019f8fd211
git-subtree-dir: users/wpcarro git-subtree-mainline:464bbcb15cgit-subtree-split:24f5a642afChange-Id: I6105b3762b79126b3488359c95978cadb3efa789
87 lines
2.3 KiB
Python
87 lines
2.3 KiB
Python
# The file '2010.census.txt' contains summary statistics from the 2010 United
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# States census including household income. The data is in an unspecified
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# format.
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# Find the average of the column called:
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# 'MEDIAN HOUSEHOLD INCOME'
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# Ideally the solution should be a command line script, of the form:
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# $ ./solution [options] [file...]
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# The solution may be written in any language, Python is preferred but not
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# required.
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# Google, stack overflow, etc. usage is allowed.
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import requests
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import csv
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url = "https://assets.tryramp.com/interview/census/2010.census.txt"
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column = 'MEDIAN HOUSEHOLD INCOME'
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columns = [
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'CENSUS YEAR',
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'TRACT',
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'BLOCK GROUP',
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'FIPS ID',
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'TOTAL POPULATION',
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'POPULATION WHITE',
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'POPULATION BLACK',
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'POPULATION ASIAN',
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'POPULATION OTHER',
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'POPULATION AMERICAN INDIAN',
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'POPULATION PACIFIC ISLANDER',
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'POPULATION ONE RACE',
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'POPULATION MULTI RACE',
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'POPULATION 25 OLDER',
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'MEDIAN AGE',
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'MEDIAN HOUSEHOLD INCOME',
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'HIGH SCHOOL MALE',
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'HIGH SCHOOL MORE MALE',
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'COLLEGE 1 YR LESS MALE',
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'COLLEGE 1 YR MORE MALE',
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'ASSOCIATES DEGREE MALE',
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'BACHELORS DEGREE MALE',
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'MASTERS DEGREE MALE',
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'PROFESSIONAL DEGREE MALE',
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'DOCTORAL DEGREE MALE',
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'HIGH SCHOOL FEMALE',
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'HIGH SCHOOL MORE FEMALE',
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'COLLEGE 1 YR LESS FEMALE',
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'COLLEGE 1 YR MORE FEMALE',
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'ASSOCIATES DEGREE FEMALE',
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'BACHELORS DEGREE FEMALE',
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'MASTERS DEGREE FEMALE',
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'PROFESSIONAL DEGREE FEMALE',
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'DOCTORAL DEGREE FEMALE',
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'PERCENT 25 YR OVER HIGH SCHOOL MORE',
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'HOUSING UNITS',
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'OCCUPIED HOUSING UNITS',
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'OWNER OCCUPIED HOUSING',
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'RENTER OCCUPIED HOUSING',
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'PERCENT OWNER OCCUPIED',
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'PERCENT RENTER OCCUPIED',
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'MEDIAN HOUSE VALUE OWNER OCCUPIED',
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'MEDIAN YEAR BUILT',
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'VACANCY RATES',
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]
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def average(xs):
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return sum(xs) / len(xs)
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def parse_body(body):
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return list(csv.DictReader(body.split('\n')[1:], delimiter='|', fieldnames=columns))
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def main():
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res = requests.get(url)
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if res.status_code not in {200}:
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raise Exception("Unexpected status code: {}".format(res.status_code))
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return average([int(d.get(column))
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for d in parse_body(res.text)
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if int(d.get(column)) >= 0])
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print(main())
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