505 |
+
<td>2978</td>
|
| 506 |
+
<td>'500<=X<1000'</td>
|
| 507 |
+
<td>'1<=X<4'</td>
|
| 508 |
+
<td>1</td>
|
| 509 |
+
<td>none</td>
|
| 510 |
+
<td>2</td>
|
| 511 |
+
<td>car</td>
|
| 512 |
+
<td>32</td>
|
| 513 |
+
<td>none</td>
|
| 514 |
+
<td>own</td>
|
| 515 |
+
<td>1</td>
|
| 516 |
+
<td>skilled</td>
|
| 517 |
+
<td>1</td>
|
| 518 |
+
<td>yes</td>
|
| 519 |
+
<td>yes</td>
|
| 520 |
+
</tr>
|
| 521 |
+
</tbody>
|
| 522 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 523 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 524 |
+
0 & male & 'no checking' & 6 & 'existing paid' & furniture/equipment & 2978 & '500<=X<1000' & '1<=X<4' & 1 & none & 2 & car & 32 & none & own & 1 & skilled & 1 & yes & yes \\
|
| 525 |
+
\end{tabular}
|
| 526 |
+
","{'age': 32, 'checking_status': ""'no checking'"", 'credit_amount': 2978, 'credit_history': ""'existing paid'"", 'duration': 6, 'employment': ""'1<=X<4'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'male', 'housing': 'own', 'installment_commitment': 1, 'job': 'skilled', 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': 'car', 'purpose': 'furniture/equipment', 'residence_since': 2, 'savings_status': ""'500<=X<1000'""}",A 32-year-old male German Foreigner is applying for a loan of 2978 credits for 6 months for furniture or equipment purposes. He has no checking account and a savings with more than 500 Deutsche Mark but less than 1000 Deutsche Mark. He has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 1%. He has no other installment plans and 1 credits at this bank. He is employed for more than one year but less than four years. He has lived in a self-owned house for 2 years. He owns a car. He owns a telephone and has 1 person that he is liable to provide maintenance for.
|
| 527 |
+
11,female,'0<=X<200',36,'existing paid',radio/tv,4795,'<100','<1',4,none,1,'no known property',30,none,own,1,'high qualif/self emp/mgmt',1,yes,yes,good,"gender is female, checking_status is '0<=X<200', duration is 36, credit_history is 'existing paid', purpose is radio/tv, credit_amount is 4795, savings_status is '<100', employment is '<1', installment_commitment is 4, other_parties is none, residence_since is 1, property_magnitude is 'no known property', age is 30, other_payment_plans is none, housing is own, existing_credits is 1, job is 'high qualif/self emp/mgmt', num_dependents is 1, own_telephone is yes, foreign_worker is yes","- gender : female
|
| 528 |
+
- checking_status : '0<=X<200'
|
| 529 |
+
- duration : 36
|
| 530 |
+
- credit_history : 'existing paid'
|
| 531 |
+
- purpose : radio/tv
|
| 532 |
+
- credit_amount : 4795
|
| 533 |
+
- savings_status : '<100'
|
| 534 |
+
- employment : '<1'
|
| 535 |
+
- installment_commitment : 4
|
| 536 |
+
- other_parties : none
|
| 537 |
+
- residence_since : 1
|
| 538 |
+
- property_magnitude : 'no known property'
|
| 539 |
+
- age : 30
|
| 540 |
+
- other_payment_plans : none
|
| 541 |
+
- housing : own
|
| 542 |
+
- existing_credits : 1
|
| 543 |
+
- job : 'high qualif/self emp/mgmt'
|
| 544 |
+
- num_dependents : 1
|
| 545 |
+
- own_telephone : yes
|
| 546 |
+
- foreign_worker : yes",The gender is female. The checking_status is '0<=X<200'. The duration is 36. The credit_history is 'existing paid'. The purpose is radio/tv. The credit_amount is 4795. The savings_status is '<100'. The employment is '<1'. The installment_commitment is 4. The other_parties is none. The residence_since is 1. The property_magnitude is 'no known property'. The age is 30. The other_payment_plans is none. The housing is own. The existing_credits is 1. The job is 'high qualif/self emp/mgmt'. The num_dependents is 1. The own_telephone is yes. The foreign_worker is yes,"<table border=""1"" class=""dataframe"">
|
| 547 |
+
<thead>
|
| 548 |
+
<tr style=""text-align: right;"">
|
| 549 |
+
<th></th>
|
| 550 |
+
<th>gender</th>
|
| 551 |
+
<th>checking_status</th>
|
| 552 |
+
<th>duration</th>
|
| 553 |
+
<th>credit_history</th>
|
| 554 |
+
<th>purpose</th>
|
| 555 |
+
<th>credit_amount</th>
|
| 556 |
+
<th>savings_status</th>
|
| 557 |
+
<th>employment</th>
|
| 558 |
+
<th>installment_commitment</th>
|
| 559 |
+
<th>other_parties</th>
|
| 560 |
+
<th>residence_since</th>
|
| 561 |
+
<th>property_magnitude</th>
|
| 562 |
+
<th>age</th>
|
| 563 |
+
<th>other_payment_plans</th>
|
| 564 |
+
<th>housing</th>
|
| 565 |
+
<th>existing_credits</th>
|
| 566 |
+
<th>job</th>
|
| 567 |
+
<th>num_dependents</th>
|
| 568 |
+
<th>own_telephone</th>
|
| 569 |
+
<th>foreign_worker</th>
|
| 570 |
+
</tr>
|
| 571 |
+
</thead>
|
| 572 |
+
<tbody>
|
| 573 |
+
<tr>
|
| 574 |
+
<th>0</th>
|
| 575 |
+
<td>female</td>
|
| 576 |
+
<td>'0<=X<200'</td>
|
| 577 |
+
<td>36</td>
|
| 578 |
+
<td>'existing paid'</td>
|
| 579 |
+
<td>radio/tv</td>
|
| 580 |
+
<td>4795</td>
|
| 581 |
+
<td>'<100'</td>
|
| 582 |
+
<td>'<1'</td>
|
| 583 |
+
<td>4</td>
|
| 584 |
+
<td>none</td>
|
| 585 |
+
<td>1</td>
|
| 586 |
+
<td>'no known property'</td>
|
| 587 |
+
<td>30</td>
|
| 588 |
+
<td>none</td>
|
| 589 |
+
<td>own</td>
|
| 590 |
+
<td>1</td>
|
| 591 |
+
<td>'high qualif/self emp/mgmt'</td>
|
| 592 |
+
<td>1</td>
|
| 593 |
+
<td>yes</td>
|
| 594 |
+
<td>yes</td>
|
| 595 |
+
</tr>
|
| 596 |
+
</tbody>
|
| 597 |
+
</table>","\begin{tabular}{lllrllrllrlrlrllrlrll}
|
| 598 |
+
& gender & checking_status & duration & credit_history & purpose & credit_amount & savings_status & employment & installment_commitment & other_parties & residence_since & property_magnitude & age & other_payment_plans & housing & existing_credits & job & num_dependents & own_telephone & foreign_worker \\
|
| 599 |
+
0 & female & '0<=X<200' & 36 & 'existing paid' & radio/tv & 4795 & '<100' & '<1' & 4 & none & 1 & 'no known property' & 30 & none & own & 1 & 'high qualif/self emp/mgmt' & 1 & yes & yes \\
|
| 600 |
+
\end{tabular}
|
| 601 |
+
","{'age': 30, 'checking_status': ""'0<=X<200'"", 'credit_amount': 4795, 'credit_history': ""'existing paid'"", 'duration': 36, 'employment': ""'<1'"", 'existing_credits': 1, 'foreign_worker': 'yes', 'gender': 'female', 'housing': 'own', 'installment_commitment': 4, 'job': ""'high qualif/self emp/mgmt'"", 'num_dependents': 1, 'other_parties': 'none', 'other_payment_plans': 'none', 'own_telephone': 'yes', 'property_magnitude': ""'no known property'"", 'purpose': 'radio/tv', 'residence_since': 1, 'savings_status': ""'<100'""}",A 30-year-old female German Foreigner is applying for a loan of 4795 credits for 36 months for radio or tv purposes. She has a checking account with less than 200 Deutsche Mark and a savings acccount with less than 100 Deutsche Mark. She has duly paid back credits received from this bank till now. There are no other party associated with this loan. The installment rate given to this applicant by the bank in percentage is 4%. She has no other installment plans and 1 credits at this bank. She is employed for less than one years and is recognized as a highly qualified employee or is self employed or has managerial position. She has lived in a self-owned house for 1 years. She owns no known property. She owns a telephone and has 1 person that she is liable to provide maintenance for.
|
new_data/ghana-fewshot-2.csv
ADDED
|
@@ -0,0 +1,121 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Unnamed: 0,sex,amnt req,amnt grnt,ration,maturity,assets val,dec profit,xperience,educatn,age,collateral,locatn,guarantor,relatnshp,purpose,sector,savings,target,great,list,text,html,latex,json,LIFT
|
| 2 |
+
1,1,1000,1000,0,30.0,3000,600.0,6.0,2,35,3000,0,0,0,1,1,0,Yes,"sex is 1, amnt req is 1000, maturity is 30.0, assets val is 3000, dec profit is 600.0, xperience is 6.0, educatn is 2, age is 35, collateral is 3000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 1, savings is 0","- sex : 1
|
| 3 |
+
- amnt req : 1000
|
| 4 |
+
- maturity : 30.0
|
| 5 |
+
- assets val : 3000
|
| 6 |
+
- dec profit : 600.0
|
| 7 |
+
- xperience : 6.0
|
| 8 |
+
- educatn : 2
|
| 9 |
+
- age : 35
|
| 10 |
+
- collateral : 3000
|
| 11 |
+
- locatn : 0
|
| 12 |
+
- guarantor : 0
|
| 13 |
+
- relatnshp : 0
|
| 14 |
+
- purpose : 1
|
| 15 |
+
- sector : 1
|
| 16 |
+
- savings : 0",The sex is 1. The amnt req is 1000. The maturity is 30.0. The assets val is 3000. The dec profit is 600.0. The xperience is 6.0. The educatn is 2. The age is 35. The collateral is 3000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 17 |
+
<thead>
|
| 18 |
+
<tr style=""text-align: right;"">
|
| 19 |
+
<th></th>
|
| 20 |
+
<th>sex</th>
|
| 21 |
+
<th>amnt req</th>
|
| 22 |
+
<th>maturity</th>
|
| 23 |
+
<th>assets val</th>
|
| 24 |
+
<th>dec profit</th>
|
| 25 |
+
<th>xperience</th>
|
| 26 |
+
<th>educatn</th>
|
| 27 |
+
<th>age</th>
|
| 28 |
+
<th>collateral</th>
|
| 29 |
+
<th>locatn</th>
|
| 30 |
+
<th>guarantor</th>
|
| 31 |
+
<th>relatnshp</th>
|
| 32 |
+
<th>purpose</th>
|
| 33 |
+
<th>sector</th>
|
| 34 |
+
<th>savings</th>
|
| 35 |
+
</tr>
|
| 36 |
+
</thead>
|
| 37 |
+
<tbody>
|
| 38 |
+
<tr>
|
| 39 |
+
<th>0</th>
|
| 40 |
+
<td>1</td>
|
| 41 |
+
<td>1000</td>
|
| 42 |
+
<td>30.0</td>
|
| 43 |
+
<td>3000</td>
|
| 44 |
+
<td>600.0</td>
|
| 45 |
+
<td>6.0</td>
|
| 46 |
+
<td>2</td>
|
| 47 |
+
<td>35</td>
|
| 48 |
+
<td>3000</td>
|
| 49 |
+
<td>0</td>
|
| 50 |
+
<td>0</td>
|
| 51 |
+
<td>0</td>
|
| 52 |
+
<td>1</td>
|
| 53 |
+
<td>1</td>
|
| 54 |
+
<td>0</td>
|
| 55 |
+
</tr>
|
| 56 |
+
</tbody>
|
| 57 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 58 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 59 |
+
0 & 1 & 1000 & 30.000000 & 3000 & 600.000000 & 6.000000 & 2 & 35 & 3000 & 0 & 0 & 0 & 1 & 1 & 0 \\
|
| 60 |
+
\end{tabular}
|
| 61 |
+
","{'age': 35, 'amnt req': 1000, 'assets val': 3000, 'collateral': 3000, 'dec profit': 600.0, 'educatn': 2, 'guarantor': 0, 'locatn': 0, 'maturity': 30.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 1, 'sex': 1, 'xperience': 6.0}",A 35-year-old male is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 30.0 years. His assets value is 3000 cedis and his declared profits (after tax) is 600.0 cedis. His educational background is secondary and the number of years that he has been in business is 6.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 3000 cedis.
|
| 62 |
+
0,0,2000,2000,0,36.0,4000,500.0,3.0,1,28,900,0,0,1,0,1,0,Yes,"sex is 0, amnt req is 2000, maturity is 36.0, assets val is 4000, dec profit is 500.0, xperience is 3.0, educatn is 1, age is 28, collateral is 900, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
|
| 63 |
+
- amnt req : 2000
|
| 64 |
+
- maturity : 36.0
|
| 65 |
+
- assets val : 4000
|
| 66 |
+
- dec profit : 500.0
|
| 67 |
+
- xperience : 3.0
|
| 68 |
+
- educatn : 1
|
| 69 |
+
- age : 28
|
| 70 |
+
- collateral : 900
|
| 71 |
+
- locatn : 0
|
| 72 |
+
- guarantor : 0
|
| 73 |
+
- relatnshp : 1
|
| 74 |
+
- purpose : 0
|
| 75 |
+
- sector : 1
|
| 76 |
+
- savings : 0",The sex is 0. The amnt req is 2000. The maturity is 36.0. The assets val is 4000. The dec profit is 500.0. The xperience is 3.0. The educatn is 1. The age is 28. The collateral is 900. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 77 |
+
<thead>
|
| 78 |
+
<tr style=""text-align: right;"">
|
| 79 |
+
<th></th>
|
| 80 |
+
<th>sex</th>
|
| 81 |
+
<th>amnt req</th>
|
| 82 |
+
<th>maturity</th>
|
| 83 |
+
<th>assets val</th>
|
| 84 |
+
<th>dec profit</th>
|
| 85 |
+
<th>xperience</th>
|
| 86 |
+
<th>educatn</th>
|
| 87 |
+
<th>age</th>
|
| 88 |
+
<th>collateral</th>
|
| 89 |
+
<th>locatn</th>
|
| 90 |
+
<th>guarantor</th>
|
| 91 |
+
<th>relatnshp</th>
|
| 92 |
+
<th>purpose</th>
|
| 93 |
+
<th>sector</th>
|
| 94 |
+
<th>savings</th>
|
| 95 |
+
</tr>
|
| 96 |
+
</thead>
|
| 97 |
+
<tbody>
|
| 98 |
+
<tr>
|
| 99 |
+
<th>0</th>
|
| 100 |
+
<td>0</td>
|
| 101 |
+
<td>2000</td>
|
| 102 |
+
<td>36.0</td>
|
| 103 |
+
<td>4000</td>
|
| 104 |
+
<td>500.0</td>
|
| 105 |
+
<td>3.0</td>
|
| 106 |
+
<td>1</td>
|
| 107 |
+
<td>28</td>
|
| 108 |
+
<td>900</td>
|
| 109 |
+
<td>0</td>
|
| 110 |
+
<td>0</td>
|
| 111 |
+
<td>1</td>
|
| 112 |
+
<td>0</td>
|
| 113 |
+
<td>1</td>
|
| 114 |
+
<td>0</td>
|
| 115 |
+
</tr>
|
| 116 |
+
</tbody>
|
| 117 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 118 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 119 |
+
0 & 0 & 2000 & 36.000000 & 4000 & 500.000000 & 3.000000 & 1 & 28 & 900 & 0 & 0 & 1 & 0 & 1 & 0 \\
|
| 120 |
+
\end{tabular}
|
| 121 |
+
","{'age': 28, 'amnt req': 2000, 'assets val': 4000, 'collateral': 900, 'dec profit': 500.0, 'educatn': 1, 'guarantor': 0, 'locatn': 0, 'maturity': 36.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 3.0}",A 28-year-old female is applying for a loan of 2000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 36.0 years. Her assets value is 4000 cedis and her declared profits (after tax) is 500.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 3.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 900 cedis.
|
new_data/ghana-fewshot-4.csv
ADDED
|
@@ -0,0 +1,241 @@
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
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|
|
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|
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|
| 1 |
+
Unnamed: 0,sex,amnt req,amnt grnt,ration,maturity,assets val,dec profit,xperience,educatn,age,collateral,locatn,guarantor,relatnshp,purpose,sector,savings,target,great,list,text,html,latex,json,LIFT
|
| 2 |
+
1,1,1000,1000,0,30.0,3000,600.0,6.0,2,35,3000,0,0,0,1,1,0,Yes,"sex is 1, amnt req is 1000, maturity is 30.0, assets val is 3000, dec profit is 600.0, xperience is 6.0, educatn is 2, age is 35, collateral is 3000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 1, savings is 0","- sex : 1
|
| 3 |
+
- amnt req : 1000
|
| 4 |
+
- maturity : 30.0
|
| 5 |
+
- assets val : 3000
|
| 6 |
+
- dec profit : 600.0
|
| 7 |
+
- xperience : 6.0
|
| 8 |
+
- educatn : 2
|
| 9 |
+
- age : 35
|
| 10 |
+
- collateral : 3000
|
| 11 |
+
- locatn : 0
|
| 12 |
+
- guarantor : 0
|
| 13 |
+
- relatnshp : 0
|
| 14 |
+
- purpose : 1
|
| 15 |
+
- sector : 1
|
| 16 |
+
- savings : 0",The sex is 1. The amnt req is 1000. The maturity is 30.0. The assets val is 3000. The dec profit is 600.0. The xperience is 6.0. The educatn is 2. The age is 35. The collateral is 3000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 17 |
+
<thead>
|
| 18 |
+
<tr style=""text-align: right;"">
|
| 19 |
+
<th></th>
|
| 20 |
+
<th>sex</th>
|
| 21 |
+
<th>amnt req</th>
|
| 22 |
+
<th>maturity</th>
|
| 23 |
+
<th>assets val</th>
|
| 24 |
+
<th>dec profit</th>
|
| 25 |
+
<th>xperience</th>
|
| 26 |
+
<th>educatn</th>
|
| 27 |
+
<th>age</th>
|
| 28 |
+
<th>collateral</th>
|
| 29 |
+
<th>locatn</th>
|
| 30 |
+
<th>guarantor</th>
|
| 31 |
+
<th>relatnshp</th>
|
| 32 |
+
<th>purpose</th>
|
| 33 |
+
<th>sector</th>
|
| 34 |
+
<th>savings</th>
|
| 35 |
+
</tr>
|
| 36 |
+
</thead>
|
| 37 |
+
<tbody>
|
| 38 |
+
<tr>
|
| 39 |
+
<th>0</th>
|
| 40 |
+
<td>1</td>
|
| 41 |
+
<td>1000</td>
|
| 42 |
+
<td>30.0</td>
|
| 43 |
+
<td>3000</td>
|
| 44 |
+
<td>600.0</td>
|
| 45 |
+
<td>6.0</td>
|
| 46 |
+
<td>2</td>
|
| 47 |
+
<td>35</td>
|
| 48 |
+
<td>3000</td>
|
| 49 |
+
<td>0</td>
|
| 50 |
+
<td>0</td>
|
| 51 |
+
<td>0</td>
|
| 52 |
+
<td>1</td>
|
| 53 |
+
<td>1</td>
|
| 54 |
+
<td>0</td>
|
| 55 |
+
</tr>
|
| 56 |
+
</tbody>
|
| 57 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 58 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 59 |
+
0 & 1 & 1000 & 30.000000 & 3000 & 600.000000 & 6.000000 & 2 & 35 & 3000 & 0 & 0 & 0 & 1 & 1 & 0 \\
|
| 60 |
+
\end{tabular}
|
| 61 |
+
","{'age': 35, 'amnt req': 1000, 'assets val': 3000, 'collateral': 3000, 'dec profit': 600.0, 'educatn': 2, 'guarantor': 0, 'locatn': 0, 'maturity': 30.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 1, 'sex': 1, 'xperience': 6.0}",A 35-year-old male is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 30.0 years. His assets value is 3000 cedis and his declared profits (after tax) is 600.0 cedis. His educational background is secondary and the number of years that he has been in business is 6.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 3000 cedis.
|
| 62 |
+
0,0,2000,2000,0,36.0,4000,500.0,3.0,1,28,900,0,0,1,0,1,0,Yes,"sex is 0, amnt req is 2000, maturity is 36.0, assets val is 4000, dec profit is 500.0, xperience is 3.0, educatn is 1, age is 28, collateral is 900, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
|
| 63 |
+
- amnt req : 2000
|
| 64 |
+
- maturity : 36.0
|
| 65 |
+
- assets val : 4000
|
| 66 |
+
- dec profit : 500.0
|
| 67 |
+
- xperience : 3.0
|
| 68 |
+
- educatn : 1
|
| 69 |
+
- age : 28
|
| 70 |
+
- collateral : 900
|
| 71 |
+
- locatn : 0
|
| 72 |
+
- guarantor : 0
|
| 73 |
+
- relatnshp : 1
|
| 74 |
+
- purpose : 0
|
| 75 |
+
- sector : 1
|
| 76 |
+
- savings : 0",The sex is 0. The amnt req is 2000. The maturity is 36.0. The assets val is 4000. The dec profit is 500.0. The xperience is 3.0. The educatn is 1. The age is 28. The collateral is 900. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 77 |
+
<thead>
|
| 78 |
+
<tr style=""text-align: right;"">
|
| 79 |
+
<th></th>
|
| 80 |
+
<th>sex</th>
|
| 81 |
+
<th>amnt req</th>
|
| 82 |
+
<th>maturity</th>
|
| 83 |
+
<th>assets val</th>
|
| 84 |
+
<th>dec profit</th>
|
| 85 |
+
<th>xperience</th>
|
| 86 |
+
<th>educatn</th>
|
| 87 |
+
<th>age</th>
|
| 88 |
+
<th>collateral</th>
|
| 89 |
+
<th>locatn</th>
|
| 90 |
+
<th>guarantor</th>
|
| 91 |
+
<th>relatnshp</th>
|
| 92 |
+
<th>purpose</th>
|
| 93 |
+
<th>sector</th>
|
| 94 |
+
<th>savings</th>
|
| 95 |
+
</tr>
|
| 96 |
+
</thead>
|
| 97 |
+
<tbody>
|
| 98 |
+
<tr>
|
| 99 |
+
<th>0</th>
|
| 100 |
+
<td>0</td>
|
| 101 |
+
<td>2000</td>
|
| 102 |
+
<td>36.0</td>
|
| 103 |
+
<td>4000</td>
|
| 104 |
+
<td>500.0</td>
|
| 105 |
+
<td>3.0</td>
|
| 106 |
+
<td>1</td>
|
| 107 |
+
<td>28</td>
|
| 108 |
+
<td>900</td>
|
| 109 |
+
<td>0</td>
|
| 110 |
+
<td>0</td>
|
| 111 |
+
<td>1</td>
|
| 112 |
+
<td>0</td>
|
| 113 |
+
<td>1</td>
|
| 114 |
+
<td>0</td>
|
| 115 |
+
</tr>
|
| 116 |
+
</tbody>
|
| 117 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 118 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 119 |
+
0 & 0 & 2000 & 36.000000 & 4000 & 500.000000 & 3.000000 & 1 & 28 & 900 & 0 & 0 & 1 & 0 & 1 & 0 \\
|
| 120 |
+
\end{tabular}
|
| 121 |
+
","{'age': 28, 'amnt req': 2000, 'assets val': 4000, 'collateral': 900, 'dec profit': 500.0, 'educatn': 1, 'guarantor': 0, 'locatn': 0, 'maturity': 36.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 3.0}",A 28-year-old female is applying for a loan of 2000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 36.0 years. Her assets value is 4000 cedis and her declared profits (after tax) is 500.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 3.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 900 cedis.
|
| 122 |
+
4,1,2000,2000,0,60.0,2800,320.0,12.0,3,42,2000,0,0,0,1,5,0,Yes,"sex is 1, amnt req is 2000, maturity is 60.0, assets val is 2800, dec profit is 320.0, xperience is 12.0, educatn is 3, age is 42, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 5, savings is 0","- sex : 1
|
| 123 |
+
- amnt req : 2000
|
| 124 |
+
- maturity : 60.0
|
| 125 |
+
- assets val : 2800
|
| 126 |
+
- dec profit : 320.0
|
| 127 |
+
- xperience : 12.0
|
| 128 |
+
- educatn : 3
|
| 129 |
+
- age : 42
|
| 130 |
+
- collateral : 2000
|
| 131 |
+
- locatn : 0
|
| 132 |
+
- guarantor : 0
|
| 133 |
+
- relatnshp : 0
|
| 134 |
+
- purpose : 1
|
| 135 |
+
- sector : 5
|
| 136 |
+
- savings : 0",The sex is 1. The amnt req is 2000. The maturity is 60.0. The assets val is 2800. The dec profit is 320.0. The xperience is 12.0. The educatn is 3. The age is 42. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 5. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 137 |
+
<thead>
|
| 138 |
+
<tr style=""text-align: right;"">
|
| 139 |
+
<th></th>
|
| 140 |
+
<th>sex</th>
|
| 141 |
+
<th>amnt req</th>
|
| 142 |
+
<th>maturity</th>
|
| 143 |
+
<th>assets val</th>
|
| 144 |
+
<th>dec profit</th>
|
| 145 |
+
<th>xperience</th>
|
| 146 |
+
<th>educatn</th>
|
| 147 |
+
<th>age</th>
|
| 148 |
+
<th>collateral</th>
|
| 149 |
+
<th>locatn</th>
|
| 150 |
+
<th>guarantor</th>
|
| 151 |
+
<th>relatnshp</th>
|
| 152 |
+
<th>purpose</th>
|
| 153 |
+
<th>sector</th>
|
| 154 |
+
<th>savings</th>
|
| 155 |
+
</tr>
|
| 156 |
+
</thead>
|
| 157 |
+
<tbody>
|
| 158 |
+
<tr>
|
| 159 |
+
<th>0</th>
|
| 160 |
+
<td>1</td>
|
| 161 |
+
<td>2000</td>
|
| 162 |
+
<td>60.0</td>
|
| 163 |
+
<td>2800</td>
|
| 164 |
+
<td>320.0</td>
|
| 165 |
+
<td>12.0</td>
|
| 166 |
+
<td>3</td>
|
| 167 |
+
<td>42</td>
|
| 168 |
+
<td>2000</td>
|
| 169 |
+
<td>0</td>
|
| 170 |
+
<td>0</td>
|
| 171 |
+
<td>0</td>
|
| 172 |
+
<td>1</td>
|
| 173 |
+
<td>5</td>
|
| 174 |
+
<td>0</td>
|
| 175 |
+
</tr>
|
| 176 |
+
</tbody>
|
| 177 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 178 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 179 |
+
0 & 1 & 2000 & 60.000000 & 2800 & 320.000000 & 12.000000 & 3 & 42 & 2000 & 0 & 0 & 0 & 1 & 5 & 0 \\
|
| 180 |
+
\end{tabular}
|
| 181 |
+
","{'age': 42, 'amnt req': 2000, 'assets val': 2800, 'collateral': 2000, 'dec profit': 320.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 60.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 5, 'sex': 1, 'xperience': 12.0}",A 42-year-old male is applying for a loan of 2000 cedis. The applicant works in service sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 60.0 years. His assets value is 2800 cedis and his declared profits (after tax) is 320.0 cedis. His educational background is primary and the number of years that he has been in business is 12.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 2000 cedis.
|
| 182 |
+
2,0,5000,3000,1,40.0,7000,1350.0,5.0,3,35,2000,0,0,1,1,4,0,No,"sex is 0, amnt req is 5000, maturity is 40.0, assets val is 7000, dec profit is 1350.0, xperience is 5.0, educatn is 3, age is 35, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 1, sector is 4, savings is 0","- sex : 0
|
| 183 |
+
- amnt req : 5000
|
| 184 |
+
- maturity : 40.0
|
| 185 |
+
- assets val : 7000
|
| 186 |
+
- dec profit : 1350.0
|
| 187 |
+
- xperience : 5.0
|
| 188 |
+
- educatn : 3
|
| 189 |
+
- age : 35
|
| 190 |
+
- collateral : 2000
|
| 191 |
+
- locatn : 0
|
| 192 |
+
- guarantor : 0
|
| 193 |
+
- relatnshp : 1
|
| 194 |
+
- purpose : 1
|
| 195 |
+
- sector : 4
|
| 196 |
+
- savings : 0",The sex is 0. The amnt req is 5000. The maturity is 40.0. The assets val is 7000. The dec profit is 1350.0. The xperience is 5.0. The educatn is 3. The age is 35. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 1. The sector is 4. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 197 |
+
<thead>
|
| 198 |
+
<tr style=""text-align: right;"">
|
| 199 |
+
<th></th>
|
| 200 |
+
<th>sex</th>
|
| 201 |
+
<th>amnt req</th>
|
| 202 |
+
<th>maturity</th>
|
| 203 |
+
<th>assets val</th>
|
| 204 |
+
<th>dec profit</th>
|
| 205 |
+
<th>xperience</th>
|
| 206 |
+
<th>educatn</th>
|
| 207 |
+
<th>age</th>
|
| 208 |
+
<th>collateral</th>
|
| 209 |
+
<th>locatn</th>
|
| 210 |
+
<th>guarantor</th>
|
| 211 |
+
<th>relatnshp</th>
|
| 212 |
+
<th>purpose</th>
|
| 213 |
+
<th>sector</th>
|
| 214 |
+
<th>savings</th>
|
| 215 |
+
</tr>
|
| 216 |
+
</thead>
|
| 217 |
+
<tbody>
|
| 218 |
+
<tr>
|
| 219 |
+
<th>0</th>
|
| 220 |
+
<td>0</td>
|
| 221 |
+
<td>5000</td>
|
| 222 |
+
<td>40.0</td>
|
| 223 |
+
<td>7000</td>
|
| 224 |
+
<td>1350.0</td>
|
| 225 |
+
<td>5.0</td>
|
| 226 |
+
<td>3</td>
|
| 227 |
+
<td>35</td>
|
| 228 |
+
<td>2000</td>
|
| 229 |
+
<td>0</td>
|
| 230 |
+
<td>0</td>
|
| 231 |
+
<td>1</td>
|
| 232 |
+
<td>1</td>
|
| 233 |
+
<td>4</td>
|
| 234 |
+
<td>0</td>
|
| 235 |
+
</tr>
|
| 236 |
+
</tbody>
|
| 237 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 238 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 239 |
+
0 & 0 & 5000 & 40.000000 & 7000 & 1350.000000 & 5.000000 & 3 & 35 & 2000 & 0 & 0 & 1 & 1 & 4 & 0 \\
|
| 240 |
+
\end{tabular}
|
| 241 |
+
","{'age': 35, 'amnt req': 5000, 'assets val': 7000, 'collateral': 2000, 'dec profit': 1350.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 40.0, 'purpose': 1, 'relatnshp': 1, 'savings': 0, 'sector': 4, 'sex': 0, 'xperience': 5.0}",A 35-year-old female is applying for a loan of 5000 cedis. The applicant works in agriculture sector and the purpose of the loan is not related to her business. The maturity period of the requested loan is 40.0 years. Her assets value is 7000 cedis and her declared profits (after tax) is 1350.0 cedis. Her educational background is primary and the number of years that she has been in business is 5.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 2000 cedis.
|
new_data/ghana-fewshot-6.csv
ADDED
|
@@ -0,0 +1,361 @@
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|
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|
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|
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|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
| 1 |
+
Unnamed: 0,sex,amnt req,amnt grnt,ration,maturity,assets val,dec profit,xperience,educatn,age,collateral,locatn,guarantor,relatnshp,purpose,sector,savings,target,great,list,text,html,latex,json,LIFT
|
| 2 |
+
1,1,1000,1000,0,30.0,3000,600.0,6.0,2,35,3000,0,0,0,1,1,0,Yes,"sex is 1, amnt req is 1000, maturity is 30.0, assets val is 3000, dec profit is 600.0, xperience is 6.0, educatn is 2, age is 35, collateral is 3000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 1, savings is 0","- sex : 1
|
| 3 |
+
- amnt req : 1000
|
| 4 |
+
- maturity : 30.0
|
| 5 |
+
- assets val : 3000
|
| 6 |
+
- dec profit : 600.0
|
| 7 |
+
- xperience : 6.0
|
| 8 |
+
- educatn : 2
|
| 9 |
+
- age : 35
|
| 10 |
+
- collateral : 3000
|
| 11 |
+
- locatn : 0
|
| 12 |
+
- guarantor : 0
|
| 13 |
+
- relatnshp : 0
|
| 14 |
+
- purpose : 1
|
| 15 |
+
- sector : 1
|
| 16 |
+
- savings : 0",The sex is 1. The amnt req is 1000. The maturity is 30.0. The assets val is 3000. The dec profit is 600.0. The xperience is 6.0. The educatn is 2. The age is 35. The collateral is 3000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 17 |
+
<thead>
|
| 18 |
+
<tr style=""text-align: right;"">
|
| 19 |
+
<th></th>
|
| 20 |
+
<th>sex</th>
|
| 21 |
+
<th>amnt req</th>
|
| 22 |
+
<th>maturity</th>
|
| 23 |
+
<th>assets val</th>
|
| 24 |
+
<th>dec profit</th>
|
| 25 |
+
<th>xperience</th>
|
| 26 |
+
<th>educatn</th>
|
| 27 |
+
<th>age</th>
|
| 28 |
+
<th>collateral</th>
|
| 29 |
+
<th>locatn</th>
|
| 30 |
+
<th>guarantor</th>
|
| 31 |
+
<th>relatnshp</th>
|
| 32 |
+
<th>purpose</th>
|
| 33 |
+
<th>sector</th>
|
| 34 |
+
<th>savings</th>
|
| 35 |
+
</tr>
|
| 36 |
+
</thead>
|
| 37 |
+
<tbody>
|
| 38 |
+
<tr>
|
| 39 |
+
<th>0</th>
|
| 40 |
+
<td>1</td>
|
| 41 |
+
<td>1000</td>
|
| 42 |
+
<td>30.0</td>
|
| 43 |
+
<td>3000</td>
|
| 44 |
+
<td>600.0</td>
|
| 45 |
+
<td>6.0</td>
|
| 46 |
+
<td>2</td>
|
| 47 |
+
<td>35</td>
|
| 48 |
+
<td>3000</td>
|
| 49 |
+
<td>0</td>
|
| 50 |
+
<td>0</td>
|
| 51 |
+
<td>0</td>
|
| 52 |
+
<td>1</td>
|
| 53 |
+
<td>1</td>
|
| 54 |
+
<td>0</td>
|
| 55 |
+
</tr>
|
| 56 |
+
</tbody>
|
| 57 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 58 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 59 |
+
0 & 1 & 1000 & 30.000000 & 3000 & 600.000000 & 6.000000 & 2 & 35 & 3000 & 0 & 0 & 0 & 1 & 1 & 0 \\
|
| 60 |
+
\end{tabular}
|
| 61 |
+
","{'age': 35, 'amnt req': 1000, 'assets val': 3000, 'collateral': 3000, 'dec profit': 600.0, 'educatn': 2, 'guarantor': 0, 'locatn': 0, 'maturity': 30.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 1, 'sex': 1, 'xperience': 6.0}",A 35-year-old male is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 30.0 years. His assets value is 3000 cedis and his declared profits (after tax) is 600.0 cedis. His educational background is secondary and the number of years that he has been in business is 6.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 3000 cedis.
|
| 62 |
+
0,0,2000,2000,0,36.0,4000,500.0,3.0,1,28,900,0,0,1,0,1,0,Yes,"sex is 0, amnt req is 2000, maturity is 36.0, assets val is 4000, dec profit is 500.0, xperience is 3.0, educatn is 1, age is 28, collateral is 900, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
|
| 63 |
+
- amnt req : 2000
|
| 64 |
+
- maturity : 36.0
|
| 65 |
+
- assets val : 4000
|
| 66 |
+
- dec profit : 500.0
|
| 67 |
+
- xperience : 3.0
|
| 68 |
+
- educatn : 1
|
| 69 |
+
- age : 28
|
| 70 |
+
- collateral : 900
|
| 71 |
+
- locatn : 0
|
| 72 |
+
- guarantor : 0
|
| 73 |
+
- relatnshp : 1
|
| 74 |
+
- purpose : 0
|
| 75 |
+
- sector : 1
|
| 76 |
+
- savings : 0",The sex is 0. The amnt req is 2000. The maturity is 36.0. The assets val is 4000. The dec profit is 500.0. The xperience is 3.0. The educatn is 1. The age is 28. The collateral is 900. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 77 |
+
<thead>
|
| 78 |
+
<tr style=""text-align: right;"">
|
| 79 |
+
<th></th>
|
| 80 |
+
<th>sex</th>
|
| 81 |
+
<th>amnt req</th>
|
| 82 |
+
<th>maturity</th>
|
| 83 |
+
<th>assets val</th>
|
| 84 |
+
<th>dec profit</th>
|
| 85 |
+
<th>xperience</th>
|
| 86 |
+
<th>educatn</th>
|
| 87 |
+
<th>age</th>
|
| 88 |
+
<th>collateral</th>
|
| 89 |
+
<th>locatn</th>
|
| 90 |
+
<th>guarantor</th>
|
| 91 |
+
<th>relatnshp</th>
|
| 92 |
+
<th>purpose</th>
|
| 93 |
+
<th>sector</th>
|
| 94 |
+
<th>savings</th>
|
| 95 |
+
</tr>
|
| 96 |
+
</thead>
|
| 97 |
+
<tbody>
|
| 98 |
+
<tr>
|
| 99 |
+
<th>0</th>
|
| 100 |
+
<td>0</td>
|
| 101 |
+
<td>2000</td>
|
| 102 |
+
<td>36.0</td>
|
| 103 |
+
<td>4000</td>
|
| 104 |
+
<td>500.0</td>
|
| 105 |
+
<td>3.0</td>
|
| 106 |
+
<td>1</td>
|
| 107 |
+
<td>28</td>
|
| 108 |
+
<td>900</td>
|
| 109 |
+
<td>0</td>
|
| 110 |
+
<td>0</td>
|
| 111 |
+
<td>1</td>
|
| 112 |
+
<td>0</td>
|
| 113 |
+
<td>1</td>
|
| 114 |
+
<td>0</td>
|
| 115 |
+
</tr>
|
| 116 |
+
</tbody>
|
| 117 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 118 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 119 |
+
0 & 0 & 2000 & 36.000000 & 4000 & 500.000000 & 3.000000 & 1 & 28 & 900 & 0 & 0 & 1 & 0 & 1 & 0 \\
|
| 120 |
+
\end{tabular}
|
| 121 |
+
","{'age': 28, 'amnt req': 2000, 'assets val': 4000, 'collateral': 900, 'dec profit': 500.0, 'educatn': 1, 'guarantor': 0, 'locatn': 0, 'maturity': 36.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 3.0}",A 28-year-old female is applying for a loan of 2000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 36.0 years. Her assets value is 4000 cedis and her declared profits (after tax) is 500.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 3.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 900 cedis.
|
| 122 |
+
4,1,2000,2000,0,60.0,2800,320.0,12.0,3,42,2000,0,0,0,1,5,0,Yes,"sex is 1, amnt req is 2000, maturity is 60.0, assets val is 2800, dec profit is 320.0, xperience is 12.0, educatn is 3, age is 42, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 5, savings is 0","- sex : 1
|
| 123 |
+
- amnt req : 2000
|
| 124 |
+
- maturity : 60.0
|
| 125 |
+
- assets val : 2800
|
| 126 |
+
- dec profit : 320.0
|
| 127 |
+
- xperience : 12.0
|
| 128 |
+
- educatn : 3
|
| 129 |
+
- age : 42
|
| 130 |
+
- collateral : 2000
|
| 131 |
+
- locatn : 0
|
| 132 |
+
- guarantor : 0
|
| 133 |
+
- relatnshp : 0
|
| 134 |
+
- purpose : 1
|
| 135 |
+
- sector : 5
|
| 136 |
+
- savings : 0",The sex is 1. The amnt req is 2000. The maturity is 60.0. The assets val is 2800. The dec profit is 320.0. The xperience is 12.0. The educatn is 3. The age is 42. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 5. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 137 |
+
<thead>
|
| 138 |
+
<tr style=""text-align: right;"">
|
| 139 |
+
<th></th>
|
| 140 |
+
<th>sex</th>
|
| 141 |
+
<th>amnt req</th>
|
| 142 |
+
<th>maturity</th>
|
| 143 |
+
<th>assets val</th>
|
| 144 |
+
<th>dec profit</th>
|
| 145 |
+
<th>xperience</th>
|
| 146 |
+
<th>educatn</th>
|
| 147 |
+
<th>age</th>
|
| 148 |
+
<th>collateral</th>
|
| 149 |
+
<th>locatn</th>
|
| 150 |
+
<th>guarantor</th>
|
| 151 |
+
<th>relatnshp</th>
|
| 152 |
+
<th>purpose</th>
|
| 153 |
+
<th>sector</th>
|
| 154 |
+
<th>savings</th>
|
| 155 |
+
</tr>
|
| 156 |
+
</thead>
|
| 157 |
+
<tbody>
|
| 158 |
+
<tr>
|
| 159 |
+
<th>0</th>
|
| 160 |
+
<td>1</td>
|
| 161 |
+
<td>2000</td>
|
| 162 |
+
<td>60.0</td>
|
| 163 |
+
<td>2800</td>
|
| 164 |
+
<td>320.0</td>
|
| 165 |
+
<td>12.0</td>
|
| 166 |
+
<td>3</td>
|
| 167 |
+
<td>42</td>
|
| 168 |
+
<td>2000</td>
|
| 169 |
+
<td>0</td>
|
| 170 |
+
<td>0</td>
|
| 171 |
+
<td>0</td>
|
| 172 |
+
<td>1</td>
|
| 173 |
+
<td>5</td>
|
| 174 |
+
<td>0</td>
|
| 175 |
+
</tr>
|
| 176 |
+
</tbody>
|
| 177 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 178 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 179 |
+
0 & 1 & 2000 & 60.000000 & 2800 & 320.000000 & 12.000000 & 3 & 42 & 2000 & 0 & 0 & 0 & 1 & 5 & 0 \\
|
| 180 |
+
\end{tabular}
|
| 181 |
+
","{'age': 42, 'amnt req': 2000, 'assets val': 2800, 'collateral': 2000, 'dec profit': 320.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 60.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 5, 'sex': 1, 'xperience': 12.0}",A 42-year-old male is applying for a loan of 2000 cedis. The applicant works in service sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 60.0 years. His assets value is 2800 cedis and his declared profits (after tax) is 320.0 cedis. His educational background is primary and the number of years that he has been in business is 12.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 2000 cedis.
|
| 182 |
+
2,0,5000,3000,1,40.0,7000,1350.0,5.0,3,35,2000,0,0,1,1,4,0,No,"sex is 0, amnt req is 5000, maturity is 40.0, assets val is 7000, dec profit is 1350.0, xperience is 5.0, educatn is 3, age is 35, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 1, sector is 4, savings is 0","- sex : 0
|
| 183 |
+
- amnt req : 5000
|
| 184 |
+
- maturity : 40.0
|
| 185 |
+
- assets val : 7000
|
| 186 |
+
- dec profit : 1350.0
|
| 187 |
+
- xperience : 5.0
|
| 188 |
+
- educatn : 3
|
| 189 |
+
- age : 35
|
| 190 |
+
- collateral : 2000
|
| 191 |
+
- locatn : 0
|
| 192 |
+
- guarantor : 0
|
| 193 |
+
- relatnshp : 1
|
| 194 |
+
- purpose : 1
|
| 195 |
+
- sector : 4
|
| 196 |
+
- savings : 0",The sex is 0. The amnt req is 5000. The maturity is 40.0. The assets val is 7000. The dec profit is 1350.0. The xperience is 5.0. The educatn is 3. The age is 35. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 1. The sector is 4. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 197 |
+
<thead>
|
| 198 |
+
<tr style=""text-align: right;"">
|
| 199 |
+
<th></th>
|
| 200 |
+
<th>sex</th>
|
| 201 |
+
<th>amnt req</th>
|
| 202 |
+
<th>maturity</th>
|
| 203 |
+
<th>assets val</th>
|
| 204 |
+
<th>dec profit</th>
|
| 205 |
+
<th>xperience</th>
|
| 206 |
+
<th>educatn</th>
|
| 207 |
+
<th>age</th>
|
| 208 |
+
<th>collateral</th>
|
| 209 |
+
<th>locatn</th>
|
| 210 |
+
<th>guarantor</th>
|
| 211 |
+
<th>relatnshp</th>
|
| 212 |
+
<th>purpose</th>
|
| 213 |
+
<th>sector</th>
|
| 214 |
+
<th>savings</th>
|
| 215 |
+
</tr>
|
| 216 |
+
</thead>
|
| 217 |
+
<tbody>
|
| 218 |
+
<tr>
|
| 219 |
+
<th>0</th>
|
| 220 |
+
<td>0</td>
|
| 221 |
+
<td>5000</td>
|
| 222 |
+
<td>40.0</td>
|
| 223 |
+
<td>7000</td>
|
| 224 |
+
<td>1350.0</td>
|
| 225 |
+
<td>5.0</td>
|
| 226 |
+
<td>3</td>
|
| 227 |
+
<td>35</td>
|
| 228 |
+
<td>2000</td>
|
| 229 |
+
<td>0</td>
|
| 230 |
+
<td>0</td>
|
| 231 |
+
<td>1</td>
|
| 232 |
+
<td>1</td>
|
| 233 |
+
<td>4</td>
|
| 234 |
+
<td>0</td>
|
| 235 |
+
</tr>
|
| 236 |
+
</tbody>
|
| 237 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 238 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 239 |
+
0 & 0 & 5000 & 40.000000 & 7000 & 1350.000000 & 5.000000 & 3 & 35 & 2000 & 0 & 0 & 1 & 1 & 4 & 0 \\
|
| 240 |
+
\end{tabular}
|
| 241 |
+
","{'age': 35, 'amnt req': 5000, 'assets val': 7000, 'collateral': 2000, 'dec profit': 1350.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 40.0, 'purpose': 1, 'relatnshp': 1, 'savings': 0, 'sector': 4, 'sex': 0, 'xperience': 5.0}",A 35-year-old female is applying for a loan of 5000 cedis. The applicant works in agriculture sector and the purpose of the loan is not related to her business. The maturity period of the requested loan is 40.0 years. Her assets value is 7000 cedis and her declared profits (after tax) is 1350.0 cedis. Her educational background is primary and the number of years that she has been in business is 5.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 2000 cedis.
|
| 242 |
+
6,1,1000,500,1,60.0,1000,120.0,8.0,3,56,1000,1,0,0,0,5,0,No,"sex is 1, amnt req is 1000, maturity is 60.0, assets val is 1000, dec profit is 120.0, xperience is 8.0, educatn is 3, age is 56, collateral is 1000, locatn is 1, guarantor is 0, relatnshp is 0, purpose is 0, sector is 5, savings is 0","- sex : 1
|
| 243 |
+
- amnt req : 1000
|
| 244 |
+
- maturity : 60.0
|
| 245 |
+
- assets val : 1000
|
| 246 |
+
- dec profit : 120.0
|
| 247 |
+
- xperience : 8.0
|
| 248 |
+
- educatn : 3
|
| 249 |
+
- age : 56
|
| 250 |
+
- collateral : 1000
|
| 251 |
+
- locatn : 1
|
| 252 |
+
- guarantor : 0
|
| 253 |
+
- relatnshp : 0
|
| 254 |
+
- purpose : 0
|
| 255 |
+
- sector : 5
|
| 256 |
+
- savings : 0",The sex is 1. The amnt req is 1000. The maturity is 60.0. The assets val is 1000. The dec profit is 120.0. The xperience is 8.0. The educatn is 3. The age is 56. The collateral is 1000. The locatn is 1. The guarantor is 0. The relatnshp is 0. The purpose is 0. The sector is 5. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 257 |
+
<thead>
|
| 258 |
+
<tr style=""text-align: right;"">
|
| 259 |
+
<th></th>
|
| 260 |
+
<th>sex</th>
|
| 261 |
+
<th>amnt req</th>
|
| 262 |
+
<th>maturity</th>
|
| 263 |
+
<th>assets val</th>
|
| 264 |
+
<th>dec profit</th>
|
| 265 |
+
<th>xperience</th>
|
| 266 |
+
<th>educatn</th>
|
| 267 |
+
<th>age</th>
|
| 268 |
+
<th>collateral</th>
|
| 269 |
+
<th>locatn</th>
|
| 270 |
+
<th>guarantor</th>
|
| 271 |
+
<th>relatnshp</th>
|
| 272 |
+
<th>purpose</th>
|
| 273 |
+
<th>sector</th>
|
| 274 |
+
<th>savings</th>
|
| 275 |
+
</tr>
|
| 276 |
+
</thead>
|
| 277 |
+
<tbody>
|
| 278 |
+
<tr>
|
| 279 |
+
<th>0</th>
|
| 280 |
+
<td>1</td>
|
| 281 |
+
<td>1000</td>
|
| 282 |
+
<td>60.0</td>
|
| 283 |
+
<td>1000</td>
|
| 284 |
+
<td>120.0</td>
|
| 285 |
+
<td>8.0</td>
|
| 286 |
+
<td>3</td>
|
| 287 |
+
<td>56</td>
|
| 288 |
+
<td>1000</td>
|
| 289 |
+
<td>1</td>
|
| 290 |
+
<td>0</td>
|
| 291 |
+
<td>0</td>
|
| 292 |
+
<td>0</td>
|
| 293 |
+
<td>5</td>
|
| 294 |
+
<td>0</td>
|
| 295 |
+
</tr>
|
| 296 |
+
</tbody>
|
| 297 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 298 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 299 |
+
0 & 1 & 1000 & 60.000000 & 1000 & 120.000000 & 8.000000 & 3 & 56 & 1000 & 1 & 0 & 0 & 0 & 5 & 0 \\
|
| 300 |
+
\end{tabular}
|
| 301 |
+
","{'age': 56, 'amnt req': 1000, 'assets val': 1000, 'collateral': 1000, 'dec profit': 120.0, 'educatn': 3, 'guarantor': 0, 'locatn': 1, 'maturity': 60.0, 'purpose': 0, 'relatnshp': 0, 'savings': 0, 'sector': 5, 'sex': 1, 'xperience': 8.0}",A 56-year-old male is applying for a loan of 1000 cedis. The applicant works in service sector and the purpose of the loan is related to his business. The maturity period of the requested loan is 60.0 years. His assets value is 1000 cedis and his declared profits (after tax) is 120.0 cedis. His educational background is primary and the number of years that he has been in business is 8.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He resides or have his business close to the bank. The value of his collateral is 1000 cedis.
|
| 302 |
+
3,0,1000,1000,0,24.0,2500,590.0,6.0,1,25,20000,1,0,1,0,1,0,Yes,"sex is 0, amnt req is 1000, maturity is 24.0, assets val is 2500, dec profit is 590.0, xperience is 6.0, educatn is 1, age is 25, collateral is 20000, locatn is 1, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
|
| 303 |
+
- amnt req : 1000
|
| 304 |
+
- maturity : 24.0
|
| 305 |
+
- assets val : 2500
|
| 306 |
+
- dec profit : 590.0
|
| 307 |
+
- xperience : 6.0
|
| 308 |
+
- educatn : 1
|
| 309 |
+
- age : 25
|
| 310 |
+
- collateral : 20000
|
| 311 |
+
- locatn : 1
|
| 312 |
+
- guarantor : 0
|
| 313 |
+
- relatnshp : 1
|
| 314 |
+
- purpose : 0
|
| 315 |
+
- sector : 1
|
| 316 |
+
- savings : 0",The sex is 0. The amnt req is 1000. The maturity is 24.0. The assets val is 2500. The dec profit is 590.0. The xperience is 6.0. The educatn is 1. The age is 25. The collateral is 20000. The locatn is 1. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 317 |
+
<thead>
|
| 318 |
+
<tr style=""text-align: right;"">
|
| 319 |
+
<th></th>
|
| 320 |
+
<th>sex</th>
|
| 321 |
+
<th>amnt req</th>
|
| 322 |
+
<th>maturity</th>
|
| 323 |
+
<th>assets val</th>
|
| 324 |
+
<th>dec profit</th>
|
| 325 |
+
<th>xperience</th>
|
| 326 |
+
<th>educatn</th>
|
| 327 |
+
<th>age</th>
|
| 328 |
+
<th>collateral</th>
|
| 329 |
+
<th>locatn</th>
|
| 330 |
+
<th>guarantor</th>
|
| 331 |
+
<th>relatnshp</th>
|
| 332 |
+
<th>purpose</th>
|
| 333 |
+
<th>sector</th>
|
| 334 |
+
<th>savings</th>
|
| 335 |
+
</tr>
|
| 336 |
+
</thead>
|
| 337 |
+
<tbody>
|
| 338 |
+
<tr>
|
| 339 |
+
<th>0</th>
|
| 340 |
+
<td>0</td>
|
| 341 |
+
<td>1000</td>
|
| 342 |
+
<td>24.0</td>
|
| 343 |
+
<td>2500</td>
|
| 344 |
+
<td>590.0</td>
|
| 345 |
+
<td>6.0</td>
|
| 346 |
+
<td>1</td>
|
| 347 |
+
<td>25</td>
|
| 348 |
+
<td>20000</td>
|
| 349 |
+
<td>1</td>
|
| 350 |
+
<td>0</td>
|
| 351 |
+
<td>1</td>
|
| 352 |
+
<td>0</td>
|
| 353 |
+
<td>1</td>
|
| 354 |
+
<td>0</td>
|
| 355 |
+
</tr>
|
| 356 |
+
</tbody>
|
| 357 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 358 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 359 |
+
0 & 0 & 1000 & 24.000000 & 2500 & 590.000000 & 6.000000 & 1 & 25 & 20000 & 1 & 0 & 1 & 0 & 1 & 0 \\
|
| 360 |
+
\end{tabular}
|
| 361 |
+
","{'age': 25, 'amnt req': 1000, 'assets val': 2500, 'collateral': 20000, 'dec profit': 590.0, 'educatn': 1, 'guarantor': 0, 'locatn': 1, 'maturity': 24.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 6.0}",A 25-year-old female is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 24.0 years. Her assets value is 2500 cedis and her declared profits (after tax) is 590.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 6.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She resides or have her business close to the bank. The value of her collateral is 20000 cedis.
|
new_data/ghana-fewshot-8.csv
ADDED
|
@@ -0,0 +1,481 @@
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|
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|
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|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
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|
| 1 |
+
Unnamed: 0,sex,amnt req,amnt grnt,ration,maturity,assets val,dec profit,xperience,educatn,age,collateral,locatn,guarantor,relatnshp,purpose,sector,savings,target,great,list,text,html,latex,json,LIFT
|
| 2 |
+
1,1,1000,1000,0,30.0,3000,600.0,6.0,2,35,3000,0,0,0,1,1,0,Yes,"sex is 1, amnt req is 1000, maturity is 30.0, assets val is 3000, dec profit is 600.0, xperience is 6.0, educatn is 2, age is 35, collateral is 3000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 1, savings is 0","- sex : 1
|
| 3 |
+
- amnt req : 1000
|
| 4 |
+
- maturity : 30.0
|
| 5 |
+
- assets val : 3000
|
| 6 |
+
- dec profit : 600.0
|
| 7 |
+
- xperience : 6.0
|
| 8 |
+
- educatn : 2
|
| 9 |
+
- age : 35
|
| 10 |
+
- collateral : 3000
|
| 11 |
+
- locatn : 0
|
| 12 |
+
- guarantor : 0
|
| 13 |
+
- relatnshp : 0
|
| 14 |
+
- purpose : 1
|
| 15 |
+
- sector : 1
|
| 16 |
+
- savings : 0",The sex is 1. The amnt req is 1000. The maturity is 30.0. The assets val is 3000. The dec profit is 600.0. The xperience is 6.0. The educatn is 2. The age is 35. The collateral is 3000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 17 |
+
<thead>
|
| 18 |
+
<tr style=""text-align: right;"">
|
| 19 |
+
<th></th>
|
| 20 |
+
<th>sex</th>
|
| 21 |
+
<th>amnt req</th>
|
| 22 |
+
<th>maturity</th>
|
| 23 |
+
<th>assets val</th>
|
| 24 |
+
<th>dec profit</th>
|
| 25 |
+
<th>xperience</th>
|
| 26 |
+
<th>educatn</th>
|
| 27 |
+
<th>age</th>
|
| 28 |
+
<th>collateral</th>
|
| 29 |
+
<th>locatn</th>
|
| 30 |
+
<th>guarantor</th>
|
| 31 |
+
<th>relatnshp</th>
|
| 32 |
+
<th>purpose</th>
|
| 33 |
+
<th>sector</th>
|
| 34 |
+
<th>savings</th>
|
| 35 |
+
</tr>
|
| 36 |
+
</thead>
|
| 37 |
+
<tbody>
|
| 38 |
+
<tr>
|
| 39 |
+
<th>0</th>
|
| 40 |
+
<td>1</td>
|
| 41 |
+
<td>1000</td>
|
| 42 |
+
<td>30.0</td>
|
| 43 |
+
<td>3000</td>
|
| 44 |
+
<td>600.0</td>
|
| 45 |
+
<td>6.0</td>
|
| 46 |
+
<td>2</td>
|
| 47 |
+
<td>35</td>
|
| 48 |
+
<td>3000</td>
|
| 49 |
+
<td>0</td>
|
| 50 |
+
<td>0</td>
|
| 51 |
+
<td>0</td>
|
| 52 |
+
<td>1</td>
|
| 53 |
+
<td>1</td>
|
| 54 |
+
<td>0</td>
|
| 55 |
+
</tr>
|
| 56 |
+
</tbody>
|
| 57 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 58 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 59 |
+
0 & 1 & 1000 & 30.000000 & 3000 & 600.000000 & 6.000000 & 2 & 35 & 3000 & 0 & 0 & 0 & 1 & 1 & 0 \\
|
| 60 |
+
\end{tabular}
|
| 61 |
+
","{'age': 35, 'amnt req': 1000, 'assets val': 3000, 'collateral': 3000, 'dec profit': 600.0, 'educatn': 2, 'guarantor': 0, 'locatn': 0, 'maturity': 30.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 1, 'sex': 1, 'xperience': 6.0}",A 35-year-old male is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 30.0 years. His assets value is 3000 cedis and his declared profits (after tax) is 600.0 cedis. His educational background is secondary and the number of years that he has been in business is 6.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 3000 cedis.
|
| 62 |
+
0,0,2000,2000,0,36.0,4000,500.0,3.0,1,28,900,0,0,1,0,1,0,Yes,"sex is 0, amnt req is 2000, maturity is 36.0, assets val is 4000, dec profit is 500.0, xperience is 3.0, educatn is 1, age is 28, collateral is 900, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
|
| 63 |
+
- amnt req : 2000
|
| 64 |
+
- maturity : 36.0
|
| 65 |
+
- assets val : 4000
|
| 66 |
+
- dec profit : 500.0
|
| 67 |
+
- xperience : 3.0
|
| 68 |
+
- educatn : 1
|
| 69 |
+
- age : 28
|
| 70 |
+
- collateral : 900
|
| 71 |
+
- locatn : 0
|
| 72 |
+
- guarantor : 0
|
| 73 |
+
- relatnshp : 1
|
| 74 |
+
- purpose : 0
|
| 75 |
+
- sector : 1
|
| 76 |
+
- savings : 0",The sex is 0. The amnt req is 2000. The maturity is 36.0. The assets val is 4000. The dec profit is 500.0. The xperience is 3.0. The educatn is 1. The age is 28. The collateral is 900. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 77 |
+
<thead>
|
| 78 |
+
<tr style=""text-align: right;"">
|
| 79 |
+
<th></th>
|
| 80 |
+
<th>sex</th>
|
| 81 |
+
<th>amnt req</th>
|
| 82 |
+
<th>maturity</th>
|
| 83 |
+
<th>assets val</th>
|
| 84 |
+
<th>dec profit</th>
|
| 85 |
+
<th>xperience</th>
|
| 86 |
+
<th>educatn</th>
|
| 87 |
+
<th>age</th>
|
| 88 |
+
<th>collateral</th>
|
| 89 |
+
<th>locatn</th>
|
| 90 |
+
<th>guarantor</th>
|
| 91 |
+
<th>relatnshp</th>
|
| 92 |
+
<th>purpose</th>
|
| 93 |
+
<th>sector</th>
|
| 94 |
+
<th>savings</th>
|
| 95 |
+
</tr>
|
| 96 |
+
</thead>
|
| 97 |
+
<tbody>
|
| 98 |
+
<tr>
|
| 99 |
+
<th>0</th>
|
| 100 |
+
<td>0</td>
|
| 101 |
+
<td>2000</td>
|
| 102 |
+
<td>36.0</td>
|
| 103 |
+
<td>4000</td>
|
| 104 |
+
<td>500.0</td>
|
| 105 |
+
<td>3.0</td>
|
| 106 |
+
<td>1</td>
|
| 107 |
+
<td>28</td>
|
| 108 |
+
<td>900</td>
|
| 109 |
+
<td>0</td>
|
| 110 |
+
<td>0</td>
|
| 111 |
+
<td>1</td>
|
| 112 |
+
<td>0</td>
|
| 113 |
+
<td>1</td>
|
| 114 |
+
<td>0</td>
|
| 115 |
+
</tr>
|
| 116 |
+
</tbody>
|
| 117 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 118 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 119 |
+
0 & 0 & 2000 & 36.000000 & 4000 & 500.000000 & 3.000000 & 1 & 28 & 900 & 0 & 0 & 1 & 0 & 1 & 0 \\
|
| 120 |
+
\end{tabular}
|
| 121 |
+
","{'age': 28, 'amnt req': 2000, 'assets val': 4000, 'collateral': 900, 'dec profit': 500.0, 'educatn': 1, 'guarantor': 0, 'locatn': 0, 'maturity': 36.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 3.0}",A 28-year-old female is applying for a loan of 2000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 36.0 years. Her assets value is 4000 cedis and her declared profits (after tax) is 500.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 3.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 900 cedis.
|
| 122 |
+
4,1,2000,2000,0,60.0,2800,320.0,12.0,3,42,2000,0,0,0,1,5,0,Yes,"sex is 1, amnt req is 2000, maturity is 60.0, assets val is 2800, dec profit is 320.0, xperience is 12.0, educatn is 3, age is 42, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 0, purpose is 1, sector is 5, savings is 0","- sex : 1
|
| 123 |
+
- amnt req : 2000
|
| 124 |
+
- maturity : 60.0
|
| 125 |
+
- assets val : 2800
|
| 126 |
+
- dec profit : 320.0
|
| 127 |
+
- xperience : 12.0
|
| 128 |
+
- educatn : 3
|
| 129 |
+
- age : 42
|
| 130 |
+
- collateral : 2000
|
| 131 |
+
- locatn : 0
|
| 132 |
+
- guarantor : 0
|
| 133 |
+
- relatnshp : 0
|
| 134 |
+
- purpose : 1
|
| 135 |
+
- sector : 5
|
| 136 |
+
- savings : 0",The sex is 1. The amnt req is 2000. The maturity is 60.0. The assets val is 2800. The dec profit is 320.0. The xperience is 12.0. The educatn is 3. The age is 42. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 0. The purpose is 1. The sector is 5. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 137 |
+
<thead>
|
| 138 |
+
<tr style=""text-align: right;"">
|
| 139 |
+
<th></th>
|
| 140 |
+
<th>sex</th>
|
| 141 |
+
<th>amnt req</th>
|
| 142 |
+
<th>maturity</th>
|
| 143 |
+
<th>assets val</th>
|
| 144 |
+
<th>dec profit</th>
|
| 145 |
+
<th>xperience</th>
|
| 146 |
+
<th>educatn</th>
|
| 147 |
+
<th>age</th>
|
| 148 |
+
<th>collateral</th>
|
| 149 |
+
<th>locatn</th>
|
| 150 |
+
<th>guarantor</th>
|
| 151 |
+
<th>relatnshp</th>
|
| 152 |
+
<th>purpose</th>
|
| 153 |
+
<th>sector</th>
|
| 154 |
+
<th>savings</th>
|
| 155 |
+
</tr>
|
| 156 |
+
</thead>
|
| 157 |
+
<tbody>
|
| 158 |
+
<tr>
|
| 159 |
+
<th>0</th>
|
| 160 |
+
<td>1</td>
|
| 161 |
+
<td>2000</td>
|
| 162 |
+
<td>60.0</td>
|
| 163 |
+
<td>2800</td>
|
| 164 |
+
<td>320.0</td>
|
| 165 |
+
<td>12.0</td>
|
| 166 |
+
<td>3</td>
|
| 167 |
+
<td>42</td>
|
| 168 |
+
<td>2000</td>
|
| 169 |
+
<td>0</td>
|
| 170 |
+
<td>0</td>
|
| 171 |
+
<td>0</td>
|
| 172 |
+
<td>1</td>
|
| 173 |
+
<td>5</td>
|
| 174 |
+
<td>0</td>
|
| 175 |
+
</tr>
|
| 176 |
+
</tbody>
|
| 177 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 178 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 179 |
+
0 & 1 & 2000 & 60.000000 & 2800 & 320.000000 & 12.000000 & 3 & 42 & 2000 & 0 & 0 & 0 & 1 & 5 & 0 \\
|
| 180 |
+
\end{tabular}
|
| 181 |
+
","{'age': 42, 'amnt req': 2000, 'assets val': 2800, 'collateral': 2000, 'dec profit': 320.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 60.0, 'purpose': 1, 'relatnshp': 0, 'savings': 0, 'sector': 5, 'sex': 1, 'xperience': 12.0}",A 42-year-old male is applying for a loan of 2000 cedis. The applicant works in service sector and the purpose of the loan is not related to his business. The maturity period of the requested loan is 60.0 years. His assets value is 2800 cedis and his declared profits (after tax) is 320.0 cedis. His educational background is primary and the number of years that he has been in business is 12.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He does not resides or have his business close to the bank. The value of his collateral is 2000 cedis.
|
| 182 |
+
2,0,5000,3000,1,40.0,7000,1350.0,5.0,3,35,2000,0,0,1,1,4,0,No,"sex is 0, amnt req is 5000, maturity is 40.0, assets val is 7000, dec profit is 1350.0, xperience is 5.0, educatn is 3, age is 35, collateral is 2000, locatn is 0, guarantor is 0, relatnshp is 1, purpose is 1, sector is 4, savings is 0","- sex : 0
|
| 183 |
+
- amnt req : 5000
|
| 184 |
+
- maturity : 40.0
|
| 185 |
+
- assets val : 7000
|
| 186 |
+
- dec profit : 1350.0
|
| 187 |
+
- xperience : 5.0
|
| 188 |
+
- educatn : 3
|
| 189 |
+
- age : 35
|
| 190 |
+
- collateral : 2000
|
| 191 |
+
- locatn : 0
|
| 192 |
+
- guarantor : 0
|
| 193 |
+
- relatnshp : 1
|
| 194 |
+
- purpose : 1
|
| 195 |
+
- sector : 4
|
| 196 |
+
- savings : 0",The sex is 0. The amnt req is 5000. The maturity is 40.0. The assets val is 7000. The dec profit is 1350.0. The xperience is 5.0. The educatn is 3. The age is 35. The collateral is 2000. The locatn is 0. The guarantor is 0. The relatnshp is 1. The purpose is 1. The sector is 4. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 197 |
+
<thead>
|
| 198 |
+
<tr style=""text-align: right;"">
|
| 199 |
+
<th></th>
|
| 200 |
+
<th>sex</th>
|
| 201 |
+
<th>amnt req</th>
|
| 202 |
+
<th>maturity</th>
|
| 203 |
+
<th>assets val</th>
|
| 204 |
+
<th>dec profit</th>
|
| 205 |
+
<th>xperience</th>
|
| 206 |
+
<th>educatn</th>
|
| 207 |
+
<th>age</th>
|
| 208 |
+
<th>collateral</th>
|
| 209 |
+
<th>locatn</th>
|
| 210 |
+
<th>guarantor</th>
|
| 211 |
+
<th>relatnshp</th>
|
| 212 |
+
<th>purpose</th>
|
| 213 |
+
<th>sector</th>
|
| 214 |
+
<th>savings</th>
|
| 215 |
+
</tr>
|
| 216 |
+
</thead>
|
| 217 |
+
<tbody>
|
| 218 |
+
<tr>
|
| 219 |
+
<th>0</th>
|
| 220 |
+
<td>0</td>
|
| 221 |
+
<td>5000</td>
|
| 222 |
+
<td>40.0</td>
|
| 223 |
+
<td>7000</td>
|
| 224 |
+
<td>1350.0</td>
|
| 225 |
+
<td>5.0</td>
|
| 226 |
+
<td>3</td>
|
| 227 |
+
<td>35</td>
|
| 228 |
+
<td>2000</td>
|
| 229 |
+
<td>0</td>
|
| 230 |
+
<td>0</td>
|
| 231 |
+
<td>1</td>
|
| 232 |
+
<td>1</td>
|
| 233 |
+
<td>4</td>
|
| 234 |
+
<td>0</td>
|
| 235 |
+
</tr>
|
| 236 |
+
</tbody>
|
| 237 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 238 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 239 |
+
0 & 0 & 5000 & 40.000000 & 7000 & 1350.000000 & 5.000000 & 3 & 35 & 2000 & 0 & 0 & 1 & 1 & 4 & 0 \\
|
| 240 |
+
\end{tabular}
|
| 241 |
+
","{'age': 35, 'amnt req': 5000, 'assets val': 7000, 'collateral': 2000, 'dec profit': 1350.0, 'educatn': 3, 'guarantor': 0, 'locatn': 0, 'maturity': 40.0, 'purpose': 1, 'relatnshp': 1, 'savings': 0, 'sector': 4, 'sex': 0, 'xperience': 5.0}",A 35-year-old female is applying for a loan of 5000 cedis. The applicant works in agriculture sector and the purpose of the loan is not related to her business. The maturity period of the requested loan is 40.0 years. Her assets value is 7000 cedis and her declared profits (after tax) is 1350.0 cedis. Her educational background is primary and the number of years that she has been in business is 5.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She does not resides or have her business close to the bank. The value of her collateral is 2000 cedis.
|
| 242 |
+
6,1,1000,500,1,60.0,1000,120.0,8.0,3,56,1000,1,0,0,0,5,0,No,"sex is 1, amnt req is 1000, maturity is 60.0, assets val is 1000, dec profit is 120.0, xperience is 8.0, educatn is 3, age is 56, collateral is 1000, locatn is 1, guarantor is 0, relatnshp is 0, purpose is 0, sector is 5, savings is 0","- sex : 1
|
| 243 |
+
- amnt req : 1000
|
| 244 |
+
- maturity : 60.0
|
| 245 |
+
- assets val : 1000
|
| 246 |
+
- dec profit : 120.0
|
| 247 |
+
- xperience : 8.0
|
| 248 |
+
- educatn : 3
|
| 249 |
+
- age : 56
|
| 250 |
+
- collateral : 1000
|
| 251 |
+
- locatn : 1
|
| 252 |
+
- guarantor : 0
|
| 253 |
+
- relatnshp : 0
|
| 254 |
+
- purpose : 0
|
| 255 |
+
- sector : 5
|
| 256 |
+
- savings : 0",The sex is 1. The amnt req is 1000. The maturity is 60.0. The assets val is 1000. The dec profit is 120.0. The xperience is 8.0. The educatn is 3. The age is 56. The collateral is 1000. The locatn is 1. The guarantor is 0. The relatnshp is 0. The purpose is 0. The sector is 5. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 257 |
+
<thead>
|
| 258 |
+
<tr style=""text-align: right;"">
|
| 259 |
+
<th></th>
|
| 260 |
+
<th>sex</th>
|
| 261 |
+
<th>amnt req</th>
|
| 262 |
+
<th>maturity</th>
|
| 263 |
+
<th>assets val</th>
|
| 264 |
+
<th>dec profit</th>
|
| 265 |
+
<th>xperience</th>
|
| 266 |
+
<th>educatn</th>
|
| 267 |
+
<th>age</th>
|
| 268 |
+
<th>collateral</th>
|
| 269 |
+
<th>locatn</th>
|
| 270 |
+
<th>guarantor</th>
|
| 271 |
+
<th>relatnshp</th>
|
| 272 |
+
<th>purpose</th>
|
| 273 |
+
<th>sector</th>
|
| 274 |
+
<th>savings</th>
|
| 275 |
+
</tr>
|
| 276 |
+
</thead>
|
| 277 |
+
<tbody>
|
| 278 |
+
<tr>
|
| 279 |
+
<th>0</th>
|
| 280 |
+
<td>1</td>
|
| 281 |
+
<td>1000</td>
|
| 282 |
+
<td>60.0</td>
|
| 283 |
+
<td>1000</td>
|
| 284 |
+
<td>120.0</td>
|
| 285 |
+
<td>8.0</td>
|
| 286 |
+
<td>3</td>
|
| 287 |
+
<td>56</td>
|
| 288 |
+
<td>1000</td>
|
| 289 |
+
<td>1</td>
|
| 290 |
+
<td>0</td>
|
| 291 |
+
<td>0</td>
|
| 292 |
+
<td>0</td>
|
| 293 |
+
<td>5</td>
|
| 294 |
+
<td>0</td>
|
| 295 |
+
</tr>
|
| 296 |
+
</tbody>
|
| 297 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 298 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 299 |
+
0 & 1 & 1000 & 60.000000 & 1000 & 120.000000 & 8.000000 & 3 & 56 & 1000 & 1 & 0 & 0 & 0 & 5 & 0 \\
|
| 300 |
+
\end{tabular}
|
| 301 |
+
","{'age': 56, 'amnt req': 1000, 'assets val': 1000, 'collateral': 1000, 'dec profit': 120.0, 'educatn': 3, 'guarantor': 0, 'locatn': 1, 'maturity': 60.0, 'purpose': 0, 'relatnshp': 0, 'savings': 0, 'sector': 5, 'sex': 1, 'xperience': 8.0}",A 56-year-old male is applying for a loan of 1000 cedis. The applicant works in service sector and the purpose of the loan is related to his business. The maturity period of the requested loan is 60.0 years. His assets value is 1000 cedis and his declared profits (after tax) is 120.0 cedis. His educational background is primary and the number of years that he has been in business is 8.0. He did not provide any guarantor and this is not his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He resides or have his business close to the bank. The value of his collateral is 1000 cedis.
|
| 302 |
+
3,0,1000,1000,0,24.0,2500,590.0,6.0,1,25,20000,1,0,1,0,1,0,Yes,"sex is 0, amnt req is 1000, maturity is 24.0, assets val is 2500, dec profit is 590.0, xperience is 6.0, educatn is 1, age is 25, collateral is 20000, locatn is 1, guarantor is 0, relatnshp is 1, purpose is 0, sector is 1, savings is 0","- sex : 0
|
| 303 |
+
- amnt req : 1000
|
| 304 |
+
- maturity : 24.0
|
| 305 |
+
- assets val : 2500
|
| 306 |
+
- dec profit : 590.0
|
| 307 |
+
- xperience : 6.0
|
| 308 |
+
- educatn : 1
|
| 309 |
+
- age : 25
|
| 310 |
+
- collateral : 20000
|
| 311 |
+
- locatn : 1
|
| 312 |
+
- guarantor : 0
|
| 313 |
+
- relatnshp : 1
|
| 314 |
+
- purpose : 0
|
| 315 |
+
- sector : 1
|
| 316 |
+
- savings : 0",The sex is 0. The amnt req is 1000. The maturity is 24.0. The assets val is 2500. The dec profit is 590.0. The xperience is 6.0. The educatn is 1. The age is 25. The collateral is 20000. The locatn is 1. The guarantor is 0. The relatnshp is 1. The purpose is 0. The sector is 1. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 317 |
+
<thead>
|
| 318 |
+
<tr style=""text-align: right;"">
|
| 319 |
+
<th></th>
|
| 320 |
+
<th>sex</th>
|
| 321 |
+
<th>amnt req</th>
|
| 322 |
+
<th>maturity</th>
|
| 323 |
+
<th>assets val</th>
|
| 324 |
+
<th>dec profit</th>
|
| 325 |
+
<th>xperience</th>
|
| 326 |
+
<th>educatn</th>
|
| 327 |
+
<th>age</th>
|
| 328 |
+
<th>collateral</th>
|
| 329 |
+
<th>locatn</th>
|
| 330 |
+
<th>guarantor</th>
|
| 331 |
+
<th>relatnshp</th>
|
| 332 |
+
<th>purpose</th>
|
| 333 |
+
<th>sector</th>
|
| 334 |
+
<th>savings</th>
|
| 335 |
+
</tr>
|
| 336 |
+
</thead>
|
| 337 |
+
<tbody>
|
| 338 |
+
<tr>
|
| 339 |
+
<th>0</th>
|
| 340 |
+
<td>0</td>
|
| 341 |
+
<td>1000</td>
|
| 342 |
+
<td>24.0</td>
|
| 343 |
+
<td>2500</td>
|
| 344 |
+
<td>590.0</td>
|
| 345 |
+
<td>6.0</td>
|
| 346 |
+
<td>1</td>
|
| 347 |
+
<td>25</td>
|
| 348 |
+
<td>20000</td>
|
| 349 |
+
<td>1</td>
|
| 350 |
+
<td>0</td>
|
| 351 |
+
<td>1</td>
|
| 352 |
+
<td>0</td>
|
| 353 |
+
<td>1</td>
|
| 354 |
+
<td>0</td>
|
| 355 |
+
</tr>
|
| 356 |
+
</tbody>
|
| 357 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 358 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 359 |
+
0 & 0 & 1000 & 24.000000 & 2500 & 590.000000 & 6.000000 & 1 & 25 & 20000 & 1 & 0 & 1 & 0 & 1 & 0 \\
|
| 360 |
+
\end{tabular}
|
| 361 |
+
","{'age': 25, 'amnt req': 1000, 'assets val': 2500, 'collateral': 20000, 'dec profit': 590.0, 'educatn': 1, 'guarantor': 0, 'locatn': 1, 'maturity': 24.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 1, 'sex': 0, 'xperience': 6.0}",A 25-year-old female is applying for a loan of 1000 cedis. The applicant works in commerce sector and the purpose of the loan is related to her business. The maturity period of the requested loan is 24.0 years. Her assets value is 2500 cedis and her declared profits (after tax) is 590.0 cedis. Her educational background is tertiary and the number of years that she has been in business is 6.0. She did not provide any guarantor and this is her first time requesting for a loan at the bank. She does not have non-mandatory savings with the bank. She resides or have her business close to the bank. The value of her collateral is 20000 cedis.
|
| 362 |
+
7,1,12000,10000,1,30.0,10000,560.0,2.0,3,38,9000,1,1,1,0,4,0,No,"sex is 1, amnt req is 12000, maturity is 30.0, assets val is 10000, dec profit is 560.0, xperience is 2.0, educatn is 3, age is 38, collateral is 9000, locatn is 1, guarantor is 1, relatnshp is 1, purpose is 0, sector is 4, savings is 0","- sex : 1
|
| 363 |
+
- amnt req : 12000
|
| 364 |
+
- maturity : 30.0
|
| 365 |
+
- assets val : 10000
|
| 366 |
+
- dec profit : 560.0
|
| 367 |
+
- xperience : 2.0
|
| 368 |
+
- educatn : 3
|
| 369 |
+
- age : 38
|
| 370 |
+
- collateral : 9000
|
| 371 |
+
- locatn : 1
|
| 372 |
+
- guarantor : 1
|
| 373 |
+
- relatnshp : 1
|
| 374 |
+
- purpose : 0
|
| 375 |
+
- sector : 4
|
| 376 |
+
- savings : 0",The sex is 1. The amnt req is 12000. The maturity is 30.0. The assets val is 10000. The dec profit is 560.0. The xperience is 2.0. The educatn is 3. The age is 38. The collateral is 9000. The locatn is 1. The guarantor is 1. The relatnshp is 1. The purpose is 0. The sector is 4. The savings is 0,"<table border=""1"" class=""dataframe"">
|
| 377 |
+
<thead>
|
| 378 |
+
<tr style=""text-align: right;"">
|
| 379 |
+
<th></th>
|
| 380 |
+
<th>sex</th>
|
| 381 |
+
<th>amnt req</th>
|
| 382 |
+
<th>maturity</th>
|
| 383 |
+
<th>assets val</th>
|
| 384 |
+
<th>dec profit</th>
|
| 385 |
+
<th>xperience</th>
|
| 386 |
+
<th>educatn</th>
|
| 387 |
+
<th>age</th>
|
| 388 |
+
<th>collateral</th>
|
| 389 |
+
<th>locatn</th>
|
| 390 |
+
<th>guarantor</th>
|
| 391 |
+
<th>relatnshp</th>
|
| 392 |
+
<th>purpose</th>
|
| 393 |
+
<th>sector</th>
|
| 394 |
+
<th>savings</th>
|
| 395 |
+
</tr>
|
| 396 |
+
</thead>
|
| 397 |
+
<tbody>
|
| 398 |
+
<tr>
|
| 399 |
+
<th>0</th>
|
| 400 |
+
<td>1</td>
|
| 401 |
+
<td>12000</td>
|
| 402 |
+
<td>30.0</td>
|
| 403 |
+
<td>10000</td>
|
| 404 |
+
<td>560.0</td>
|
| 405 |
+
<td>2.0</td>
|
| 406 |
+
<td>3</td>
|
| 407 |
+
<td>38</td>
|
| 408 |
+
<td>9000</td>
|
| 409 |
+
<td>1</td>
|
| 410 |
+
<td>1</td>
|
| 411 |
+
<td>1</td>
|
| 412 |
+
<td>0</td>
|
| 413 |
+
<td>4</td>
|
| 414 |
+
<td>0</td>
|
| 415 |
+
</tr>
|
| 416 |
+
</tbody>
|
| 417 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 418 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 419 |
+
0 & 1 & 12000 & 30.000000 & 10000 & 560.000000 & 2.000000 & 3 & 38 & 9000 & 1 & 1 & 1 & 0 & 4 & 0 \\
|
| 420 |
+
\end{tabular}
|
| 421 |
+
","{'age': 38, 'amnt req': 12000, 'assets val': 10000, 'collateral': 9000, 'dec profit': 560.0, 'educatn': 3, 'guarantor': 1, 'locatn': 1, 'maturity': 30.0, 'purpose': 0, 'relatnshp': 1, 'savings': 0, 'sector': 4, 'sex': 1, 'xperience': 2.0}",A 38-year-old male is applying for a loan of 12000 cedis. The applicant works in agriculture sector and the purpose of the loan is related to his business. The maturity period of the requested loan is 30.0 years. His assets value is 10000 cedis and his declared profits (after tax) is 560.0 cedis. His educational background is primary and the number of years that he has been in business is 2.0. He provided a guarantor and this is his first time requesting for a loan at the bank. He does not have non-mandatory savings with the bank. He resides or have his business close to the bank. The value of his collateral is 9000 cedis.
|
| 422 |
+
5,0,9000,9000,0,30.0,5000,320.0,9.0,4,38,9000,1,1,1,1,1,1,Yes,"sex is 0, amnt req is 9000, maturity is 30.0, assets val is 5000, dec profit is 320.0, xperience is 9.0, educatn is 4, age is 38, collateral is 9000, locatn is 1, guarantor is 1, relatnshp is 1, purpose is 1, sector is 1, savings is 1","- sex : 0
|
| 423 |
+
- amnt req : 9000
|
| 424 |
+
- maturity : 30.0
|
| 425 |
+
- assets val : 5000
|
| 426 |
+
- dec profit : 320.0
|
| 427 |
+
- xperience : 9.0
|
| 428 |
+
- educatn : 4
|
| 429 |
+
- age : 38
|
| 430 |
+
- collateral : 9000
|
| 431 |
+
- locatn : 1
|
| 432 |
+
- guarantor : 1
|
| 433 |
+
- relatnshp : 1
|
| 434 |
+
- purpose : 1
|
| 435 |
+
- sector : 1
|
| 436 |
+
- savings : 1",The sex is 0. The amnt req is 9000. The maturity is 30.0. The assets val is 5000. The dec profit is 320.0. The xperience is 9.0. The educatn is 4. The age is 38. The collateral is 9000. The locatn is 1. The guarantor is 1. The relatnshp is 1. The purpose is 1. The sector is 1. The savings is 1,"<table border=""1"" class=""dataframe"">
|
| 437 |
+
<thead>
|
| 438 |
+
<tr style=""text-align: right;"">
|
| 439 |
+
<th></th>
|
| 440 |
+
<th>sex</th>
|
| 441 |
+
<th>amnt req</th>
|
| 442 |
+
<th>maturity</th>
|
| 443 |
+
<th>assets val</th>
|
| 444 |
+
<th>dec profit</th>
|
| 445 |
+
<th>xperience</th>
|
| 446 |
+
<th>educatn</th>
|
| 447 |
+
<th>age</th>
|
| 448 |
+
<th>collateral</th>
|
| 449 |
+
<th>locatn</th>
|
| 450 |
+
<th>guarantor</th>
|
| 451 |
+
<th>relatnshp</th>
|
| 452 |
+
<th>purpose</th>
|
| 453 |
+
<th>sector</th>
|
| 454 |
+
<th>savings</th>
|
| 455 |
+
</tr>
|
| 456 |
+
</thead>
|
| 457 |
+
<tbody>
|
| 458 |
+
<tr>
|
| 459 |
+
<th>0</th>
|
| 460 |
+
<td>0</td>
|
| 461 |
+
<td>9000</td>
|
| 462 |
+
<td>30.0</td>
|
| 463 |
+
<td>5000</td>
|
| 464 |
+
<td>320.0</td>
|
| 465 |
+
<td>9.0</td>
|
| 466 |
+
<td>4</td>
|
| 467 |
+
<td>38</td>
|
| 468 |
+
<td>9000</td>
|
| 469 |
+
<td>1</td>
|
| 470 |
+
<td>1</td>
|
| 471 |
+
<td>1</td>
|
| 472 |
+
<td>1</td>
|
| 473 |
+
<td>1</td>
|
| 474 |
+
<td>1</td>
|
| 475 |
+
</tr>
|
| 476 |
+
</tbody>
|
| 477 |
+
</table>","\begin{tabular}{lrrrrrrrrrrrrrrr}
|
| 478 |
+
& sex & amnt req & maturity & assets val & dec profit & xperience & educatn & age & collateral & locatn & guarantor & relatnshp & purpose & sector & savings \\
|
| 479 |
+
0 & 0 & 9000 & 30.000000 & 5000 & 320.000000 & 9.000000 & 4 & 38 & 9000 & 1 & 1 & 1 & 1 & 1 & 1 \\
|
| 480 |
+
\end{tabular}
|
| 481 |
+
","{'age': 38, 'amnt req': 9000, 'assets val': 5000, 'collateral': 9000, 'dec profit': 320.0, 'educatn': 4, 'guarantor': 1, 'locatn': 1, 'maturity': 30.0, 'purpose': 1, 'relatnshp': 1, 'savings': 1, 'sector': 1, 'sex': 0, 'xperience': 9.0}",A 38-year-old female is applying for a loan of 9000 cedis. The applicant works in commerce sector and the purpose of the loan is not related to her business. The maturity period of the requested loan is 30.0 years. Her assets value is 5000 cedis and her declared profits (after tax) is 320.0 cedis. Her educational background is illiterate and the number of years that she has been in business is 9.0. She provided a guarantor and this is her first time requesting for a loan at the bank. She has non-mandatory savings with the bank. She resides or have her business close to the bank. The value of her collateral is 9000 cedis.
|
new_data/loan_pred-fewshot-2.csv
ADDED
|
@@ -0,0 +1,97 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Unnamed: 0,Gender,Loan_ID,Gender.1,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status,great,list,text,html,latex,json,LIFT
|
| 2 |
+
0,Male,LP001273,Male,Yes,0,Graduate,No,6000,2250.0,265.0,360.0,,Semiurban,N,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 6000, CoapplicantIncome is 2250.0, LoanAmount is 265.0, Loan_Amount_Term is 360.0, Credit_History is None, Property_Area is Semiurban","- Gender : Male
|
| 3 |
+
- Married : Yes
|
| 4 |
+
- Dependents : 0
|
| 5 |
+
- Education : Graduate
|
| 6 |
+
- Self_Employed : No
|
| 7 |
+
- ApplicantIncome : 6000
|
| 8 |
+
- CoapplicantIncome : 2250.0
|
| 9 |
+
- LoanAmount : 265.0
|
| 10 |
+
- Loan_Amount_Term : 360.0
|
| 11 |
+
- Credit_History : None
|
| 12 |
+
- Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6000. The CoapplicantIncome is 2250.0. The LoanAmount is 265.0. The Loan_Amount_Term is 360.0. The Credit_History is None. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 13 |
+
<thead>
|
| 14 |
+
<tr style=""text-align: right;"">
|
| 15 |
+
<th></th>
|
| 16 |
+
<th>Gender</th>
|
| 17 |
+
<th>Married</th>
|
| 18 |
+
<th>Dependents</th>
|
| 19 |
+
<th>Education</th>
|
| 20 |
+
<th>Self_Employed</th>
|
| 21 |
+
<th>ApplicantIncome</th>
|
| 22 |
+
<th>CoapplicantIncome</th>
|
| 23 |
+
<th>LoanAmount</th>
|
| 24 |
+
<th>Loan_Amount_Term</th>
|
| 25 |
+
<th>Credit_History</th>
|
| 26 |
+
<th>Property_Area</th>
|
| 27 |
+
</tr>
|
| 28 |
+
</thead>
|
| 29 |
+
<tbody>
|
| 30 |
+
<tr>
|
| 31 |
+
<th>0</th>
|
| 32 |
+
<td>Male</td>
|
| 33 |
+
<td>Yes</td>
|
| 34 |
+
<td>0</td>
|
| 35 |
+
<td>Graduate</td>
|
| 36 |
+
<td>No</td>
|
| 37 |
+
<td>6000</td>
|
| 38 |
+
<td>2250.0</td>
|
| 39 |
+
<td>265.0</td>
|
| 40 |
+
<td>360.0</td>
|
| 41 |
+
<td>None</td>
|
| 42 |
+
<td>Semiurban</td>
|
| 43 |
+
</tr>
|
| 44 |
+
</tbody>
|
| 45 |
+
</table>","\begin{tabular}{llllllrrrrll}
|
| 46 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 47 |
+
0 & Male & Yes & 0 & Graduate & No & 6000 & 2250.000000 & 265.000000 & 360.000000 & None & Semiurban \\
|
| 48 |
+
\end{tabular}
|
| 49 |
+
","{'ApplicantIncome': 6000, 'CoapplicantIncome': 2250.0, 'Credit_History': None, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 265.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 265.0 dollars for 30.0 months. He has unknown credit history. He is a graduate and is not self employed. He earns 6000 dollars and his co-applicant earns 2250.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
|
| 50 |
+
8,Female,LP001639,Female,Yes,0,Graduate,No,3625,0.0,108.0,360.0,1.0,Semiurban,Y,"Gender is Female, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 3625, CoapplicantIncome is 0.0, LoanAmount is 108.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Female
|
| 51 |
+
- Married : Yes
|
| 52 |
+
- Dependents : 0
|
| 53 |
+
- Education : Graduate
|
| 54 |
+
- Self_Employed : No
|
| 55 |
+
- ApplicantIncome : 3625
|
| 56 |
+
- CoapplicantIncome : 0.0
|
| 57 |
+
- LoanAmount : 108.0
|
| 58 |
+
- Loan_Amount_Term : 360.0
|
| 59 |
+
- Credit_History : 1.0
|
| 60 |
+
- Property_Area : Semiurban",The Gender is Female. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 3625. The CoapplicantIncome is 0.0. The LoanAmount is 108.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 61 |
+
<thead>
|
| 62 |
+
<tr style=""text-align: right;"">
|
| 63 |
+
<th></th>
|
| 64 |
+
<th>Gender</th>
|
| 65 |
+
<th>Married</th>
|
| 66 |
+
<th>Dependents</th>
|
| 67 |
+
<th>Education</th>
|
| 68 |
+
<th>Self_Employed</th>
|
| 69 |
+
<th>ApplicantIncome</th>
|
| 70 |
+
<th>CoapplicantIncome</th>
|
| 71 |
+
<th>LoanAmount</th>
|
| 72 |
+
<th>Loan_Amount_Term</th>
|
| 73 |
+
<th>Credit_History</th>
|
| 74 |
+
<th>Property_Area</th>
|
| 75 |
+
</tr>
|
| 76 |
+
</thead>
|
| 77 |
+
<tbody>
|
| 78 |
+
<tr>
|
| 79 |
+
<th>0</th>
|
| 80 |
+
<td>Female</td>
|
| 81 |
+
<td>Yes</td>
|
| 82 |
+
<td>0</td>
|
| 83 |
+
<td>Graduate</td>
|
| 84 |
+
<td>No</td>
|
| 85 |
+
<td>3625</td>
|
| 86 |
+
<td>0.0</td>
|
| 87 |
+
<td>108.0</td>
|
| 88 |
+
<td>360.0</td>
|
| 89 |
+
<td>1.0</td>
|
| 90 |
+
<td>Semiurban</td>
|
| 91 |
+
</tr>
|
| 92 |
+
</tbody>
|
| 93 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 94 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 95 |
+
0 & Female & Yes & 0 & Graduate & No & 3625 & 0.000000 & 108.000000 & 360.000000 & 1.000000 & Semiurban \\
|
| 96 |
+
\end{tabular}
|
| 97 |
+
","{'ApplicantIncome': 3625, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 108.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married female individual is applying for a loan of 108.0 dollars for 30.0 months. She has a credit history. She is a graduate and is not self employed. She earns 3625 dollars. She has no person that she is liable to provide maintenance for. She lives in semiurban area.
|
new_data/loan_pred-fewshot-4.csv
ADDED
|
@@ -0,0 +1,193 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Unnamed: 0,Gender,Loan_ID,Gender.1,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status,great,list,text,html,latex,json,LIFT
|
| 2 |
+
0,Male,LP001273,Male,Yes,0,Graduate,No,6000,2250.0,265.0,360.0,,Semiurban,N,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 6000, CoapplicantIncome is 2250.0, LoanAmount is 265.0, Loan_Amount_Term is 360.0, Credit_History is None, Property_Area is Semiurban","- Gender : Male
|
| 3 |
+
- Married : Yes
|
| 4 |
+
- Dependents : 0
|
| 5 |
+
- Education : Graduate
|
| 6 |
+
- Self_Employed : No
|
| 7 |
+
- ApplicantIncome : 6000
|
| 8 |
+
- CoapplicantIncome : 2250.0
|
| 9 |
+
- LoanAmount : 265.0
|
| 10 |
+
- Loan_Amount_Term : 360.0
|
| 11 |
+
- Credit_History : None
|
| 12 |
+
- Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6000. The CoapplicantIncome is 2250.0. The LoanAmount is 265.0. The Loan_Amount_Term is 360.0. The Credit_History is None. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 13 |
+
<thead>
|
| 14 |
+
<tr style=""text-align: right;"">
|
| 15 |
+
<th></th>
|
| 16 |
+
<th>Gender</th>
|
| 17 |
+
<th>Married</th>
|
| 18 |
+
<th>Dependents</th>
|
| 19 |
+
<th>Education</th>
|
| 20 |
+
<th>Self_Employed</th>
|
| 21 |
+
<th>ApplicantIncome</th>
|
| 22 |
+
<th>CoapplicantIncome</th>
|
| 23 |
+
<th>LoanAmount</th>
|
| 24 |
+
<th>Loan_Amount_Term</th>
|
| 25 |
+
<th>Credit_History</th>
|
| 26 |
+
<th>Property_Area</th>
|
| 27 |
+
</tr>
|
| 28 |
+
</thead>
|
| 29 |
+
<tbody>
|
| 30 |
+
<tr>
|
| 31 |
+
<th>0</th>
|
| 32 |
+
<td>Male</td>
|
| 33 |
+
<td>Yes</td>
|
| 34 |
+
<td>0</td>
|
| 35 |
+
<td>Graduate</td>
|
| 36 |
+
<td>No</td>
|
| 37 |
+
<td>6000</td>
|
| 38 |
+
<td>2250.0</td>
|
| 39 |
+
<td>265.0</td>
|
| 40 |
+
<td>360.0</td>
|
| 41 |
+
<td>None</td>
|
| 42 |
+
<td>Semiurban</td>
|
| 43 |
+
</tr>
|
| 44 |
+
</tbody>
|
| 45 |
+
</table>","\begin{tabular}{llllllrrrrll}
|
| 46 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 47 |
+
0 & Male & Yes & 0 & Graduate & No & 6000 & 2250.000000 & 265.000000 & 360.000000 & None & Semiurban \\
|
| 48 |
+
\end{tabular}
|
| 49 |
+
","{'ApplicantIncome': 6000, 'CoapplicantIncome': 2250.0, 'Credit_History': None, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 265.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 265.0 dollars for 30.0 months. He has unknown credit history. He is a graduate and is not self employed. He earns 6000 dollars and his co-applicant earns 2250.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
|
| 50 |
+
8,Female,LP001639,Female,Yes,0,Graduate,No,3625,0.0,108.0,360.0,1.0,Semiurban,Y,"Gender is Female, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 3625, CoapplicantIncome is 0.0, LoanAmount is 108.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Female
|
| 51 |
+
- Married : Yes
|
| 52 |
+
- Dependents : 0
|
| 53 |
+
- Education : Graduate
|
| 54 |
+
- Self_Employed : No
|
| 55 |
+
- ApplicantIncome : 3625
|
| 56 |
+
- CoapplicantIncome : 0.0
|
| 57 |
+
- LoanAmount : 108.0
|
| 58 |
+
- Loan_Amount_Term : 360.0
|
| 59 |
+
- Credit_History : 1.0
|
| 60 |
+
- Property_Area : Semiurban",The Gender is Female. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 3625. The CoapplicantIncome is 0.0. The LoanAmount is 108.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 61 |
+
<thead>
|
| 62 |
+
<tr style=""text-align: right;"">
|
| 63 |
+
<th></th>
|
| 64 |
+
<th>Gender</th>
|
| 65 |
+
<th>Married</th>
|
| 66 |
+
<th>Dependents</th>
|
| 67 |
+
<th>Education</th>
|
| 68 |
+
<th>Self_Employed</th>
|
| 69 |
+
<th>ApplicantIncome</th>
|
| 70 |
+
<th>CoapplicantIncome</th>
|
| 71 |
+
<th>LoanAmount</th>
|
| 72 |
+
<th>Loan_Amount_Term</th>
|
| 73 |
+
<th>Credit_History</th>
|
| 74 |
+
<th>Property_Area</th>
|
| 75 |
+
</tr>
|
| 76 |
+
</thead>
|
| 77 |
+
<tbody>
|
| 78 |
+
<tr>
|
| 79 |
+
<th>0</th>
|
| 80 |
+
<td>Female</td>
|
| 81 |
+
<td>Yes</td>
|
| 82 |
+
<td>0</td>
|
| 83 |
+
<td>Graduate</td>
|
| 84 |
+
<td>No</td>
|
| 85 |
+
<td>3625</td>
|
| 86 |
+
<td>0.0</td>
|
| 87 |
+
<td>108.0</td>
|
| 88 |
+
<td>360.0</td>
|
| 89 |
+
<td>1.0</td>
|
| 90 |
+
<td>Semiurban</td>
|
| 91 |
+
</tr>
|
| 92 |
+
</tbody>
|
| 93 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 94 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 95 |
+
0 & Female & Yes & 0 & Graduate & No & 3625 & 0.000000 & 108.000000 & 360.000000 & 1.000000 & Semiurban \\
|
| 96 |
+
\end{tabular}
|
| 97 |
+
","{'ApplicantIncome': 3625, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 108.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married female individual is applying for a loan of 108.0 dollars for 30.0 months. She has a credit history. She is a graduate and is not self employed. She earns 3625 dollars. She has no person that she is liable to provide maintenance for. She lives in semiurban area.
|
| 98 |
+
1,Male,LP001316,Male,Yes,0,Graduate,No,2958,2900.0,131.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 2958, CoapplicantIncome is 2900.0, LoanAmount is 131.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
|
| 99 |
+
- Married : Yes
|
| 100 |
+
- Dependents : 0
|
| 101 |
+
- Education : Graduate
|
| 102 |
+
- Self_Employed : No
|
| 103 |
+
- ApplicantIncome : 2958
|
| 104 |
+
- CoapplicantIncome : 2900.0
|
| 105 |
+
- LoanAmount : 131.0
|
| 106 |
+
- Loan_Amount_Term : 360.0
|
| 107 |
+
- Credit_History : 1.0
|
| 108 |
+
- Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 2958. The CoapplicantIncome is 2900.0. The LoanAmount is 131.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 109 |
+
<thead>
|
| 110 |
+
<tr style=""text-align: right;"">
|
| 111 |
+
<th></th>
|
| 112 |
+
<th>Gender</th>
|
| 113 |
+
<th>Married</th>
|
| 114 |
+
<th>Dependents</th>
|
| 115 |
+
<th>Education</th>
|
| 116 |
+
<th>Self_Employed</th>
|
| 117 |
+
<th>ApplicantIncome</th>
|
| 118 |
+
<th>CoapplicantIncome</th>
|
| 119 |
+
<th>LoanAmount</th>
|
| 120 |
+
<th>Loan_Amount_Term</th>
|
| 121 |
+
<th>Credit_History</th>
|
| 122 |
+
<th>Property_Area</th>
|
| 123 |
+
</tr>
|
| 124 |
+
</thead>
|
| 125 |
+
<tbody>
|
| 126 |
+
<tr>
|
| 127 |
+
<th>0</th>
|
| 128 |
+
<td>Male</td>
|
| 129 |
+
<td>Yes</td>
|
| 130 |
+
<td>0</td>
|
| 131 |
+
<td>Graduate</td>
|
| 132 |
+
<td>No</td>
|
| 133 |
+
<td>2958</td>
|
| 134 |
+
<td>2900.0</td>
|
| 135 |
+
<td>131.0</td>
|
| 136 |
+
<td>360.0</td>
|
| 137 |
+
<td>1.0</td>
|
| 138 |
+
<td>Semiurban</td>
|
| 139 |
+
</tr>
|
| 140 |
+
</tbody>
|
| 141 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 142 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 143 |
+
0 & Male & Yes & 0 & Graduate & No & 2958 & 2900.000000 & 131.000000 & 360.000000 & 1.000000 & Semiurban \\
|
| 144 |
+
\end{tabular}
|
| 145 |
+
","{'ApplicantIncome': 2958, 'CoapplicantIncome': 2900.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 131.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 131.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 2958 dollars and his co-applicant earns 2900.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
|
| 146 |
+
19,Female,LP002367,Female,No,1,Not Graduate,No,4606,0.0,81.0,360.0,1.0,Rural,N,"Gender is Female, Married is No, Dependents is 1, Education is Not Graduate, Self_Employed is No, ApplicantIncome is 4606, CoapplicantIncome is 0.0, LoanAmount is 81.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Rural","- Gender : Female
|
| 147 |
+
- Married : No
|
| 148 |
+
- Dependents : 1
|
| 149 |
+
- Education : Not Graduate
|
| 150 |
+
- Self_Employed : No
|
| 151 |
+
- ApplicantIncome : 4606
|
| 152 |
+
- CoapplicantIncome : 0.0
|
| 153 |
+
- LoanAmount : 81.0
|
| 154 |
+
- Loan_Amount_Term : 360.0
|
| 155 |
+
- Credit_History : 1.0
|
| 156 |
+
- Property_Area : Rural",The Gender is Female. The Married is No. The Dependents is 1. The Education is Not Graduate. The Self_Employed is No. The ApplicantIncome is 4606. The CoapplicantIncome is 0.0. The LoanAmount is 81.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Rural,"<table border=""1"" class=""dataframe"">
|
| 157 |
+
<thead>
|
| 158 |
+
<tr style=""text-align: right;"">
|
| 159 |
+
<th></th>
|
| 160 |
+
<th>Gender</th>
|
| 161 |
+
<th>Married</th>
|
| 162 |
+
<th>Dependents</th>
|
| 163 |
+
<th>Education</th>
|
| 164 |
+
<th>Self_Employed</th>
|
| 165 |
+
<th>ApplicantIncome</th>
|
| 166 |
+
<th>CoapplicantIncome</th>
|
| 167 |
+
<th>LoanAmount</th>
|
| 168 |
+
<th>Loan_Amount_Term</th>
|
| 169 |
+
<th>Credit_History</th>
|
| 170 |
+
<th>Property_Area</th>
|
| 171 |
+
</tr>
|
| 172 |
+
</thead>
|
| 173 |
+
<tbody>
|
| 174 |
+
<tr>
|
| 175 |
+
<th>0</th>
|
| 176 |
+
<td>Female</td>
|
| 177 |
+
<td>No</td>
|
| 178 |
+
<td>1</td>
|
| 179 |
+
<td>Not Graduate</td>
|
| 180 |
+
<td>No</td>
|
| 181 |
+
<td>4606</td>
|
| 182 |
+
<td>0.0</td>
|
| 183 |
+
<td>81.0</td>
|
| 184 |
+
<td>360.0</td>
|
| 185 |
+
<td>1.0</td>
|
| 186 |
+
<td>Rural</td>
|
| 187 |
+
</tr>
|
| 188 |
+
</tbody>
|
| 189 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 190 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 191 |
+
0 & Female & No & 1 & Not Graduate & No & 4606 & 0.000000 & 81.000000 & 360.000000 & 1.000000 & Rural \\
|
| 192 |
+
\end{tabular}
|
| 193 |
+
","{'ApplicantIncome': 4606, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '1', 'Education': 'Not Graduate', 'Gender': 'Female', 'LoanAmount': 81.0, 'Loan_Amount_Term': 360.0, 'Married': 'No', 'Property_Area': 'Rural', 'Self_Employed': 'No'}",A unmarried female individual is applying for a loan of 81.0 dollars for 30.0 months. She has a credit history. She is not a graduate and is not self employed. She earns 4606 dollars. She has 1 person that she is liable to provide maintenance for. She lives in rural area.
|
new_data/loan_pred-fewshot-6.csv
ADDED
|
@@ -0,0 +1,289 @@
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Unnamed: 0,Gender,Loan_ID,Gender.1,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status,great,list,text,html,latex,json,LIFT
|
| 2 |
+
0,Male,LP001273,Male,Yes,0,Graduate,No,6000,2250.0,265.0,360.0,,Semiurban,N,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 6000, CoapplicantIncome is 2250.0, LoanAmount is 265.0, Loan_Amount_Term is 360.0, Credit_History is None, Property_Area is Semiurban","- Gender : Male
|
| 3 |
+
- Married : Yes
|
| 4 |
+
- Dependents : 0
|
| 5 |
+
- Education : Graduate
|
| 6 |
+
- Self_Employed : No
|
| 7 |
+
- ApplicantIncome : 6000
|
| 8 |
+
- CoapplicantIncome : 2250.0
|
| 9 |
+
- LoanAmount : 265.0
|
| 10 |
+
- Loan_Amount_Term : 360.0
|
| 11 |
+
- Credit_History : None
|
| 12 |
+
- Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6000. The CoapplicantIncome is 2250.0. The LoanAmount is 265.0. The Loan_Amount_Term is 360.0. The Credit_History is None. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 13 |
+
<thead>
|
| 14 |
+
<tr style=""text-align: right;"">
|
| 15 |
+
<th></th>
|
| 16 |
+
<th>Gender</th>
|
| 17 |
+
<th>Married</th>
|
| 18 |
+
<th>Dependents</th>
|
| 19 |
+
<th>Education</th>
|
| 20 |
+
<th>Self_Employed</th>
|
| 21 |
+
<th>ApplicantIncome</th>
|
| 22 |
+
<th>CoapplicantIncome</th>
|
| 23 |
+
<th>LoanAmount</th>
|
| 24 |
+
<th>Loan_Amount_Term</th>
|
| 25 |
+
<th>Credit_History</th>
|
| 26 |
+
<th>Property_Area</th>
|
| 27 |
+
</tr>
|
| 28 |
+
</thead>
|
| 29 |
+
<tbody>
|
| 30 |
+
<tr>
|
| 31 |
+
<th>0</th>
|
| 32 |
+
<td>Male</td>
|
| 33 |
+
<td>Yes</td>
|
| 34 |
+
<td>0</td>
|
| 35 |
+
<td>Graduate</td>
|
| 36 |
+
<td>No</td>
|
| 37 |
+
<td>6000</td>
|
| 38 |
+
<td>2250.0</td>
|
| 39 |
+
<td>265.0</td>
|
| 40 |
+
<td>360.0</td>
|
| 41 |
+
<td>None</td>
|
| 42 |
+
<td>Semiurban</td>
|
| 43 |
+
</tr>
|
| 44 |
+
</tbody>
|
| 45 |
+
</table>","\begin{tabular}{llllllrrrrll}
|
| 46 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 47 |
+
0 & Male & Yes & 0 & Graduate & No & 6000 & 2250.000000 & 265.000000 & 360.000000 & None & Semiurban \\
|
| 48 |
+
\end{tabular}
|
| 49 |
+
","{'ApplicantIncome': 6000, 'CoapplicantIncome': 2250.0, 'Credit_History': None, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 265.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 265.0 dollars for 30.0 months. He has unknown credit history. He is a graduate and is not self employed. He earns 6000 dollars and his co-applicant earns 2250.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
|
| 50 |
+
8,Female,LP001639,Female,Yes,0,Graduate,No,3625,0.0,108.0,360.0,1.0,Semiurban,Y,"Gender is Female, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 3625, CoapplicantIncome is 0.0, LoanAmount is 108.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Female
|
| 51 |
+
- Married : Yes
|
| 52 |
+
- Dependents : 0
|
| 53 |
+
- Education : Graduate
|
| 54 |
+
- Self_Employed : No
|
| 55 |
+
- ApplicantIncome : 3625
|
| 56 |
+
- CoapplicantIncome : 0.0
|
| 57 |
+
- LoanAmount : 108.0
|
| 58 |
+
- Loan_Amount_Term : 360.0
|
| 59 |
+
- Credit_History : 1.0
|
| 60 |
+
- Property_Area : Semiurban",The Gender is Female. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 3625. The CoapplicantIncome is 0.0. The LoanAmount is 108.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 61 |
+
<thead>
|
| 62 |
+
<tr style=""text-align: right;"">
|
| 63 |
+
<th></th>
|
| 64 |
+
<th>Gender</th>
|
| 65 |
+
<th>Married</th>
|
| 66 |
+
<th>Dependents</th>
|
| 67 |
+
<th>Education</th>
|
| 68 |
+
<th>Self_Employed</th>
|
| 69 |
+
<th>ApplicantIncome</th>
|
| 70 |
+
<th>CoapplicantIncome</th>
|
| 71 |
+
<th>LoanAmount</th>
|
| 72 |
+
<th>Loan_Amount_Term</th>
|
| 73 |
+
<th>Credit_History</th>
|
| 74 |
+
<th>Property_Area</th>
|
| 75 |
+
</tr>
|
| 76 |
+
</thead>
|
| 77 |
+
<tbody>
|
| 78 |
+
<tr>
|
| 79 |
+
<th>0</th>
|
| 80 |
+
<td>Female</td>
|
| 81 |
+
<td>Yes</td>
|
| 82 |
+
<td>0</td>
|
| 83 |
+
<td>Graduate</td>
|
| 84 |
+
<td>No</td>
|
| 85 |
+
<td>3625</td>
|
| 86 |
+
<td>0.0</td>
|
| 87 |
+
<td>108.0</td>
|
| 88 |
+
<td>360.0</td>
|
| 89 |
+
<td>1.0</td>
|
| 90 |
+
<td>Semiurban</td>
|
| 91 |
+
</tr>
|
| 92 |
+
</tbody>
|
| 93 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 94 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 95 |
+
0 & Female & Yes & 0 & Graduate & No & 3625 & 0.000000 & 108.000000 & 360.000000 & 1.000000 & Semiurban \\
|
| 96 |
+
\end{tabular}
|
| 97 |
+
","{'ApplicantIncome': 3625, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 108.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married female individual is applying for a loan of 108.0 dollars for 30.0 months. She has a credit history. She is a graduate and is not self employed. She earns 3625 dollars. She has no person that she is liable to provide maintenance for. She lives in semiurban area.
|
| 98 |
+
1,Male,LP001316,Male,Yes,0,Graduate,No,2958,2900.0,131.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 2958, CoapplicantIncome is 2900.0, LoanAmount is 131.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
|
| 99 |
+
- Married : Yes
|
| 100 |
+
- Dependents : 0
|
| 101 |
+
- Education : Graduate
|
| 102 |
+
- Self_Employed : No
|
| 103 |
+
- ApplicantIncome : 2958
|
| 104 |
+
- CoapplicantIncome : 2900.0
|
| 105 |
+
- LoanAmount : 131.0
|
| 106 |
+
- Loan_Amount_Term : 360.0
|
| 107 |
+
- Credit_History : 1.0
|
| 108 |
+
- Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 2958. The CoapplicantIncome is 2900.0. The LoanAmount is 131.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 109 |
+
<thead>
|
| 110 |
+
<tr style=""text-align: right;"">
|
| 111 |
+
<th></th>
|
| 112 |
+
<th>Gender</th>
|
| 113 |
+
<th>Married</th>
|
| 114 |
+
<th>Dependents</th>
|
| 115 |
+
<th>Education</th>
|
| 116 |
+
<th>Self_Employed</th>
|
| 117 |
+
<th>ApplicantIncome</th>
|
| 118 |
+
<th>CoapplicantIncome</th>
|
| 119 |
+
<th>LoanAmount</th>
|
| 120 |
+
<th>Loan_Amount_Term</th>
|
| 121 |
+
<th>Credit_History</th>
|
| 122 |
+
<th>Property_Area</th>
|
| 123 |
+
</tr>
|
| 124 |
+
</thead>
|
| 125 |
+
<tbody>
|
| 126 |
+
<tr>
|
| 127 |
+
<th>0</th>
|
| 128 |
+
<td>Male</td>
|
| 129 |
+
<td>Yes</td>
|
| 130 |
+
<td>0</td>
|
| 131 |
+
<td>Graduate</td>
|
| 132 |
+
<td>No</td>
|
| 133 |
+
<td>2958</td>
|
| 134 |
+
<td>2900.0</td>
|
| 135 |
+
<td>131.0</td>
|
| 136 |
+
<td>360.0</td>
|
| 137 |
+
<td>1.0</td>
|
| 138 |
+
<td>Semiurban</td>
|
| 139 |
+
</tr>
|
| 140 |
+
</tbody>
|
| 141 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 142 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 143 |
+
0 & Male & Yes & 0 & Graduate & No & 2958 & 2900.000000 & 131.000000 & 360.000000 & 1.000000 & Semiurban \\
|
| 144 |
+
\end{tabular}
|
| 145 |
+
","{'ApplicantIncome': 2958, 'CoapplicantIncome': 2900.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 131.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 131.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 2958 dollars and his co-applicant earns 2900.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
|
| 146 |
+
19,Female,LP002367,Female,No,1,Not Graduate,No,4606,0.0,81.0,360.0,1.0,Rural,N,"Gender is Female, Married is No, Dependents is 1, Education is Not Graduate, Self_Employed is No, ApplicantIncome is 4606, CoapplicantIncome is 0.0, LoanAmount is 81.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Rural","- Gender : Female
|
| 147 |
+
- Married : No
|
| 148 |
+
- Dependents : 1
|
| 149 |
+
- Education : Not Graduate
|
| 150 |
+
- Self_Employed : No
|
| 151 |
+
- ApplicantIncome : 4606
|
| 152 |
+
- CoapplicantIncome : 0.0
|
| 153 |
+
- LoanAmount : 81.0
|
| 154 |
+
- Loan_Amount_Term : 360.0
|
| 155 |
+
- Credit_History : 1.0
|
| 156 |
+
- Property_Area : Rural",The Gender is Female. The Married is No. The Dependents is 1. The Education is Not Graduate. The Self_Employed is No. The ApplicantIncome is 4606. The CoapplicantIncome is 0.0. The LoanAmount is 81.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Rural,"<table border=""1"" class=""dataframe"">
|
| 157 |
+
<thead>
|
| 158 |
+
<tr style=""text-align: right;"">
|
| 159 |
+
<th></th>
|
| 160 |
+
<th>Gender</th>
|
| 161 |
+
<th>Married</th>
|
| 162 |
+
<th>Dependents</th>
|
| 163 |
+
<th>Education</th>
|
| 164 |
+
<th>Self_Employed</th>
|
| 165 |
+
<th>ApplicantIncome</th>
|
| 166 |
+
<th>CoapplicantIncome</th>
|
| 167 |
+
<th>LoanAmount</th>
|
| 168 |
+
<th>Loan_Amount_Term</th>
|
| 169 |
+
<th>Credit_History</th>
|
| 170 |
+
<th>Property_Area</th>
|
| 171 |
+
</tr>
|
| 172 |
+
</thead>
|
| 173 |
+
<tbody>
|
| 174 |
+
<tr>
|
| 175 |
+
<th>0</th>
|
| 176 |
+
<td>Female</td>
|
| 177 |
+
<td>No</td>
|
| 178 |
+
<td>1</td>
|
| 179 |
+
<td>Not Graduate</td>
|
| 180 |
+
<td>No</td>
|
| 181 |
+
<td>4606</td>
|
| 182 |
+
<td>0.0</td>
|
| 183 |
+
<td>81.0</td>
|
| 184 |
+
<td>360.0</td>
|
| 185 |
+
<td>1.0</td>
|
| 186 |
+
<td>Rural</td>
|
| 187 |
+
</tr>
|
| 188 |
+
</tbody>
|
| 189 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 190 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 191 |
+
0 & Female & No & 1 & Not Graduate & No & 4606 & 0.000000 & 81.000000 & 360.000000 & 1.000000 & Rural \\
|
| 192 |
+
\end{tabular}
|
| 193 |
+
","{'ApplicantIncome': 4606, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '1', 'Education': 'Not Graduate', 'Gender': 'Female', 'LoanAmount': 81.0, 'Loan_Amount_Term': 360.0, 'Married': 'No', 'Property_Area': 'Rural', 'Self_Employed': 'No'}",A unmarried female individual is applying for a loan of 81.0 dollars for 30.0 months. She has a credit history. She is not a graduate and is not self employed. She earns 4606 dollars. She has 1 person that she is liable to provide maintenance for. She lives in rural area.
|
| 194 |
+
2,Male,LP001758,Male,Yes,2,Graduate,No,6250,1695.0,210.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 2, Education is Graduate, Self_Employed is No, ApplicantIncome is 6250, CoapplicantIncome is 1695.0, LoanAmount is 210.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
|
| 195 |
+
- Married : Yes
|
| 196 |
+
- Dependents : 2
|
| 197 |
+
- Education : Graduate
|
| 198 |
+
- Self_Employed : No
|
| 199 |
+
- ApplicantIncome : 6250
|
| 200 |
+
- CoapplicantIncome : 1695.0
|
| 201 |
+
- LoanAmount : 210.0
|
| 202 |
+
- Loan_Amount_Term : 360.0
|
| 203 |
+
- Credit_History : 1.0
|
| 204 |
+
- Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 2. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6250. The CoapplicantIncome is 1695.0. The LoanAmount is 210.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 205 |
+
<thead>
|
| 206 |
+
<tr style=""text-align: right;"">
|
| 207 |
+
<th></th>
|
| 208 |
+
<th>Gender</th>
|
| 209 |
+
<th>Married</th>
|
| 210 |
+
<th>Dependents</th>
|
| 211 |
+
<th>Education</th>
|
| 212 |
+
<th>Self_Employed</th>
|
| 213 |
+
<th>ApplicantIncome</th>
|
| 214 |
+
<th>CoapplicantIncome</th>
|
| 215 |
+
<th>LoanAmount</th>
|
| 216 |
+
<th>Loan_Amount_Term</th>
|
| 217 |
+
<th>Credit_History</th>
|
| 218 |
+
<th>Property_Area</th>
|
| 219 |
+
</tr>
|
| 220 |
+
</thead>
|
| 221 |
+
<tbody>
|
| 222 |
+
<tr>
|
| 223 |
+
<th>0</th>
|
| 224 |
+
<td>Male</td>
|
| 225 |
+
<td>Yes</td>
|
| 226 |
+
<td>2</td>
|
| 227 |
+
<td>Graduate</td>
|
| 228 |
+
<td>No</td>
|
| 229 |
+
<td>6250</td>
|
| 230 |
+
<td>1695.0</td>
|
| 231 |
+
<td>210.0</td>
|
| 232 |
+
<td>360.0</td>
|
| 233 |
+
<td>1.0</td>
|
| 234 |
+
<td>Semiurban</td>
|
| 235 |
+
</tr>
|
| 236 |
+
</tbody>
|
| 237 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 238 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 239 |
+
0 & Male & Yes & 2 & Graduate & No & 6250 & 1695.000000 & 210.000000 & 360.000000 & 1.000000 & Semiurban \\
|
| 240 |
+
\end{tabular}
|
| 241 |
+
","{'ApplicantIncome': 6250, 'CoapplicantIncome': 1695.0, 'Credit_History': 1.0, 'Dependents': '2', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 210.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 210.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 6250 dollars and his co-applicant earns 1695.0 dollars. He has 2 people that he is liable to provide maintenance for. He lives in semiurban area.
|
| 242 |
+
20,Female,LP002949,Female,No,3+,Graduate,,416,41667.0,350.0,180.0,,Urban,N,"Gender is Female, Married is No, Dependents is 3+, Education is Graduate, Self_Employed is None, ApplicantIncome is 416, CoapplicantIncome is 41667.0, LoanAmount is 350.0, Loan_Amount_Term is 180.0, Credit_History is None, Property_Area is Urban","- Gender : Female
|
| 243 |
+
- Married : No
|
| 244 |
+
- Dependents : 3+
|
| 245 |
+
- Education : Graduate
|
| 246 |
+
- Self_Employed : None
|
| 247 |
+
- ApplicantIncome : 416
|
| 248 |
+
- CoapplicantIncome : 41667.0
|
| 249 |
+
- LoanAmount : 350.0
|
| 250 |
+
- Loan_Amount_Term : 180.0
|
| 251 |
+
- Credit_History : None
|
| 252 |
+
- Property_Area : Urban",The Gender is Female. The Married is No. The Dependents is 3+. The Education is Graduate. The Self_Employed is None. The ApplicantIncome is 416. The CoapplicantIncome is 41667.0. The LoanAmount is 350.0. The Loan_Amount_Term is 180.0. The Credit_History is None. The Property_Area is Urban,"<table border=""1"" class=""dataframe"">
|
| 253 |
+
<thead>
|
| 254 |
+
<tr style=""text-align: right;"">
|
| 255 |
+
<th></th>
|
| 256 |
+
<th>Gender</th>
|
| 257 |
+
<th>Married</th>
|
| 258 |
+
<th>Dependents</th>
|
| 259 |
+
<th>Education</th>
|
| 260 |
+
<th>Self_Employed</th>
|
| 261 |
+
<th>ApplicantIncome</th>
|
| 262 |
+
<th>CoapplicantIncome</th>
|
| 263 |
+
<th>LoanAmount</th>
|
| 264 |
+
<th>Loan_Amount_Term</th>
|
| 265 |
+
<th>Credit_History</th>
|
| 266 |
+
<th>Property_Area</th>
|
| 267 |
+
</tr>
|
| 268 |
+
</thead>
|
| 269 |
+
<tbody>
|
| 270 |
+
<tr>
|
| 271 |
+
<th>0</th>
|
| 272 |
+
<td>Female</td>
|
| 273 |
+
<td>No</td>
|
| 274 |
+
<td>3+</td>
|
| 275 |
+
<td>Graduate</td>
|
| 276 |
+
<td>None</td>
|
| 277 |
+
<td>416</td>
|
| 278 |
+
<td>41667.0</td>
|
| 279 |
+
<td>350.0</td>
|
| 280 |
+
<td>180.0</td>
|
| 281 |
+
<td>None</td>
|
| 282 |
+
<td>Urban</td>
|
| 283 |
+
</tr>
|
| 284 |
+
</tbody>
|
| 285 |
+
</table>","\begin{tabular}{llllllrrrrll}
|
| 286 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 287 |
+
0 & Female & No & 3+ & Graduate & None & 416 & 41667.000000 & 350.000000 & 180.000000 & None & Urban \\
|
| 288 |
+
\end{tabular}
|
| 289 |
+
","{'ApplicantIncome': 416, 'CoapplicantIncome': 41667.0, 'Credit_History': None, 'Dependents': '3+', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 350.0, 'Loan_Amount_Term': 180.0, 'Married': 'No', 'Property_Area': 'Urban', 'Self_Employed': None}",A unmarried female individual is applying for a loan of 350.0 dollars for 15.0 months. She has unknown credit history. She is a graduate and has unknown self employment status. She earns 416 dollars and her co-applicant earns 41667.0 dollars. She has 3+ people that she is liable to provide maintenance for. She lives in urban area.
|
new_data/loan_pred-fewshot-8.csv
ADDED
|
@@ -0,0 +1,385 @@
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|
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|
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|
|
|
|
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|
| 1 |
+
Unnamed: 0,Gender,Loan_ID,Gender.1,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status,great,list,text,html,latex,json,LIFT
|
| 2 |
+
0,Male,LP001273,Male,Yes,0,Graduate,No,6000,2250.0,265.0,360.0,,Semiurban,N,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 6000, CoapplicantIncome is 2250.0, LoanAmount is 265.0, Loan_Amount_Term is 360.0, Credit_History is None, Property_Area is Semiurban","- Gender : Male
|
| 3 |
+
- Married : Yes
|
| 4 |
+
- Dependents : 0
|
| 5 |
+
- Education : Graduate
|
| 6 |
+
- Self_Employed : No
|
| 7 |
+
- ApplicantIncome : 6000
|
| 8 |
+
- CoapplicantIncome : 2250.0
|
| 9 |
+
- LoanAmount : 265.0
|
| 10 |
+
- Loan_Amount_Term : 360.0
|
| 11 |
+
- Credit_History : None
|
| 12 |
+
- Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6000. The CoapplicantIncome is 2250.0. The LoanAmount is 265.0. The Loan_Amount_Term is 360.0. The Credit_History is None. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 13 |
+
<thead>
|
| 14 |
+
<tr style=""text-align: right;"">
|
| 15 |
+
<th></th>
|
| 16 |
+
<th>Gender</th>
|
| 17 |
+
<th>Married</th>
|
| 18 |
+
<th>Dependents</th>
|
| 19 |
+
<th>Education</th>
|
| 20 |
+
<th>Self_Employed</th>
|
| 21 |
+
<th>ApplicantIncome</th>
|
| 22 |
+
<th>CoapplicantIncome</th>
|
| 23 |
+
<th>LoanAmount</th>
|
| 24 |
+
<th>Loan_Amount_Term</th>
|
| 25 |
+
<th>Credit_History</th>
|
| 26 |
+
<th>Property_Area</th>
|
| 27 |
+
</tr>
|
| 28 |
+
</thead>
|
| 29 |
+
<tbody>
|
| 30 |
+
<tr>
|
| 31 |
+
<th>0</th>
|
| 32 |
+
<td>Male</td>
|
| 33 |
+
<td>Yes</td>
|
| 34 |
+
<td>0</td>
|
| 35 |
+
<td>Graduate</td>
|
| 36 |
+
<td>No</td>
|
| 37 |
+
<td>6000</td>
|
| 38 |
+
<td>2250.0</td>
|
| 39 |
+
<td>265.0</td>
|
| 40 |
+
<td>360.0</td>
|
| 41 |
+
<td>None</td>
|
| 42 |
+
<td>Semiurban</td>
|
| 43 |
+
</tr>
|
| 44 |
+
</tbody>
|
| 45 |
+
</table>","\begin{tabular}{llllllrrrrll}
|
| 46 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 47 |
+
0 & Male & Yes & 0 & Graduate & No & 6000 & 2250.000000 & 265.000000 & 360.000000 & None & Semiurban \\
|
| 48 |
+
\end{tabular}
|
| 49 |
+
","{'ApplicantIncome': 6000, 'CoapplicantIncome': 2250.0, 'Credit_History': None, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 265.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 265.0 dollars for 30.0 months. He has unknown credit history. He is a graduate and is not self employed. He earns 6000 dollars and his co-applicant earns 2250.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
|
| 50 |
+
8,Female,LP001639,Female,Yes,0,Graduate,No,3625,0.0,108.0,360.0,1.0,Semiurban,Y,"Gender is Female, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 3625, CoapplicantIncome is 0.0, LoanAmount is 108.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Female
|
| 51 |
+
- Married : Yes
|
| 52 |
+
- Dependents : 0
|
| 53 |
+
- Education : Graduate
|
| 54 |
+
- Self_Employed : No
|
| 55 |
+
- ApplicantIncome : 3625
|
| 56 |
+
- CoapplicantIncome : 0.0
|
| 57 |
+
- LoanAmount : 108.0
|
| 58 |
+
- Loan_Amount_Term : 360.0
|
| 59 |
+
- Credit_History : 1.0
|
| 60 |
+
- Property_Area : Semiurban",The Gender is Female. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 3625. The CoapplicantIncome is 0.0. The LoanAmount is 108.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 61 |
+
<thead>
|
| 62 |
+
<tr style=""text-align: right;"">
|
| 63 |
+
<th></th>
|
| 64 |
+
<th>Gender</th>
|
| 65 |
+
<th>Married</th>
|
| 66 |
+
<th>Dependents</th>
|
| 67 |
+
<th>Education</th>
|
| 68 |
+
<th>Self_Employed</th>
|
| 69 |
+
<th>ApplicantIncome</th>
|
| 70 |
+
<th>CoapplicantIncome</th>
|
| 71 |
+
<th>LoanAmount</th>
|
| 72 |
+
<th>Loan_Amount_Term</th>
|
| 73 |
+
<th>Credit_History</th>
|
| 74 |
+
<th>Property_Area</th>
|
| 75 |
+
</tr>
|
| 76 |
+
</thead>
|
| 77 |
+
<tbody>
|
| 78 |
+
<tr>
|
| 79 |
+
<th>0</th>
|
| 80 |
+
<td>Female</td>
|
| 81 |
+
<td>Yes</td>
|
| 82 |
+
<td>0</td>
|
| 83 |
+
<td>Graduate</td>
|
| 84 |
+
<td>No</td>
|
| 85 |
+
<td>3625</td>
|
| 86 |
+
<td>0.0</td>
|
| 87 |
+
<td>108.0</td>
|
| 88 |
+
<td>360.0</td>
|
| 89 |
+
<td>1.0</td>
|
| 90 |
+
<td>Semiurban</td>
|
| 91 |
+
</tr>
|
| 92 |
+
</tbody>
|
| 93 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 94 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 95 |
+
0 & Female & Yes & 0 & Graduate & No & 3625 & 0.000000 & 108.000000 & 360.000000 & 1.000000 & Semiurban \\
|
| 96 |
+
\end{tabular}
|
| 97 |
+
","{'ApplicantIncome': 3625, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 108.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married female individual is applying for a loan of 108.0 dollars for 30.0 months. She has a credit history. She is a graduate and is not self employed. She earns 3625 dollars. She has no person that she is liable to provide maintenance for. She lives in semiurban area.
|
| 98 |
+
1,Male,LP001316,Male,Yes,0,Graduate,No,2958,2900.0,131.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 2958, CoapplicantIncome is 2900.0, LoanAmount is 131.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
|
| 99 |
+
- Married : Yes
|
| 100 |
+
- Dependents : 0
|
| 101 |
+
- Education : Graduate
|
| 102 |
+
- Self_Employed : No
|
| 103 |
+
- ApplicantIncome : 2958
|
| 104 |
+
- CoapplicantIncome : 2900.0
|
| 105 |
+
- LoanAmount : 131.0
|
| 106 |
+
- Loan_Amount_Term : 360.0
|
| 107 |
+
- Credit_History : 1.0
|
| 108 |
+
- Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 2958. The CoapplicantIncome is 2900.0. The LoanAmount is 131.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 109 |
+
<thead>
|
| 110 |
+
<tr style=""text-align: right;"">
|
| 111 |
+
<th></th>
|
| 112 |
+
<th>Gender</th>
|
| 113 |
+
<th>Married</th>
|
| 114 |
+
<th>Dependents</th>
|
| 115 |
+
<th>Education</th>
|
| 116 |
+
<th>Self_Employed</th>
|
| 117 |
+
<th>ApplicantIncome</th>
|
| 118 |
+
<th>CoapplicantIncome</th>
|
| 119 |
+
<th>LoanAmount</th>
|
| 120 |
+
<th>Loan_Amount_Term</th>
|
| 121 |
+
<th>Credit_History</th>
|
| 122 |
+
<th>Property_Area</th>
|
| 123 |
+
</tr>
|
| 124 |
+
</thead>
|
| 125 |
+
<tbody>
|
| 126 |
+
<tr>
|
| 127 |
+
<th>0</th>
|
| 128 |
+
<td>Male</td>
|
| 129 |
+
<td>Yes</td>
|
| 130 |
+
<td>0</td>
|
| 131 |
+
<td>Graduate</td>
|
| 132 |
+
<td>No</td>
|
| 133 |
+
<td>2958</td>
|
| 134 |
+
<td>2900.0</td>
|
| 135 |
+
<td>131.0</td>
|
| 136 |
+
<td>360.0</td>
|
| 137 |
+
<td>1.0</td>
|
| 138 |
+
<td>Semiurban</td>
|
| 139 |
+
</tr>
|
| 140 |
+
</tbody>
|
| 141 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 142 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 143 |
+
0 & Male & Yes & 0 & Graduate & No & 2958 & 2900.000000 & 131.000000 & 360.000000 & 1.000000 & Semiurban \\
|
| 144 |
+
\end{tabular}
|
| 145 |
+
","{'ApplicantIncome': 2958, 'CoapplicantIncome': 2900.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 131.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 131.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 2958 dollars and his co-applicant earns 2900.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
|
| 146 |
+
19,Female,LP002367,Female,No,1,Not Graduate,No,4606,0.0,81.0,360.0,1.0,Rural,N,"Gender is Female, Married is No, Dependents is 1, Education is Not Graduate, Self_Employed is No, ApplicantIncome is 4606, CoapplicantIncome is 0.0, LoanAmount is 81.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Rural","- Gender : Female
|
| 147 |
+
- Married : No
|
| 148 |
+
- Dependents : 1
|
| 149 |
+
- Education : Not Graduate
|
| 150 |
+
- Self_Employed : No
|
| 151 |
+
- ApplicantIncome : 4606
|
| 152 |
+
- CoapplicantIncome : 0.0
|
| 153 |
+
- LoanAmount : 81.0
|
| 154 |
+
- Loan_Amount_Term : 360.0
|
| 155 |
+
- Credit_History : 1.0
|
| 156 |
+
- Property_Area : Rural",The Gender is Female. The Married is No. The Dependents is 1. The Education is Not Graduate. The Self_Employed is No. The ApplicantIncome is 4606. The CoapplicantIncome is 0.0. The LoanAmount is 81.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Rural,"<table border=""1"" class=""dataframe"">
|
| 157 |
+
<thead>
|
| 158 |
+
<tr style=""text-align: right;"">
|
| 159 |
+
<th></th>
|
| 160 |
+
<th>Gender</th>
|
| 161 |
+
<th>Married</th>
|
| 162 |
+
<th>Dependents</th>
|
| 163 |
+
<th>Education</th>
|
| 164 |
+
<th>Self_Employed</th>
|
| 165 |
+
<th>ApplicantIncome</th>
|
| 166 |
+
<th>CoapplicantIncome</th>
|
| 167 |
+
<th>LoanAmount</th>
|
| 168 |
+
<th>Loan_Amount_Term</th>
|
| 169 |
+
<th>Credit_History</th>
|
| 170 |
+
<th>Property_Area</th>
|
| 171 |
+
</tr>
|
| 172 |
+
</thead>
|
| 173 |
+
<tbody>
|
| 174 |
+
<tr>
|
| 175 |
+
<th>0</th>
|
| 176 |
+
<td>Female</td>
|
| 177 |
+
<td>No</td>
|
| 178 |
+
<td>1</td>
|
| 179 |
+
<td>Not Graduate</td>
|
| 180 |
+
<td>No</td>
|
| 181 |
+
<td>4606</td>
|
| 182 |
+
<td>0.0</td>
|
| 183 |
+
<td>81.0</td>
|
| 184 |
+
<td>360.0</td>
|
| 185 |
+
<td>1.0</td>
|
| 186 |
+
<td>Rural</td>
|
| 187 |
+
</tr>
|
| 188 |
+
</tbody>
|
| 189 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 190 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 191 |
+
0 & Female & No & 1 & Not Graduate & No & 4606 & 0.000000 & 81.000000 & 360.000000 & 1.000000 & Rural \\
|
| 192 |
+
\end{tabular}
|
| 193 |
+
","{'ApplicantIncome': 4606, 'CoapplicantIncome': 0.0, 'Credit_History': 1.0, 'Dependents': '1', 'Education': 'Not Graduate', 'Gender': 'Female', 'LoanAmount': 81.0, 'Loan_Amount_Term': 360.0, 'Married': 'No', 'Property_Area': 'Rural', 'Self_Employed': 'No'}",A unmarried female individual is applying for a loan of 81.0 dollars for 30.0 months. She has a credit history. She is not a graduate and is not self employed. She earns 4606 dollars. She has 1 person that she is liable to provide maintenance for. She lives in rural area.
|
| 194 |
+
2,Male,LP001758,Male,Yes,2,Graduate,No,6250,1695.0,210.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 2, Education is Graduate, Self_Employed is No, ApplicantIncome is 6250, CoapplicantIncome is 1695.0, LoanAmount is 210.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
|
| 195 |
+
- Married : Yes
|
| 196 |
+
- Dependents : 2
|
| 197 |
+
- Education : Graduate
|
| 198 |
+
- Self_Employed : No
|
| 199 |
+
- ApplicantIncome : 6250
|
| 200 |
+
- CoapplicantIncome : 1695.0
|
| 201 |
+
- LoanAmount : 210.0
|
| 202 |
+
- Loan_Amount_Term : 360.0
|
| 203 |
+
- Credit_History : 1.0
|
| 204 |
+
- Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 2. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 6250. The CoapplicantIncome is 1695.0. The LoanAmount is 210.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 205 |
+
<thead>
|
| 206 |
+
<tr style=""text-align: right;"">
|
| 207 |
+
<th></th>
|
| 208 |
+
<th>Gender</th>
|
| 209 |
+
<th>Married</th>
|
| 210 |
+
<th>Dependents</th>
|
| 211 |
+
<th>Education</th>
|
| 212 |
+
<th>Self_Employed</th>
|
| 213 |
+
<th>ApplicantIncome</th>
|
| 214 |
+
<th>CoapplicantIncome</th>
|
| 215 |
+
<th>LoanAmount</th>
|
| 216 |
+
<th>Loan_Amount_Term</th>
|
| 217 |
+
<th>Credit_History</th>
|
| 218 |
+
<th>Property_Area</th>
|
| 219 |
+
</tr>
|
| 220 |
+
</thead>
|
| 221 |
+
<tbody>
|
| 222 |
+
<tr>
|
| 223 |
+
<th>0</th>
|
| 224 |
+
<td>Male</td>
|
| 225 |
+
<td>Yes</td>
|
| 226 |
+
<td>2</td>
|
| 227 |
+
<td>Graduate</td>
|
| 228 |
+
<td>No</td>
|
| 229 |
+
<td>6250</td>
|
| 230 |
+
<td>1695.0</td>
|
| 231 |
+
<td>210.0</td>
|
| 232 |
+
<td>360.0</td>
|
| 233 |
+
<td>1.0</td>
|
| 234 |
+
<td>Semiurban</td>
|
| 235 |
+
</tr>
|
| 236 |
+
</tbody>
|
| 237 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 238 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 239 |
+
0 & Male & Yes & 2 & Graduate & No & 6250 & 1695.000000 & 210.000000 & 360.000000 & 1.000000 & Semiurban \\
|
| 240 |
+
\end{tabular}
|
| 241 |
+
","{'ApplicantIncome': 6250, 'CoapplicantIncome': 1695.0, 'Credit_History': 1.0, 'Dependents': '2', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 210.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 210.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 6250 dollars and his co-applicant earns 1695.0 dollars. He has 2 people that he is liable to provide maintenance for. He lives in semiurban area.
|
| 242 |
+
20,Female,LP002949,Female,No,3+,Graduate,,416,41667.0,350.0,180.0,,Urban,N,"Gender is Female, Married is No, Dependents is 3+, Education is Graduate, Self_Employed is None, ApplicantIncome is 416, CoapplicantIncome is 41667.0, LoanAmount is 350.0, Loan_Amount_Term is 180.0, Credit_History is None, Property_Area is Urban","- Gender : Female
|
| 243 |
+
- Married : No
|
| 244 |
+
- Dependents : 3+
|
| 245 |
+
- Education : Graduate
|
| 246 |
+
- Self_Employed : None
|
| 247 |
+
- ApplicantIncome : 416
|
| 248 |
+
- CoapplicantIncome : 41667.0
|
| 249 |
+
- LoanAmount : 350.0
|
| 250 |
+
- Loan_Amount_Term : 180.0
|
| 251 |
+
- Credit_History : None
|
| 252 |
+
- Property_Area : Urban",The Gender is Female. The Married is No. The Dependents is 3+. The Education is Graduate. The Self_Employed is None. The ApplicantIncome is 416. The CoapplicantIncome is 41667.0. The LoanAmount is 350.0. The Loan_Amount_Term is 180.0. The Credit_History is None. The Property_Area is Urban,"<table border=""1"" class=""dataframe"">
|
| 253 |
+
<thead>
|
| 254 |
+
<tr style=""text-align: right;"">
|
| 255 |
+
<th></th>
|
| 256 |
+
<th>Gender</th>
|
| 257 |
+
<th>Married</th>
|
| 258 |
+
<th>Dependents</th>
|
| 259 |
+
<th>Education</th>
|
| 260 |
+
<th>Self_Employed</th>
|
| 261 |
+
<th>ApplicantIncome</th>
|
| 262 |
+
<th>CoapplicantIncome</th>
|
| 263 |
+
<th>LoanAmount</th>
|
| 264 |
+
<th>Loan_Amount_Term</th>
|
| 265 |
+
<th>Credit_History</th>
|
| 266 |
+
<th>Property_Area</th>
|
| 267 |
+
</tr>
|
| 268 |
+
</thead>
|
| 269 |
+
<tbody>
|
| 270 |
+
<tr>
|
| 271 |
+
<th>0</th>
|
| 272 |
+
<td>Female</td>
|
| 273 |
+
<td>No</td>
|
| 274 |
+
<td>3+</td>
|
| 275 |
+
<td>Graduate</td>
|
| 276 |
+
<td>None</td>
|
| 277 |
+
<td>416</td>
|
| 278 |
+
<td>41667.0</td>
|
| 279 |
+
<td>350.0</td>
|
| 280 |
+
<td>180.0</td>
|
| 281 |
+
<td>None</td>
|
| 282 |
+
<td>Urban</td>
|
| 283 |
+
</tr>
|
| 284 |
+
</tbody>
|
| 285 |
+
</table>","\begin{tabular}{llllllrrrrll}
|
| 286 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 287 |
+
0 & Female & No & 3+ & Graduate & None & 416 & 41667.000000 & 350.000000 & 180.000000 & None & Urban \\
|
| 288 |
+
\end{tabular}
|
| 289 |
+
","{'ApplicantIncome': 416, 'CoapplicantIncome': 41667.0, 'Credit_History': None, 'Dependents': '3+', 'Education': 'Graduate', 'Gender': 'Female', 'LoanAmount': 350.0, 'Loan_Amount_Term': 180.0, 'Married': 'No', 'Property_Area': 'Urban', 'Self_Employed': None}",A unmarried female individual is applying for a loan of 350.0 dollars for 15.0 months. She has unknown credit history. She is a graduate and has unknown self employment status. She earns 416 dollars and her co-applicant earns 41667.0 dollars. She has 3+ people that she is liable to provide maintenance for. She lives in urban area.
|
| 290 |
+
3,Male,LP002537,Male,Yes,0,Graduate,No,2083,3150.0,128.0,360.0,1.0,Semiurban,Y,"Gender is Male, Married is Yes, Dependents is 0, Education is Graduate, Self_Employed is No, ApplicantIncome is 2083, CoapplicantIncome is 3150.0, LoanAmount is 128.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Male
|
| 291 |
+
- Married : Yes
|
| 292 |
+
- Dependents : 0
|
| 293 |
+
- Education : Graduate
|
| 294 |
+
- Self_Employed : No
|
| 295 |
+
- ApplicantIncome : 2083
|
| 296 |
+
- CoapplicantIncome : 3150.0
|
| 297 |
+
- LoanAmount : 128.0
|
| 298 |
+
- Loan_Amount_Term : 360.0
|
| 299 |
+
- Credit_History : 1.0
|
| 300 |
+
- Property_Area : Semiurban",The Gender is Male. The Married is Yes. The Dependents is 0. The Education is Graduate. The Self_Employed is No. The ApplicantIncome is 2083. The CoapplicantIncome is 3150.0. The LoanAmount is 128.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 301 |
+
<thead>
|
| 302 |
+
<tr style=""text-align: right;"">
|
| 303 |
+
<th></th>
|
| 304 |
+
<th>Gender</th>
|
| 305 |
+
<th>Married</th>
|
| 306 |
+
<th>Dependents</th>
|
| 307 |
+
<th>Education</th>
|
| 308 |
+
<th>Self_Employed</th>
|
| 309 |
+
<th>ApplicantIncome</th>
|
| 310 |
+
<th>CoapplicantIncome</th>
|
| 311 |
+
<th>LoanAmount</th>
|
| 312 |
+
<th>Loan_Amount_Term</th>
|
| 313 |
+
<th>Credit_History</th>
|
| 314 |
+
<th>Property_Area</th>
|
| 315 |
+
</tr>
|
| 316 |
+
</thead>
|
| 317 |
+
<tbody>
|
| 318 |
+
<tr>
|
| 319 |
+
<th>0</th>
|
| 320 |
+
<td>Male</td>
|
| 321 |
+
<td>Yes</td>
|
| 322 |
+
<td>0</td>
|
| 323 |
+
<td>Graduate</td>
|
| 324 |
+
<td>No</td>
|
| 325 |
+
<td>2083</td>
|
| 326 |
+
<td>3150.0</td>
|
| 327 |
+
<td>128.0</td>
|
| 328 |
+
<td>360.0</td>
|
| 329 |
+
<td>1.0</td>
|
| 330 |
+
<td>Semiurban</td>
|
| 331 |
+
</tr>
|
| 332 |
+
</tbody>
|
| 333 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 334 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 335 |
+
0 & Male & Yes & 0 & Graduate & No & 2083 & 3150.000000 & 128.000000 & 360.000000 & 1.000000 & Semiurban \\
|
| 336 |
+
\end{tabular}
|
| 337 |
+
","{'ApplicantIncome': 2083, 'CoapplicantIncome': 3150.0, 'Credit_History': 1.0, 'Dependents': '0', 'Education': 'Graduate', 'Gender': 'Male', 'LoanAmount': 128.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': 'No'}",A married male individual is applying for a loan of 128.0 dollars for 30.0 months. He has a credit history. He is a graduate and is not self employed. He earns 2083 dollars and his co-applicant earns 3150.0 dollars. He has no person that he is liable to provide maintenance for. He lives in semiurban area.
|
| 338 |
+
27,Female,LP002502,Female,Yes,2,Not Graduate,,210,2917.0,98.0,360.0,1.0,Semiurban,Y,"Gender is Female, Married is Yes, Dependents is 2, Education is Not Graduate, Self_Employed is None, ApplicantIncome is 210, CoapplicantIncome is 2917.0, LoanAmount is 98.0, Loan_Amount_Term is 360.0, Credit_History is 1.0, Property_Area is Semiurban","- Gender : Female
|
| 339 |
+
- Married : Yes
|
| 340 |
+
- Dependents : 2
|
| 341 |
+
- Education : Not Graduate
|
| 342 |
+
- Self_Employed : None
|
| 343 |
+
- ApplicantIncome : 210
|
| 344 |
+
- CoapplicantIncome : 2917.0
|
| 345 |
+
- LoanAmount : 98.0
|
| 346 |
+
- Loan_Amount_Term : 360.0
|
| 347 |
+
- Credit_History : 1.0
|
| 348 |
+
- Property_Area : Semiurban",The Gender is Female. The Married is Yes. The Dependents is 2. The Education is Not Graduate. The Self_Employed is None. The ApplicantIncome is 210. The CoapplicantIncome is 2917.0. The LoanAmount is 98.0. The Loan_Amount_Term is 360.0. The Credit_History is 1.0. The Property_Area is Semiurban,"<table border=""1"" class=""dataframe"">
|
| 349 |
+
<thead>
|
| 350 |
+
<tr style=""text-align: right;"">
|
| 351 |
+
<th></th>
|
| 352 |
+
<th>Gender</th>
|
| 353 |
+
<th>Married</th>
|
| 354 |
+
<th>Dependents</th>
|
| 355 |
+
<th>Education</th>
|
| 356 |
+
<th>Self_Employed</th>
|
| 357 |
+
<th>ApplicantIncome</th>
|
| 358 |
+
<th>CoapplicantIncome</th>
|
| 359 |
+
<th>LoanAmount</th>
|
| 360 |
+
<th>Loan_Amount_Term</th>
|
| 361 |
+
<th>Credit_History</th>
|
| 362 |
+
<th>Property_Area</th>
|
| 363 |
+
</tr>
|
| 364 |
+
</thead>
|
| 365 |
+
<tbody>
|
| 366 |
+
<tr>
|
| 367 |
+
<th>0</th>
|
| 368 |
+
<td>Female</td>
|
| 369 |
+
<td>Yes</td>
|
| 370 |
+
<td>2</td>
|
| 371 |
+
<td>Not Graduate</td>
|
| 372 |
+
<td>None</td>
|
| 373 |
+
<td>210</td>
|
| 374 |
+
<td>2917.0</td>
|
| 375 |
+
<td>98.0</td>
|
| 376 |
+
<td>360.0</td>
|
| 377 |
+
<td>1.0</td>
|
| 378 |
+
<td>Semiurban</td>
|
| 379 |
+
</tr>
|
| 380 |
+
</tbody>
|
| 381 |
+
</table>","\begin{tabular}{llllllrrrrrl}
|
| 382 |
+
& Gender & Married & Dependents & Education & Self_Employed & ApplicantIncome & CoapplicantIncome & LoanAmount & Loan_Amount_Term & Credit_History & Property_Area \\
|
| 383 |
+
0 & Female & Yes & 2 & Not Graduate & None & 210 & 2917.000000 & 98.000000 & 360.000000 & 1.000000 & Semiurban \\
|
| 384 |
+
\end{tabular}
|
| 385 |
+
","{'ApplicantIncome': 210, 'CoapplicantIncome': 2917.0, 'Credit_History': 1.0, 'Dependents': '2', 'Education': 'Not Graduate', 'Gender': 'Female', 'LoanAmount': 98.0, 'Loan_Amount_Term': 360.0, 'Married': 'Yes', 'Property_Area': 'Semiurban', 'Self_Employed': None}",A married female individual is applying for a loan of 98.0 dollars for 30.0 months. She has a credit history. She is not a graduate and has unknown self employment status. She earns 210 dollars and her co-applicant earns 2917.0 dollars. She has 2 people that she is liable to provide maintenance for. She lives in semiurban area.
|