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3c4e575 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 | Columns in the dataset:
['Name', 'Age', 'City', 'Profession', 'Salary', 'Expenses', 'Savings', 'Lifecycle Stage', 'Risk Appetite', 'Investment Horizon', 'Equity (%)', 'Debt (%)', 'Gold (%)', 'FD/Cash (%)']
Preview of the data:
Name Age City Profession Salary Expenses Savings \
0 Rohan Sharma 28 Mumbai Software Engineer 85000 65000 20000
1 Priya Patel 45 Delhi Doctor 220000 150000 70000
2 Arjun Singh 60 Bangalore Retired Banker 45000 40000 5000
3 Anika Reddy 22 Hyderabad Student 15000 14000 1000
4 Vikram Mehta 35 Pune Marketing Manager 140000 100000 40000
Lifecycle Stage Risk Appetite Investment Horizon Equity (%) Debt (%) \
0 Early Career Medium Long-term 45 25
1 Mid-Career Medium Medium-term 40 30
2 Retired Low Short-term 10 40
3 Student Low Short-term 0 30
4 Early Career High Long-term 70 15
Gold (%) FD/Cash (%)
0 10 20
1 10 20
2 15 35
3 5 65
4 5 10
Data types:
Name object
Age int64
City object
Profession object
Salary int64
Expenses int64
Savings int64
Lifecycle Stage object
Risk Appetite object
Investment Horizon object
Equity (%) int64
Debt (%) int64
Gold (%) int64
FD/Cash (%) int64
dtype: object
Unique values in 'City':
['Mumbai' 'Delhi' 'Bangalore' 'Hyderabad' 'Pune' 'Chennai' 'Jaipur'
'Kochi' 'Kolkata' 'Ahmedabad' 'Gurgaon' 'Lucknow' 'Nagpur' 'Chandigarh'
'Surat' 'Indore' 'Bhopal']
Unique values in 'Profession':
['Software Engineer' 'Doctor' 'Retired Banker' 'Student'
'Marketing Manager' 'Teacher' 'Freelancer' 'Architect' 'Business Owner'
'Nurse' 'Product Manager' 'CA' 'Data Analyst' 'Retired Professor'
'Journalist' 'Graphic Designer' 'Sales Executive' 'HR Manager' 'Intern'
'Dentist' 'Lawyer' 'Content Creator' 'Pensioner' 'UX Designer'
'Government Employee' 'Fashion Designer' 'Startup Founder'
'Homemaker (Investor)' 'Investment Banker' 'IT Consultant'
'College Student' 'Pharmacist' 'Textile Business Owner' 'Event Planner'
'Film Producer' 'Nutritionist' 'Retired Army Officer'
'Social Media Manager' 'Airline Pilot' 'Biotech Researcher'
'Real Estate Agent' 'AI Engineer' 'Retired Teacher' 'Financial Analyst'
'Software Developer' 'NGO Director' 'Fitness Trainer' 'Digital Marketer'
'Content Strategist' 'Retired Engineer' 'UI Developer'
'Operations Manager' 'Corporate Lawyer' 'School Principal'
'AI Researcher' 'Junior Doctor' 'Finance Manager' 'Fashion Blogger'
'HR Consultant' 'Video Editor' 'Small Business Owner' 'Dietitian'
'Supply Chain Manager' 'Interior Designer' 'Sales Manager' 'PR Executive'
'Logistics Head' 'Content Writer' 'Retired Govt. Employee'
'Marketing Lead' 'IT Manager' 'Startup Intern' 'Export Manager'
'Fitness Instructor' 'Real Estate Broker' 'Event Manager'
'Software Trainee' 'Data Scientist' 'HR Director' 'Hotel Manager'
'Social Worker' 'Cybersecurity Expert' 'E-commerce Manager'
'Bank Manager' 'Retired IT Manager' 'UX Researcher' 'Product Designer'
'Cybersecurity Analyst' 'Podcast Producer' 'E-commerce Seller'
'Cloud Architect' 'Corporate Trainer' 'AI Trainer' 'Supply Chain Head'
'Product Owner' 'UI/UX Designer' 'Finance Director'
'Sustainability Consultant' 'Retired Bank Manager'
'Social Media Influencer' 'Blockchain Developer' 'NGO Head'
'Data Engineer' 'Event Curator' 'CTO' 'Content Marketer'
'Retired Army Major' 'AR/VR Developer' 'Logistics Manager' 'VP Sales'
'EdTech Founder' 'SEO Specialist' 'Yoga Instructor' 'IT Director'
'App Developer' 'Consultant Cardiologist' 'Freelance Writer'
'Cloud Engineer' 'Retired CA' 'Digital Artist' 'Retired Pilot'
'Graphic Animator' 'AI Ethicist' 'School Trustee' 'Robotics Engineer'
'Fashion Stylist' 'Retired Nurse' 'AI Ethics Consultant' 'Drone Engineer'
'Retired Bank Clerk' 'Digital Nomad' 'CFO' 'Sustainability Analyst'
'Retired Journalist' 'Social Entrepreneur' 'DevOps Engineer'
'School Counselor' 'Retired Army Colonel' 'AR Developer' 'Sales Director'
'EdTech Consultant' 'SEO Expert' 'Cardiologist' '3D Artist' 'HR Head'
'Animator' 'Fashion Influencer']
Unique values in 'Lifecycle Stage':
['Early Career' 'Mid-Career' 'Retired' 'Student' 'Late Career']
Unique values in 'Risk Appetite':
['Medium' 'Low' 'High']
Unique values in 'Investment Horizon':
['Long-term' 'Medium-term' 'Short-term']
Numerical columns summary:
Salary Expenses Savings Equity (%) Debt (%) \
count 198.000000 198.000000 198.000000 198.000000 198.000000
mean 115075.757576 84686.868687 30388.888889 39.469697 28.308081
std 69388.842695 48499.494260 21425.713424 20.713089 11.534149
min 8000.000000 7500.000000 500.000000 0.000000 10.000000
25% 60000.000000 48000.000000 10000.000000 25.000000 20.000000
50% 95000.000000 70000.000000 25000.000000 45.000000 25.000000
75% 163750.000000 118750.000000 45000.000000 50.000000 30.000000
max 310000.000000 230000.000000 90000.000000 70.000000 55.000000
Gold (%) FD/Cash (%)
count 198.000000 198.000000
mean 8.434343 23.787879
std 3.427751 16.426902
min 0.000000 10.000000
25% 5.000000 15.000000
50% 10.000000 20.000000
75% 10.000000 20.000000
max 15.000000 80.000000 |