Dictionaries: Keeping track of pairs

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Presentation transcript:

Dictionaries: Keeping track of pairs Introduction to Computing Using Python Dictionaries: Keeping track of pairs Class dict Class tuple

The dictionary: An associative data type Introduction to Computing Using Python The dictionary: An associative data type Many things in the world come in pairs, where Thing 1 is associated with Thing 2. For example A word and its definition A person and the person's birthday A living thing and its species The Python class dictionary models such relationships flexibly and efficiently >>> definitions = {'modest':'unassuming', 'eat':'chew and swallow'} >>> bdays = {'Napoleon':'15 Aug 1769', 'Lady Gaga':'Mar 28 1986'} >>> species = {'Fido':'dog', 'Finny':'catfish', 'Pepe Le Pew':'skunk'}

Dictionary: Syntax and types Introduction to Computing Using Python Dictionary: Syntax and types This is the syntax of a dictionary: A dictionary is enclosed in curly brackets. The empty dictionary is denoted {}. A dictionary is a set of key:value pairs. Each key and its value are separated by a colon (':'). Key:value pairs are separated by commas. Permitted types of keys and values: A key can be any immutable type – for example, a string, a number or a tuple. A key cannot be a mutable type, such as a list. A dictionary may contain keys of different types, but Each key in a dictionary must be unique A value can be any type we have learned – a string, a number, a list – even another dictionary.

Dictionary: Basic operations Introduction to Computing Using Python Dictionary: Basic operations >>> # create an empty dictionary >>> d = {} >>> # add a key:value pair, using index and assignment operators >>> d['NJIT'] = 'tech' >>> # look up the value of a key using the index ([]) operator >>> d['NJIT'] 'tech' >>> # change a value by assigning a new value >>> d['NJIT'] = 'tech school' >>> d['NJIT'] 'tech school' >>> # remove a key:value pair and return its value >>> njitSchoolType = d.pop('NJIT') >>> njitSchoolType 'tech school' >>> d {}

Dictionary: More things you can do Introduction to Computing Using Python Dictionary: More things you can do >>> # find the size (number of key:value pairs) of a dictionary >>> d = {1:'for the money', 'two':'for the show'} >>> len(d) 2 >>> # test for the membership (presence) of a key >>> 1 in d True >>> 2 in d False >>> # incorporate dictionary d2 into dictionary d >>> d2 = {'Twain':'Mark'} >>> d.update(d2) >>> d {1: 'for the money', 'Twain': 'Mark', 'two': 'for the show'} >>> # note that dictionary d2 is not changed >>> d2 {'Twain':'Mark'}

Dictionary properties: Order and speed Introduction to Computing Using Python Dictionary properties: Order and speed The order that a dictionary stores keys is not guaranteed >>> d = {1:'for the money', 'two':'for the show'} >>> d2 = {'Twain':'Mark'} >>> d.update(d2) >>> d {1: 'for the money', 'Twain': 'Mark', 'two': 'for the show'} >>> # Note that the key:value pair 'Twain':'Mark' from d2 has been >>> # inserted between the pairs already in d Dictionary lookup (amazingly!) does not get slower as the dictionary gets bigger >>> # Inserting ten million elements may take a few seconds >>> d = {} >>> for i in range(10000000): d[i] = str(i) >>> # Retrieving one element from among 10,000,000 is immediate >>> d[5000000] '5000000'

Iterating over a dictionary Introduction to Computing Using Python Iterating over a dictionary Iterate over dictionary keys like this >>> # Use the dictionary method d.keys() >>> d = {'tree':'oak', 'fish':'guppy', 'dog':'boxer', 'cat':'tabby'} >>> for thing in d.keys(): if 't' in thing: print(thing, end=' ') cat tree >>> # Note: for thing in d: is the same as for thing in d.keys() Iterate over dictionary values like this >>> # Use the dictionary method d.values() >>> for value in d.values(): if 'y' in value: print(value, end=' ') guppy tabby

The tuple as a dictionary key Introduction to Computing Using Python The tuple as a dictionary key A tuple is almost the same as a list, except that it is immutable. A tuple is delimited by parentheses where a list has square brackets >>> # This is a list of int's >>> intList = [1, 2, 3] >>> # Attempting to use a list as a key will result in an error >>> d = {intList: "some int's"} Traceback (most recent call last): File "<pyshell#193>", line 1, in <module> d = {intList:"some int's"} TypeError: unhashable type: 'list' >>> # Solution: Use a tuple as a key instead >>> intTuple = (1, 2, 3) # or intTuple = tuple(intList) >>> d = {intTuple: "some int's"} >>> d {(1, 2, 3): "some int's"}

Example: Keeping count(s) Introduction to Computing Using Python Problem: you want to count how many times each item in a list occurs, but you don't know the items in advance. For example, for this list >>> grades = [95, 96, 100, 85, 95, 90, 95, 100, 100] a good solution might look like this 100 3 96 1 95 90 85 Complications: until you see the list, you don't know what counters to create you'd like to be able to access the count of an item via the item itself Solution: create a dictionary in which each distinct item is a key and its count is the associated value

A dictionary as a collection of counters Introduction to Computing Using Python def frequency(itemList): '''Compute the frequency of each item in itemList. Return the result as a dictionary in which each distinct item in itemList is a key and the item's frequency (count) is the associated value.''' counters = {} for item in itemList: # if the item hasn't been seen before if item not in counters: # add the item to the dictionary # and set its count to 1 counters[item] = 1 # otherwise, increment the count of item else: counters[item] += 1 return counters