Pythonlearn-09-Dictionaries.pptx

Python Dictionaries Chapter 9 Python for Everybody www.py4e.com What is a Collection? A collection is nice because we can put more than one value in it and carry them all around in one convenient package We have a bunch of values in a single “variable” We do this by hav...

Python Dictionaries Chapter 9 Python for Everybody www.py4e.com What is a Collection? A collection is nice because we can put more than one value in it and carry them all around in one convenient package We have a bunch of values in a single “variable” We do this by having more than one place “in” the variable We have ways of finding the different places in the variable  What is Not a “Collection”? Most of our variables have one value in them - when we put a new value in the variable - the old value is overwritten $ python >>> x = 2 >>> x = 4 >>> print(x) 4  A Story of Two Collections.. List - A linear collection of values that stay in order Dictionary - A “bag” of values, each with its own label Dictionaries tissue calculator perfume money candy http://en.wikipedia.org/wiki/Associative_array  Dictionaries Dictionaries are Python’s most powerful data collection Dictionaries allow us to do fast database-like operations in Python Dictionaries have different names in different languages - Associative Arrays - Perl / PHP - Properties or Map or HashMap - Java - Property Bag - C# /.Net  Dictionaries Lists index their entries >>> purse = dict() based on the position in the >>> purse['money'] = 12 >>> purse['candy'] = 3 list >>> purse['tissues'] = 75 >>> print(purse) Dictionaries are like bags - {'money': 12, 'tissues': 75, 'candy': 3} >>> print(purse['candy']) no order 3 >>> purse['candy'] = purse['candy'] + 2 So we index the things we >>> print(purse) {'money': 12, 'tissues': 75, 'candy': 5} put in the dictionary with a “lookup tag”  Comparing Lists and Dictionaries Dictionaries are like lists except that they use keys instead of numbers to look up values >>> lst = list() >>> ddd = dict() >>> lst.append(21) >>> ddd['age'] = 21 >>> lst.append(183) >>> ddd['course'] = 182 >>> print(lst) >>> print(ddd) [21, 183] {'course': 182, 'age': 21} >>> lst = 23 >>> ddd['age'] = 23 >>> print(lst) >>> print(ddd) [23, 183] {'course': 182, 'age': 23} >>> lst = list() List >>> lst.append(21) >>> lst.append(183) Key Value >>> print(lst) 21 [21, 183] lst >>> lst = 23 183 >>> print(lst) [23, 183] >>> ddd = dict() Dictionary >>> ddd['age'] = 21 >>> ddd['course'] = 182 Key Value >>> print(ddd) {'course': 182, 'age': 21} ['course'] 182 >>> ddd['age'] = 23 ddd >>> print(ddd) ['age'] 21 {'course': 182, 'age': 23}  Dictionary Literals (Constants) Dictionary literals use curly braces and have a list of key : value pairs You can make an empty dictionary using empty curly braces >>> jjj = { 'chuck' : 1 , 'fred' : 42, 'jan': 100} >>> print(jjj) {'jan': 100, 'chuck': 1, 'fred': 42} >>> ooo = { } >>> print(ooo) {} >>> Most Common Name?  Most Common Name? marquard cwen cwen zhen marquard zhen csev csev zhen marquard zhen csev zhen  Most Common Name? marquard cwen cwen zhen marquard zhen csev csev zhen marquard zhen csev zhen Many Counters with a Dictionary Key Value One common use of dictionaries is counting how often we “see” something >>> ccc = dict() >>> ccc['csev'] = 1 >>> ccc['cwen'] = 1 >>> print(ccc) {'csev': 1, 'cwen': 1} >>> ccc['cwen'] = ccc['cwen'] + 1 >>> print(ccc) {'csev': 1, 'cwen': 2}  Dictionary Tracebacks It is an error to reference a key which is not in the dictionary We can use the in operator to see if a key is in the dictionary >>> ccc = dict() >>> print(ccc['csev']) Traceback (most recent call last): File "", line 1, in KeyError: 'csev' >>> 'csev' in ccc False  When We See a New Name When we encounter a new name, we need to add a new entry in the dictionary and if this the second or later time we have seen the name, we simply add one to the count in the dictionary under that name counts = dict() names = ['csev', 'cwen', 'csev', 'zqian', 'cwen'] for name in names : if name not in counts: {'csev': 2, 'zqian': 1, 'cwen': 2} counts[name] = 1 else : counts[name] = counts[name] + 1 print(counts)  The get Method for Dictionaries The pattern of checking to see if a if name in counts: key is already in a dictionary and x = counts[name] assuming a default value if the key else : is not there is so common that there x = 0 is a method called get() that does this for us x = counts.get(name, 0) Default value if key does not exist (and no Traceback). {'csev': 2, 'zqian': 1, 'cwen': 2}  Simplified Counting with get() We can use get() and provide a default value of zero when the key is not yet in the dictionary - and then just add one counts = dict() names = ['csev', 'cwen', 'csev', 'zqian', 'cwen'] for name in names : counts[name] = counts.get(name, 0) + 1 print(counts) Default {'csev': 2, 'zqian': 1, 'cwen': 2}  Simplified Counting with get() counts = dict() names = ['csev', 'cwen', 'csev', 'zqian', 'cwen'] for name in names : counts[name] = counts.get(name, 0) + 1 print(counts) http://www.youtube.com/watch?v=EHJ9uYx5L58 Counting Words in Text  Writing programs (or programming) is a very creative and rewarding activity. You can write programs for many reasons ranging from making your living to solving a difficult data analysis problem to having fun to helping someone else solve a problem. This book assumes that everyone needs to know how to program and that once you know how to program, you will figure out what you want to do with your newfound skills. We are surrounded in our daily lives with computers ranging from laptops to cell phones. We can think of these computers as our “personal assistants” who can take care of many things on our behalf. The hardware in our current-day computers is essentially built to continuously ask us the question, “What would you like me to do next?” Our computers are fast and have vast amounts of memory and could be very helpful to us if we only knew the language to speak to explain to the computer what we would like it to do next. If we knew this language we could tell the computer to do tasks on our behalf that were repetitive. Interestingly, the kinds of things computers can do best are often the kinds of things that we humans find boring and mind-numbing.  Counting Pattern counts = dict() print('Enter a line of text:') The general pattern to count the line = input('') words in a line of text is to split words = line.split() the line into words, then loop through the words and use a print('Words:', words) dictionary to track the count of print('Counting...') each word independently. for word in words: counts[word] = counts.get(word,0) + 1 print('Counts', counts) python wordcount.py Enter a line of text: the clown ran after the car and the car ran into the tent and the tent fell down on the clown and the car Words: ['the', 'clown', 'ran', 'after', 'the', 'car', 'and', 'the', 'car', 'ran', 'into', 'the', 'tent', 'and', 'the', 'tent', 'fell', 'down', 'on', 'the', 'clown', 'and', 'the', 'car'] Counting… Counts {'and': 3, 'on': 1, 'ran': 2, 'car': 3, 'into': 1, 'after': 1, 'clown': 2, 'down': 1, 'fell': 1, 'the': 7, 'tent': 2} http://www.flickr.com/photos/71502646@N00/2526007974/  python wordcount.py counts = dict() Enter a line of text: line = input('Enter a line of text:') the clown ran after the car and the car ran words = line.split() into the tent and the tent fell down on the print('Words:', words) clown and the car print('Counting...’) Words: ['the', 'clown', 'ran', 'after', 'the', 'car', for word in words: 'and', 'the', 'car', 'ran', 'into', 'the', 'tent', 'and', counts[word] = counts.get(word,0) + 1 'the', 'tent', 'fell', 'down', 'on', 'the', 'clown', print('Counts', counts) 'and', 'the', 'car'] Counting... Counts {'and': 3, 'on': 1, 'ran': 2, 'car': 3, 'into': 1, 'after': 1, 'clown': 2, 'down': 1, 'fell': 1, 'the': 7, 'tent': 2} Definite Loops and Dictionaries Even though dictionaries are not stored in order, we can write a for loop that goes through all the entries in a dictionary - actually it goes through all of the keys in the dictionary and looks up the values >>> counts = { 'chuck' : 1 , 'fred' : 42, 'jan': 100} >>> for key in counts:... print(key, counts[key])... jan 100 chuck 1 fred 42 >>>  Retrieving Lists of Keys and Values >>> jjj = { 'chuck' : 1 , 'fred' : 42, 'jan': 100} You can get a list >>> print(list(jjj)) ['jan', 'chuck', 'fred'] of keys, values, or >>> print(list(jjj.keys())) items (both) from ['jan', 'chuck', 'fred'] a dictionary >>> print(list(jjj.values())) [100, 1, 42] >>> print(list(jjj.items())) [('jan', 100), ('chuck', 1), ('fred', 42)] >>> What is a “tuple”? - coming soon...  Bonus: Two Iteration Variables! We loop through the key-value pairs in a jjj = { 'chuck' : 1 , 'fred' : 42, 'jan': 100} for aaa,bbb in jjj.items() : dictionary using *two* print(aaa, bbb) iteration variables aaa bbb Each iteration, the first jan 100 [jan] 100 chuck 1 variable is the key and fred 42 [chuck] 1 the second variable is the corresponding [fred] 42 value for the key name = input('Enter file:') handle = open(name) python words.py counts = dict() Enter file: words.txt for line in handle: words = line.split() to 16 for word in words: counts[word] = counts.get(word,0) + 1 bigcount = None bigword = None python words.py for word,count in counts.items(): Enter file: clown.txt if bigcount is None or count > bigcount: the 7 bigword = word bigcount = count print(bigword, bigcount) Using two nested loops Summary  Acknowledgements / Contributions These slides are Copyright 2010- Charles R. Severance (... www.dr-chuck.com) of the University of Michigan School of Information and open.umich.edu and made available under a Creative Commons Attribution 4.0 License. Please maintain this last slide in all copies of the document to comply with the attribution requirements of the license. If you make a change, feel free to add your name and organization to the list of contributors on this page as you republish the materials. Initial Development: Charles Severance, University of Michigan School of Information … Insert new Contributors or translation credits here