ISYS90088 Introduction to Application Development
Week 8 – Contd. from week 6: tuples & Dictionaries
Semester 2 , 2018
Dr Antonette Mendoza
s
1
Objectives
After completing this lecture, you will be able to:
• Work with Tuples
• Work with Dictionaries
2
Lists, tuples and Dictionaries
• A list allows the programmer to manipulate a sequence of data values of any types
– Indicate by enclosing its elements in []
3
Lists, tuples and Dictionaries
• A list allows the programmer to manipulate a sequence of data values of any types
– Indicate by enclosing its elements in []
• A tuple resembles a list, but is immutable
– Indicate by enclosing its elements in ()
4
Tuples
• A tuple resembles a list, but is immutable
– Indicate by enclosing its elements in ()
• Thedifferencesbetweentuplesandlistsare:
– the tuples cannot be changed unlike lists
– tuples use parentheses, whereas lists use square brackets
• Creating a tuple is as simple as putting different comma-separated values.
5
Tuples
• Lists can be converted to tuples; two sets of tuples can be concatenated
• For example:
• Most of the operators and functions used with lists can be used in a similar fashion with tuples
Fundamentals of Python: First Programs
6
Tuples
• Most of the operators and functions used with lists can be used in a similar fashion with tuples:
– The empty tuple is written as two parentheses containing nothing
tup1 = ();
– To write a tuple containing a single value you have to include a comma, even though there is only one value −
tup1 = (50,);
7
Tuples
• Most of the operators and functions used with lists can be used in a similar fashion with tuples:
– The empty tuple is written as two parentheses containing nothing
tup1 = ();
for lists: list1 = []
– To write a tuple containing a single value you have to include a comma, even though there is only one value −
tup1 = (50,);
For lists: list1 = [50]
8
Tuples
• Likestringindices,tupleindicesstartat0.Theoperations performed are: concatenation, iteration, in, slicing and indexing
• AccessingValuesinTuples:usethesquarebracketsforslicing along with the index or indices to obtain value available at that index.
• UpdatingTuples-Tuplesareimmutablewhichmeansyou cannot update or change the values of tuple elements.
• DeleteTupleElements-Removingindividualtupleelementsis not possible.
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Tuples
Ø To explicitly remove an entire tuple, just use the del statement. For example:
tuple1 = (‘physics’, ‘chemistry’, 1997, 2000)
print (tuple1)
del tuple1
print (“After deleting tuple : “)
print (tuple1)
• Thisproducesthefollowingresult(checkexample).Noteanexception raised, this is because after del tup tuple does not exist any more.
Example:
>>>tuple3 = (1,2,3)
>>>list(tuple3)
[1,2,3]
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Tuples
Built-in Tuple Functions can be used:
## length, max and min in a tuple
tuple1, tuple2 = (‘zar’, ‘xyz’, ‘zara’), (100, 500, 20)
print (“Max value element : “, max(tuple1))
print (“Max value element : “, max(tuple2))
print (“Min value element : “, min(tuple1))
print (“Min value element : “, min(tuple2))
print (“First tuple length : “, len(tuple1))
print (“Second tuple length : “, len(tuple2))
#convert a list of items into tuples
Listofitems = [23, ‘years’, ‘dogs’, ‘cats’];
toaTuple = tuple(Listofitems)
print (“Tuple elements : “, toaTuple)
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Difference between lists and tuples
• Lists are mutable. Lists however have this method called append. In order for most of your appends to be fast, python will actually create a larger array in memory just in case you append.
• This way, when you do append, it does not have to recreate a list every time. You can add items to the list .How would it know that you don’t want to maybe add a 4th 5th 6th element? To play safe, we assume you might want more in the memory
• On the other hand, by using tuples, it tells python that you want an immutable structure. Give me space for 3 things, fill those slots up, and move on.
• Sincetuplesareimmutable,thismeansthattuplesarefixed.Wecan’tdo anything to them in memory.
• Performance:processingoftuplesissaidtobefasterthanlistprocessing
• Usingtuplesissafe:Sincetheyareimmutable,wecantchangecontentof the tuple. This can be useful when you don’t want any data modified by your code
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Lists, tuples and Dictionaries
• A list allows the programmer to manipulate a sequence of data values of any types
– Indicatebyenclosingitselementsin[]
• A tuple resembles a list, but is immutable
– Indicate by enclosing its elements in ()
• A dictionary organizes data values by association with other data values rather than by ‘sequential position’
• Lists and dictionaries provide powerful ways to organize data in useful and interesting applications
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Dictionaries
• A dictionary organizes information by
association, not position
– Example: When you use a dictionary to look up the definition of “Mammal,” you don’t start at page 1; instead, you turn to the words beginning with “M”
• Data structures organized by association are also called tables or association lists
• In Python, a dictionary associates a set of keys with data values
Fundamentals of Python: First Programs 14
Dictionary Literals
• A Python dictionary is written as a sequence of key/ value pairs separated by commas
– Pairs are sometimes called entries – Enclosed in curly braces ({ and })
– A colon (:) separates a key and its value
• Examples:
{‘Sarah’:’476-3321′, ‘Nathan’:’351-7743′} #A Phone book
{‘Name’:’Molly’, ‘Age’:18} # Personal information {} #An empty dictionary
Fundamentals of Python: First Programs
15
Mixing data types in a dictionary
• Keys in a dictionary are immutable but their associated values can be of any type. For example, the values can be lists.
d1 = {‘matt’: [23, 2000, 2010], ‘anne’: [25, 2545, 2012], ‘jack’: [34, 2500, 2011]}
• Thevaluesstoredinasingledictionarycanbeofdifferenttypes.For example one element in the dictionary can be a string, another an integer, another a float etc..
Example:
>>> employee_record = {‘name’:’kevin’, ‘Age’: 43,
‘ID’:23145, ‘payrate’:24.99}
>>>employee_record
{‘Age’: 43, ‘name’: ‘kevin’, ‘ID’: 23145,
‘payrate’: 24.99}
Properties of Dictionary Keys
Dictionary values have no restrictions. However, same is not true for the keys. There exists a mapping between keys and the values. There are two important points to remember about dictionary keys −
(a) More than one entry per key not allowed. Which means no duplicate key is allowed. When duplicate keys encountered during assignment, the last assignment wins. For example −
>>>dict = {‘Name’: ’Anne’, ‘Age’: 10, ‘Name’: ’Jack’} >>> print (“dict[‘Name’]: “, dict[‘Name’])
When the above code is executed, it produces the following result −
dict[‘Name’]: ‘jack’ => Why?
Dictionaries: as hash tables to explain immutability
(b) Keys are immutable. For example, when you insert a key into a hash table, the hash table asks the key for its hash code, and remembers it along with the key itself and the associated value. When you later perform a lookup, the hash table asks the key you’re looking for its hash code, and can very quickly find all the keys in the table that have the same hash code.
• If a key is mutable, then finding the value associated with the unique key is not possible – the hash table would be messed up as you wont know accurately the associated value to the specific key.
Adding Keys and Replacing Values
• Add a new key/value pair to a dictionary using []: • Example:
• Use [] to replace a value at an existing key: Fundamentals of Python: First Programs
19
Accessing Values
• Use[]toobtainthevalueassociatedwithakey
– If key is not present in dictionary, an error is raised
• Iftheexistenceofakeyisuncertain,testforitusingthe dictionary method get
Fundamentals of Python: First Programs
20
Deleting elements
• To delete an existing key-value pair from a dictionary, use the del statement. After the statement is executed, the key and its associated value will be deleted from the dictionary.
• If the key does not exist, a KeyError exception is raised. Syntax:
del dictionary_name[key]
Note: To prevent the KeyError from being raised, use the in opeartor to determine whether the key exists before you try to delete it and its associated value.
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Dict: Del and Clear
>>>dict = {‘Name’: ’Anne’, ‘Age’: 10, ‘Class’: ’Third’}
>>>del dict[‘Name’]; # remove entry with key ‘Name’
What is the output?
>>>dict.clear(); # remove all entries in dict
What is the output?
>>>del dict ; # delete entire dictionary
What is the output?
Using in and not in operators to test for a value in a Dictionary
#illustrate in operator to find a value in dict phonebook = {‘jack’:’0423123′, ‘jill’:’2345433′,
‘jane’:’3334444′}
if ‘jack’ in phonebook: print(phonebook[‘jack’])
else:
print(‘not found’)
# to illustrate not in operator to find a value in dictionary
if ‘jacky’ not in phonebook: print(‘not found’)
Using the for loop to iterate over a Dictionary – traverse thru’ a dictionary
for var in
statement
statement
…
…
Example:
employee_record = {‘name’:’kevin’, ‘Age’: 43,
‘ID’:23145, ‘payrate’:24.99}
for key in employee_record:
print(key)
Note: when the dict is printed, the order is different from the initial order in the dict. This means accessing elements using an index is not possible in dictionaries.
Traversing a Dictionary
• To print all of the keys and their values:
info = {‘apple’: ‘jack’, ‘banana’:’jill’, ‘pears’: ‘brad’}
• Alternative: Use the dictionary method items()
– Entries are represented as tuples within the list • You can sort the list first:
25
Assessing information: check this!
>>> d1 = {‘matt’: [23, 2000, 2010],
‘anne’: [25, 2545, 2012], ‘jack’:
[34, 2500, 2011]}
>>> if ‘jack’ in d1:
print(d1[‘jack’])
[34, 2500, 2011]
>>> d1[‘jack’][2]
2011
Example code : check this out!
info = {‘apple’: [‘jack’, ‘jane’], ‘banana’:
[‘jill’], ‘pears’: [‘brad’, ‘sally’]}
keylist = list (info.keys())
keylist.sort() #sorted this list
for key in keylist:
print(key, info[key])
print(key, info[key][0])
What does this output?
Try this – dictionary with a list of values for a key
list1 = []
d1 = {‘matt’: [23, 2000, 2010], ‘anne’:
[25, 2545, 2012], ‘jack’:
[34, 2500, 2011]}
for list1 in d1[‘matt’]:
print(list1)
What is the output?
Getting the number of elements in a dictionary using len
• Use the built in method called len Example:
>>> employee_record = {‘name’:’kevin’,
‘Age’: 43, ‘ID’:23145, ‘payrate’:24.99}
>>>len(employee_record)
4
Other Dictionary methods: clear • Use the built in method called clear
Syntax:
dictionary_name.clear()
Example:
>>> employee_record = {‘name’:’kevin’,
‘Age’: 43, ‘ID’:23145, ‘payrate’:24.99}
>>> employee_record.clear()
>>> employee_record
{}
Other Dictionary methods: get • Usethebuiltinmethodcalledget
• Whenexecuted,thismethodsoutputsthevalueassociatedwith the key that is searched. If not present, will output the default value as shown in the example.
Syntax:
dictionary_name.get(key, default)
Example:
>>> employee_record = {‘name’:’kevin’, ‘Age’:
43, ‘ID’:23145, ‘payrate’:24.99}
>>> employee_record.get(‘name’, ‘not found’}
‘kevin’
>>> employee_record.get(‘dob’, ‘not found’)
‘not found’
Other Dictionary methods: items • Use the built in method called items
• When executed, it outputs all the key-value pairs in a dictionary view.
Syntax:
dictionary_name.items()
Example:
>>> employee_record = {‘name’:’kevin’,
‘Age’: 43, ‘ID’:23145, ‘payrate’:24.99}
>>> employee_record.items()
dict_items([(‘payrate’, 24.99), (‘name’,
‘kevin’), (‘ID’, 23145), (‘Age’, 43)])
Other Dictionary methods: keys
• Use the built in method called keys
• When executed, it outputs all the keys
Syntax:
dictionary_name.keys()
Example:
>>> employee_record = {‘name’:’kevin’,
‘Age’: 43, ‘ID’:23145, ‘payrate’:24.99}
>>> employee_record.keys()
ID
payrate
name
Age
Other Dictionary methods: values
• Use the built in method called values
• When executed, it outputs all the values in the dict
Syntax:
dictionary_name.values()
Example:
>>> employee_record = {‘name’:’kevin’,
‘Age’: 43, ‘ID’:23145, ‘payrate’:24.99}
>>> employee_record.values()
24.99
kevin
23145
43
Other Dictionary methods: pop and
popitem • Usethebuiltinmethodcalledpop
• When executed, it outputs the value associated with the specific key and removes it from the dict.
Syntax:
dictionary_name.pop(key, default)
Example:
>>> employee_record = {‘name’:’kevin’, ‘Age’: 43,
‘ID’:23145, ‘payrate’:24.99}
>>> employee_record.pop(‘name’)
‘kevin’
>>> employee_record
{‘payrate’: 24.99, ‘ID’: 23145, ‘Age’: 43}
>>>
Other Dictionary methods: pop and popitem
• Usethebuiltinmethodcalledpopitem
• Whenexecuted,itoutputsakey-valuepair,anditremovesthat key-value pair from the dict. (front of the list/dict – last in first out)
Syntax:
dictionary_name.popitem()
Example:
>>> employee_record
{‘payrate’: 24.99, ‘name’: ‘kevin’, ‘ID’: 23145, ‘Age’:
45}
>>> employee_record.popitem()
(‘payrate’, 24.99)
>>> employee_record.popitem()
(‘name’, ‘kevin’)
>>> employee_record.popitem()
(‘ID’, 23145)
>>>
Traversing: using list and dict methods
>>> employee_record = {‘name’:’kevin’,
‘Age’: 43, ‘ID’:23145, ‘payrate’:24.99}
>>> list(employee_record.keys())
[‘payrate’, ‘name’, ‘ID’, ‘Age’]
>>> list(employee_record.values())
[24.99, ‘kevin’, 23145, 43]
>>> >>> list(employee_record.items())
[(‘payrate’, 24.99), (‘name’, ‘kevin’),
(‘ID’, 23145), (‘Age’, 43)]
>>>
Fundamentals of Python: First Programs 37
Example: creating a dict from a list
from collections import defaultdict
employee_list = [(‘yosh’,23,2001),
(‘farah’, 22, 2010), (‘matt’, 34, 2000)]
#you can take a list of tuples and make it
#into a dict with key-value pairs
#start with an empty dict, start a for
loop #and append values to a key
d1 = defaultdict(list)
for key, age, start_date in employee_list:
d1[key].append(age)
d1[key].append(start_date)
print(d1, d1.items(), d1.values())