Airlines come and go. Some operate for only a few years before financial pressures force them to close; others endure for decades, surviving recessions, deregulation, fuel crises, and pandemics. The airlines.csv file (right-click, open in new tab or window) contains information about commercial airlines from around the world. The columns are labeled in the file. The ceased column contains 0 for airlines still operating at the time the data file was compiled. Write a function named top_carriers that accepts four arguments: a file name, a beginning year, an ending year, and a number n. Return a 2-dimensional NumPy array containing the name and country of the n longest-operating (defined as ceased – founded) airlines that ceased operations between the beginning year and ending year (inclusive). Include in your analysis only those airlines whose operations have ended. For full credit, your function should use NumPy concepts and techniques to calculate and return the result without using loops or list comprehensions. In [1]: top_carriers(‘airlines.csv’, 1920, 2025, 3) Out[1]: array([[‘Czech Airlines’, ‘Czech Republic’], [‘Mexicana’, ‘Mexico’], [‘Northwest Airlines’, ‘USA’]], dtype=’
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