Sets and Dictionaries in Python: Aggregation (Learner Version)

Objectives

Recognize problems that can be solved by aggregating values.
Use dictionaries to aggregate values.
Explain why actual data values should be used as initializers rather than "impossible" values.

Lesson

How early in the day did we see each kind of bird?



In [2]:

    
!cat some_birds.txt









    



2010-07-03    05:38    loon
2010-07-03    06:02    goose
2010-07-03    06:07    loon
2010-07-04    05:09    ostrich   # hallucinating?
2010-07-04    05:29    loon

Read data, returning list of tuples



In [5]:

    
def read_observations(filename):
    '''Read data, returning [(date, time, bird)...].'''

    reader = open(filename, 'r')
    result = []

    for line in reader:
        fields = line.split('#')[0].strip().split()
        assert len(fields) == 3, 'Bad line "%s"' % line
        result.append(fields)

    return result

Turn list of tuples into dictionary



In [6]:

    
def earliest_observation(data):
    '''How early did we see each bird?'''

    result = {}
    for (date, time, bird) in data:
        if bird not in result:
            result[bird] = time
        else:
            result[bird] = min(result[bird], time)

    return result

Test



In [7]:

    
entries = read_observations('some_birds.txt')
result = earliest_observation(entries)
print result









    



{'loon': '05:29', 'goose': '06:02', 'ostrich': '05:09'}

Which birds did we see on a particular day?



In [8]:

    
def birds_by_date(data):
    '''Which birds were seen on each day?'''

    result = {}
    for (date, time, bird) in data:
        if date not in result:
            result[date] = {bird}
        else:
            result[date].add(bird)

    return result

print birds_by_date(entries)









    



{'2010-07-04': set(['loon', 'ostrich']), '2010-07-03': set(['loon', 'goose'])}

Which bird (or birds, in case of ties) did we see least frequently?
Try to do it without doing two passes through the data (to find the least value)
And without choosing some arbitrary large initial value for least
Solution: initialize least to None and handle its replacement as a special case



In [9]:

    
def least_common_birds(data):
    '''Which bird or birds have been seen least frequently?'''
    
    counts = count_by_bird(data) # need to write this
    least = min(counts.values())
    result = set()
    for bird in counts:
        if counts[bird] == least:
            result.add(bird)
    return result

# Helper function.
def count_by_bird(data):
    '''How many times was each bird seen?'''
    result = {}
    for (date, time, bird) in data:
        if bird not in result:
            result[bird] = 0
        result[bird] += 1
    return result

# Test.
print least_common_birds(entries)









    



set(['goose', 'ostrich'])

Key Points

Use dictionaries to count things.
Initialize values from actual data instead of trying to guess what values could "never" occur.