Database System Concepts
Database System Concepts
7th Edition
ISBN: 9780078022159
Author: Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher: McGraw-Hill Education
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Transcribed Image Text:Part C - advanced file reading
You will need a Python repl to solve part C.
Define a Python function named expensive_counties that has two parameters. The first parameter is a string representing the name of a text file. Each line of this text file will be a state code. The second
parameter is a string representing the name of a CSV file. The CSV file will be portion of the US government's dataset documenting median rents in each US county. Each row in the CSV file has the format:
Area Name, Efficiency, 1-Bedroom, 2-Bedroom, 3-Bedroom, 4-Bedroom, State Code
Your function will need to use the accumulator pattern to return a new list. You will need to add to this list the Area Name from every row that meets 2 criteria:
(1) The state code (the column at index 6) was a line in the text file named in the first parameter; AND
(2) The median rent on a 1-bedroom apartment (the column at index 2) is over 1000.
Important Hints:
* You will really, really want to use the built-in csv library because it makes processing a CSV file much easier and Area Name values may include commas.
* Reusing 1 of your functions part A will be very helpful in solving this problem.
Sample test cases:
expensive_counties ("empty.txt","empty.csv") would evaluate to [] (finds bug if accumulator variable not initialized correctly)
expensive_counties("codes.txt", "simple.csv") would evaluate to ['San Fran', 'Sunnyvale, CA', 'New York City'] (finds bug if accumulator variable not updated correctly)
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