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HW1: Exercise in Basic Python data structures.
Reproduce the following python interactive listing using different data of
your choosing, e.g., choose different variable names and data strings other
than ‘Bob Smith’ and ‘Sue Jones’
>>> bob = ['Bob Smith', 42, 30000, 'software']
>>> sue = ['Sue Jones', 45, 40000, 'hardware']
>>> bob[0], sue[2]
('Bob Smith', 40000)
# fetch name, pay
>>> bob[0].split()[-1]
'Smith'
# what's bob's last name?
>>> sue[2] *= 1.25
>>> sue
# give sue a 25% raise
['Sue Jones', 45, 50000.0, 'hardware']
>>> people = [bob, sue ]
# reference in list of lists
>>> for person in people:
print(person)
['Bob Smith', 42, 30000, 'software']
['Sue Jones', 45, 50000.0, 'hardware']
>>> people[1][0]
'Sue Jones'
>>> for person in people:
print(person[0].split()[-1])
person[2] *= 1.20
# print last names
# give each a 20% raise
Smith
Jones
>>> for person in people: print(person[2])
# check new pay
36000.0
60000.0
>>> pays = [person[2] for person in people]
>>> pays
# collect all pay
[36000.0, 60000.0]
>>> pays = map((lambda x: x[2]), people)
3.X)
>>> list(pays)
[36000.0, 60000.0]
# ditto (map is a generator in
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>>> sum(person[2] for person in people)
built-in
# generator expression, sum
96000.0
>>> people.append(['Tom', 50, 0, None])
>>> len(people)
3
>>> people[-1][0]
'Tom'
>>> NAME, AGE, PAY = range(3)
>>> bob = ['Bob Smith', 42, 10000]
>>> bob[NAME]
# 0, 1, and 2
'Bob Smith'
>>> PAY, bob[PAY]
(2, 10000)
>>> bob = [['name', 'Bob Smith'], ['age', 42], ['pay', 10000]]
>>> sue = [['name', 'Sue Jones'], ['age', 45], ['pay', 20000]]
>>> people = [bob, sue]
>>> for person in people:
print(person[0][1], person[2][1])
# name, pay
Bob Smith 10000
Sue Jones 20000
>>> [person[0][1] for person in people]
# collect names
['Bob Smith', 'Sue Jones']
>>> for person in people:
print(person[0][1].split()[-1])
person[2][1] *= 1.10
# get last names
# give a 10% raise
Smith
Jones
>>> for person in people: print(person[2])
['pay', 11000.0]
['pay', 22000.0]
>>> for person in people:
for (name, value) in person:
if name == 'name': print(value)
Bob Smith
# find a specific field
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Sue Jones
>>> def field(record, label):
for (fname, fvalue) in record:
if fname == label:
return fvalue
# find any field by name
>>> field(bob, 'name')
'Bob Smith'
>>> field(sue, 'pay')
22000.0
>>> for rec in people:
print(field(rec, 'age'))
# print all ages
42
45
>>> bob = {'name': 'Bob Smith', 'age': 42, 'pay': 30000, 'job': 'dev'}
>>> sue = {'name': 'Sue Jones', 'age': 45, 'pay': 40000, 'job': 'hdw'}
>>> bob['name'], sue['pay']
# not bob[0], sue[2]
('Bob Smith', 40000)
>>> bob['name'].split()[-1]
'Smith'
>>> sue['pay'] *= 1.10
>>> sue['pay']
44000.0
>>> bob = dict(name='Bob Smith', age=42, pay=30000, job='dev')
>>> sue = dict(name='Sue Jones', age=45, pay=40000, job='hdw')
>>> bob
{'pay': 30000, 'job': 'dev', 'age': 42, 'name': 'Bob Smith'}
>>> sue
{'pay': 40000, 'job': 'hdw', 'age': 45, 'name': 'Sue Jones'}
>>>
>>>
>>>
>>>
>>>
>>>
sue = {}
sue['name']
sue['age']
sue['pay']
sue['job']
sue
=
=
=
=
'Sue Jones'
45
40000
'hdw'
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{'job': 'hdw', 'pay': 40000, 'age': 45, 'name': 'Sue Jones'}
>>> names = ['name', 'age', 'pay', 'job']
>>> values = ['Sue Jones', 45, 40000, 'hdw']
>>> list(zip(names, values))
[('name', 'Sue Jones'), ('age', 45), ('pay', 40000), ('job', 'hdw')]
>>> sue = dict(zip(names, values))
>>> sue
{'job': 'hdw', 'pay': 40000, 'age': 45, 'name': 'Sue Jones'}
>>> fields = ('name', 'age', 'job', 'pay')
>>> record = dict.fromkeys(fields, '?')
>>> record
{'job': '?', 'pay': '?', 'age': '?', 'name': '?'}
>>> bob
{'pay': 30000, 'job': 'dev', 'age': 42, 'name': 'Bob Smith'}
>>> sue
{'job': 'hdw', 'pay': 40000, 'age': 45, 'name': 'Sue Jones'}
>>> people = [bob, sue]
# reference in a list
>>> for person in people:
print(person['name'], person['pay'], sep=', ')
# all pay
Bob Smith, 30000
Sue Jones, 40000
>>> for person in people:
if person['name'] == 'Sue Jones':
print(person['pay'])
# fetch sue's pay
40000
>>> names = [person['name'] for person in people]
>>> names
# collect names
['Bob Smith', 'Sue Jones']
>>> list(map((lambda x: x['name']), people))
# ditto, generate
['Bob Smith', 'Sue Jones']
>>> sum(person['pay'] for person in people)
70000
>>> for person in people:
# sum all pay
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print(person['name'].split()[-1])
person['pay'] *= 1.10
# last name
# a 10% raise
Smith
Jones
>>> for person in people: print(person['pay'])
33000.0
44000.0
>>> bob2 = {'name':
'age':
'job':
'pay':
{'first': 'Bob', 'last': 'Smith'},
42,
['software', 'writing'],
(40000, 50000)}
>>> bob2['name']
# bob's full name
{'last': 'Smith', 'first': 'Bob'}
>>> bob2['name']['last']
# bob's last name\
'Smith'
>>> bob2['pay'][1]
# bob's upper pay
50000
>>> for job in bob2['job']: print(job)
# all of bob's jobs
software
writing
>> bob2['job'][-1]
# bob's last job
'writing'
>>> bob2['job'].append('janitor')
# bob gets a new job
>>> bob2
{'job': ['software', 'writing', 'janitor'], 'pay': (40000, 50000), 'age': 42,
'name':
{'last': 'Smith', 'first': 'Bob'}}
>>> bob = dict(name='Bob Smith', age=42, pay=30000, job='dev')
>>> sue = dict(name='Sue Jones', age=45, pay=40000, job='hdw')
>>> bob
{'pay': 30000, 'job': 'dev', 'age': 42, 'name': 'Bob Smith'}
>>> db = {}
>>> db['bob'] = bob
>>> db['sue'] = sue
# reference in a dict of dicts
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>>> db['bob']['name']
# fetch bob's name
'Bob Smith'
>>> db['sue']['pay'] = 50000
>>> db['sue']['pay']
# change sue's pay
# fetch sue's pay
50000
>>> db
{'bob': {'pay': 30000, 'job': 'dev', 'age': 42, 'name': 'Bob Smith'}, 'sue':
{'pay': 50000, 'job': 'hdw', 'age': 45, 'name': 'Sue Jones'}}
>>> import pprint
>>> pprint.pprint(db)
{'bob': {'age': 42, 'job': 'dev', 'name': 'Bob Smith', 'pay': 30000},
'sue': {'age': 45, 'job': 'hdw', 'name': 'Sue Jones', 'pay': 50000}}
>>> for key in db:
print(key, '=>', db[key]['name'])
bob => Bob Smith
sue => Sue Jones
>>> for key in db:
print(key, '=>', db[key]['pay'])
bob => 30000
sue => 50000
>>> for key in db:
print(db[key]['name'].split()[-1])
db[key]['pay'] *= 1.10
Smith
Jones
>>> for record in db.values(): print(record['pay'])
33000.0
55000.0
>>> x = [db[key]['name'] for key in db]
>>> x
['Bob Smith', 'Sue Jones']
>>> x = [rec['name'] for rec in db.values()]
>>> x
['Bob Smith', 'Sue Jones']
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>>> db['tom'] = dict(name='Tom', age=50, job=None, pay=0)
>>> db['tom']
{'pay': 0, 'job': None, 'age': 50, 'name': 'To'}
>>> db['tom']['name']
'Tom'
>>> list(db.keys())
['bob', 'sue', 'tom']
>>> len(db)
3
>>> [rec['age'] for rec in db.values()
[42, 45, 50]