Market Research: If you're in the travel industry or running a travel-related business, analyzing flight price data can help you understand market trends, customer preferences, and demand patterns. This information can inform pricing strategies and marketing efforts.
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Sample flight data (You can replace this with your actual data)
flight_data = [
{"airline": "Airline A", "route": "Route 1", "date": "2023-09-15", "price": 300},
{"airline": "Airline B", "route": "Route 2", "date": "2023-09-15", "price": 250},
{"airline": "Airline A", "route": "Route 1", "date": "2023-09-16", "price": 320},
{"airline": "Airline B", "route": "Route 2", "date": "2023-09-16", "price": 260},
# Add more flight data here...
]
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Function to calculate average flight price for a specific route and airline
def calculate_average_price(flight_data, airline, route):
prices = [flight["price"] for flight in flight_data if flight["airline"] == airline and flight["route"] == route]
if not prices:
return None
return sum(prices) / len(prices)
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In this script:
flight_data represents the sample flight price data for different airlines and routes. Replace this with your actual data or fetch it through web scraping or an API.
The calculate_average_price function calculates the average flight price for a specific route and airline based on the provided dataset.
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Example usage
airline = "Airline A"
route = "Route 1"
average_price = calculate_average_price(flight_data, airline, route)
if average_price is not None:
print(f"Average flight price for {airline} on {route} is ${average_price:.2f}")
else:
print(f"No data available for {airline} on {route}")
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You can further enhance this script by:
Extending the dataset with more historical flight price data.
Analyzing trends in prices over time, such as monthly or seasonal variations.
Creating visualizations to represent price trends.
Incorporating additional market research factors, such as customer reviews, competition analysis, and demand patterns.
By analyzing flight price data, you can gain insights into market trends and customer preferences, allowing you to make informed decisions for pricing strategies and marketing efforts in the travel industry.
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