Some datasets for the project (all included in the data folder)
-
route-info: Distance between ADJACENT cities, the final column is the toll cost to travel between two adjacent cities. -
air-info: Flight distance between two cities (if there exists a flight route). -
heuristics: The distance as crow flies between two arbitrary cities (32x32 matrix) -
city-label: The label for each city in the 32 given cities. -
Explain data processing
- Use Pandas to read the 'route-info.csv' and 'air-info.csv' file
- Convert their data frame into numpy array( data and data1)
- Create a column present the total cost between cities( sum of path cost and toll station) ( fee )
- Using two matrix data and fee to create a new matrix contain total cost between adjacent cities ( final_fee)
- Merge the cost data of using taxi to travel and the cost data of flights.
- create a dictionary named 'map'
- 'map' is a dictionary with key is a city name and value is a list of adjacent cities and theirs cost to that city. for example : { laocai:[ (HaGiang,300000),(VietTri,312000)]}
- Using two file 'city-label' and 'heuristics.csv' to write a function to return heuristics dict of a city