Python problems on Datastructure
Problem 1: stocks
You are provided with a data structure named stocks which contains information about different companies.
stocks = [
{
"name": "Company A",
"symbol": "CMPA",
"sector": "Technology",
"current_price": 100.0,
"historical_data": [
{
"date": "2024-01-10",
"prices": {
"open": 98.0,
"close": 100.0,
"high": 101.0,
"low": 97.0
},
"volume": 12000
},
{
"date": "2024-01-09",
"prices": {
"open": 97.0,
"close": 98.0,
"high": 99.0,
"low": 96.0
},
"volume": 15000
}
],
"locations": ["New York", "London"]
},
{
"name": "Company B",
"symbol": "CMPB",
"sector": "Finance",
"current_price": 200.0,
"historical_data": [
{
"date": "2024-01-10",
"prices": {
"open": 198.0,
"close": 200.0,
"high": 202.0,
"low": 196.0
},
"volume": 18000
},
{
"date": "2024-01-09",
"prices": {
"open": 196.0,
"close": 198.0,
"high": 199.0,
"low": 195.0
},
"volume": 17000
}
],
"locations": ["Tokyo", "Singapore"]
},
{
"name": "Company C",
"symbol": "CMPC",
"sector": "Healthcare",
"current_price": 300.0,
"historical_data": [
{
"date": "2024-01-10",
"prices": {
"open": 295.0,
"close": 300.0,
"high": 302.0,
"low": 294.0
},
"volume": 22000
},
{
"date": "2024-01-09",
"prices": {
"open": 294.0,
"close": 295.0,
"high": 296.0,
"low": 293.0
},
"volume": 21000
}
],
"locations": ["Berlin", "Paris"]
}
]
Each stock is a dictionary with fields for name, symbol, sector, and current price.
historical_datais a list of dictionaries, each representing a day's data. Within this,pricesis another dictionary with open, close, high, and low values.volumerepresents the trading volume for that day.locationsis a list of strings indicating where the company operates.
Q 1: Read Data
Task: Read and display the current price of "Company B".
Q2: Write Data
Task: Add a new company "Company D" with some initial data to the stocks list.
Q 3: Update Data
Task: Update the current price of "Company C" to 310.0.
Q 4: Delete Data
Task: Remove the historical data for "Company A" on "2024-01-09".
Q5: Read Nested Data
Task: Read and display the closing price of "Company B" on "2024-01-10".
Q6: Update Nested Data
Task: Change the opening price of "Company A" on "2024-01-10" to 99.0.
Q 7: Add Nested Data
Task: Add a new historical data entry for "Company C" on "2024-01-11".
Q 8: Delete an Item from a List Inside a Dictionary
Task: Remove "Singapore" from the locations of "Company B".
Problem 2 :Investment Portfolio
This data structure represents an investment portfolio, including various assets like stocks, bonds, and mutual funds, along with their respective holdings and performance metrics.
investment_portfolio = {
"investor_name": "Jane Doe",
"portfolio_id": "JD1234",
"assets": {
"stocks": [
{
"ticker": "AAPL",
"quantity": 50,
"purchase_price": 120.00,
"current_price": 130.00
},
{
"ticker": "MSFT",
"quantity": 30,
"purchase_price": 200.00,
"current_price": 210.00
}
],
"bonds": [
{
"identifier": "US123456",
"quantity": 100,
"purchase_price": 1000.00,
"current_price": 1020.00,
"maturity_date": "2030-01-01"
}
],
"mutual_funds": [
{
"name": "XYZ Growth Fund",
"quantity": 200,
"purchase_price": 15.00,
"current_price": 15.50
}
]
},
"cash_holdings": 10000.00,
"investment_goals": {"retirement": 2035, "education": 2025}
}
Q 1: Read Data
Task: Display the current price of the mutual fund "XYZ Growth Fund".
Q 2: Write Data
Task: Add a new stock with ticker "GOOG", 40 shares, a purchase price of 1500.00, and a current price of 1520.00 to the stocks in the assets.
Q3: Update Data
Task: Update the quantity of "AAPL" stock to 60.
Q4: Delete Data
Task: Remove the bond with identifier "US123456" from the bonds in assets.
Q 5: Read Nested Data
Task: Read and display the maturity date of the bond in the portfolio.
Q 6: Update Nested Data
Task: Change the current price of "MSFT" stock to 215.00.
Q7: Add Nested Data
Task: Add a new goal "vacation" set for the year 2028 in the investment goals.
Q 8: Delete an Item from a List Inside a Dictionary
Task: Remove the mutual fund "XYZ Growth Fund" from the portfolio.
Problem 3: Financial Market Analysis
A data structure for analyzing financial markets, including sectors, companies within each sector, and their stock performance.
market_analysis = {
"sectors": {
"Technology": {
"companies": [
{"name": "Tech Corp A", "ticker": "TCA", "price_change": 5.2},
{"name": "Tech Corp B", "ticker": "TCB", "price_change": -3.1}
]
},
"Healthcare": {
"companies": [
{"name": "Health Inc A", "ticker": "HIA", "price_change": 4.0},
{"name": "Health Inc B", "ticker": "HIB", "price_change": 2.5}
]
}
},
"index_performance": {
"S&P 500": {"change": 1.5},
"NASDAQ": {"change": 2.3},
"DOW JONES": {"change": -1.2}
},
"notable_events": [
("2024-01-10", "Interest Rate Decision", "Fed raises rates by 0.25%"),
("2024-01-15", "Earnings Report", "Tech Corp A reports better than expected earnings")
]
}
Q 1: Read Data
Task: Display the price change of "Health Inc B".
Q 2: Write Data
Task: Add a new sector "Energy" with one company "Energy Co A" having a ticker "ECA" and a price change of -2.0.
Q 3: Update Data
Task: Update the price change of "Tech Corp A" to 6.0.
Q 4: Delete Data
Task: Remove the "DOW JONES" index from index_performance.
Q 5: Read Nested Data
Task: Read and display the change in "NASDAQ" index performance.
Q 6: Update Nested Data
Task: Change the name of "Health Inc A" to "Health Inc Alpha".
Q 7: Add Nested Data
Task: Add a new notable event on "2024-01-20" stating "Acquisition", with the description "Tech Corp B acquires smaller competitor".
Q 8: Delete an Item from a List Inside a Dictionary
Task: Remove the first notable event from the list.
Problem 4: Foreign Exchange Rates
A data structure for tracking foreign exchange rates and historical changes.
foreign_exchange = {
"base_currency": "USD",
"exchange_rates": {
"EUR": {
"current_rate": 0.85,
"historical_rates": [
{"date": "2024-01-10", "rate": 0.84},
{"date": "2024-01-09", "rate": 0.85}
]
},
"JPY": {
"current_rate": 110.00,
"historical_rates": [
{"date": "2024-01-10", "rate": 109.50},
{"date": "2024-01-09", "rate": 110.20}
]
}
}
}
Q1: Read Data
Task: Display the current exchange rate for the Euro (EUR).
Q2: Write Data
Task: Add a new currency, the British Pound (GBP), with a current rate of 0.75 and two historical rates: 0.76 on "2024-01-10" and 0.77 on "2024-01-09".
Q 3: Update Data
Task: Update the current exchange rate of the Japanese Yen (JPY) to 111.00.
Q4: Delete Data
Task: Remove the historical rates for the Euro (EUR).
Q 5: Read Nested Data
Task: Read and display the exchange rate of the Japanese Yen (JPY) on "2024-01-10".
Q 6: Update Nested Data
Task: Change the rate of the Euro (EUR) on "2024-01-10" to 0.83.
Q 7: Add Nested Data
Task: Add a new historical rate for the Japanese Yen (JPY) on "2024-01-11" with a rate of 109.00.
Q 8: Delete an Item from a List Inside a Dictionary
Task: Remove the historical rate of the Japanese Yen (JPY) on "2024-01-09".
Problem 5: Credit Risk Assessment
A complex structure for assessing credit risk of different individuals based on their financial profiles.
credit_risk_profiles = {
"individuals": [
{
"name": "John Doe",
"credit_score": 750,
"outstanding_loans": {
"auto_loan": {"amount": 20000, "interest_rate": 3.5},
"home_loan": {"amount": 150000, "interest_rate": 2.8}
},
"payment_history": [("2024-01-10", "On Time"), ("2024-01-01", "Late")]
},
{
"name": "Jane Smith",
"credit_score": 680,
"outstanding_loans": {
"credit_card": {"amount": 5000, "interest_rate": 12.0}
},
"payment_history": [("2024-01-10", "On Time")]
}
]
}
Q 1: Read Data
Task: Display the interest rate for John Doe's home loan.
Q 2: Write Data
Task: Add a new individual "Alice Johnson" with a credit score of 720, no outstanding loans, and no payment history.
Q 3: Update Data
Task: Update Jane Smith's credit score to 700.
Q 4: Delete Data
Task: Remove the auto loan entry from John Doe's outstanding loans.
Q 5: Read Nested Data
Task: Read and display the latest payment status of John Doe.
Q 6: Update Nested Data
Task: Change the amount of Jane Smith's credit card loan to 5500.
Q 7: Add Nested Data
Task: Add a new payment history entry for John Doe on "2024-01-15" marked as "On Time".
Q 8: Delete an Item from a List Inside a Dictionary
Task: Remove the first payment history entry of Jane Smith.
Problem 6: Hedge Fund Portfolio
A complex structure for a hedge fund's investment portfolio, detailing various types of investments and their performance.
hedge_fund_portfolio = {
"fund_name": "Alpha Investments",
"portfolio_value": 50000000,
"investments": [
{
"type": "Equity",
"holdings": [
{"ticker": "AAPL", "quantity": 10000, "average_buy_price": 120},
{"ticker": "TSLA", "quantity": 5000, "average_buy_price": 600}
]
},
{
"type": "Fixed Income",
"holdings": [
{"bond_issue": "US Treasuries", "amount": 10000000, "yield": 1.5}
]
},
{
"type": "Derivatives",
"holdings": [
{"instrument": "Options", "details": {"underlying": "GOOGL", "type": "Call", "strike_price": 1500}}
]
}
],
"performance_metrics": {
"year_to_date_return": 5.2,
"five_year_annualized_return": 7.1
}
}
Q 1: Read Data
Task: Display the quantity of "TSLA" equity held in the portfolio.
Q 2: Write Data
Task: Add a new investment type "Real Estate" with one holding of a property "Downtown Complex" valued at 2000000.
Q 3: Update Data
Task: Update the portfolio value to 51000000.
Q 4: Delete Data
Task: Remove the "Derivatives" investment from the portfolio.
Q 5: Read Nested Data
Task: Read and display the yield of the "US Treasuries" bond.
Q 6: Update Nested Data
Task: Change the average buy price of "AAPL" equity to 125.
Q 7: Add Nested Data
Task: Add a new equity holding for "AMZN" with a quantity of 3000 and an average buy price of 3100.\
Q 8: Delete an Item from a List Inside a Dictionary
Task: Remove the first holding (AAPL) under the "Equity" type.
