DictionariesPython Programming.One of the datatypes of Python which explains the dictionary methods and examples.pptx

Python Programming.One of the datatypes of Python which explains the dictionary methods and examples

1. Chapter 9 Dictionaries

2. Dictionaries A dictionary is like a list , but more general. In a list , the index positions have to be integers ; in a dictionary , the indices can be (almost) any type. You can think of a dictionary as a mapping between a set of indices ( which are called keys) and a set of values . Each key maps to a value. The association of a key and a value is called a key-value pair or sometimes an item. As an example, we’ll build a dictionary that maps from English to Spanish words , so the keys and the values are all strings. The function dict creates a new dictionary with no items. Because dict is the name of a built-in function, you should avoid using it as a variable name.

3. >>> eng2sp = dict () >>> print(eng2sp) {} The curly brackets, {}, represent an empty dictionary. To add items to the dictionary, you can use square brackets: >>> eng2sp['one'] = ' uno ' This line creates an item that maps from the key ’one’ to the value “ uno ”. If we print the dictionary again, we see a key-value pair with a colon between the key and value : >>> print(eng2sp) {'one': ' uno '}

4. The above output format is also an input format . For example, you can create a new dictionary with three items . >>> eng2sp = {'one': ' uno ', 'two': 'dos', 'three': ' tres '} But if you print eng2sp, you might be surprised : >>> print(eng2sp) {'one': ' uno ', 'three': ' tres ', 'two': 'dos '} The order of the key-value pairs is not the same . In fact, if you type the same example on your computer, you might get a different result . In general, the order of items in a dictionary is unpredictable.

5. You use the keys to look up the corresponding values: >>> print(eng2sp['two']) 'dos’ The key ’two’ always maps to the value “dos” so the order of the items doesn’t matter . If the key isn’t in the dictionary, you get an exception: >>> print(eng2sp['four']) KeyError : 'four'

6. The len function works on dictionaries; it returns the number of key-value pairs: >>> len (eng2sp) 3 The in operator works on dictionaries; by default it tells you whether something appears as a key in the dictionary (appearing as a value is not by default). >>> 'one' in eng2sp True >>> ' uno ' in eng2sp False

7. To see whether something appears as a value in a dictionary, you can use the method values, which returns the values as a list, and then use the in operator: >>> vals = list(eng2sp.values()) >>> ' uno ' in vals True

8. In operator The in operator uses different algorithms for lists and dictionaries. For lists, it uses a linear search algorithm . As the list gets longer, the search time gets longer in direct proportion to the length of the list. For dictionaries, Python uses an algorithm called a hash table that has a remarkable property : the in operator takes about the same amount of time no matter how many items there are in a dictionary .

9. sorted () function sorted( iterable , key, reverse) sorted() takes two three parameters: iterable  - sequence ( string ,  tuple ,  list ) or collection ( set ,  dictionary ,  frozen set ) or any iterator   reverse (Optional)  - If true, the sorted list is reversed (or sorted in ASC order) key (Optional)  - function that serves as a key for the sort comparison. pyList = ['e', 'a', 'u', 'o', ' i '] print(sorted( pyList )) ['a', 'e', ' i ', 'o', 'u'] print(sorted( pyList,reverse =True)) ['u', 'o', ' i ', 'e', 'a']

10. dictionary pyDict = {'e': 1, 'a': 2, 'u': 3, 'o': 4, ' i ': 5} print(sorted( pyDict , reverse=True))

11. Custom Sorting using the key parameter sorted() function has an optional parameter called ‘key’ which takes a function as its value. This key function transforms each element before sorting, it takes the value and returns 1 value which is then used within sort instead of the original value.

12. Example For example, if we pass a list of strings in sorted(), it gets sorted alphabetically . But if we specify key = len , i.e. give len function as key, then the strings would be passed to len , and the value it returns, i.e. the length of strings will be sorted. Which means that the strings would be sorted based on their lengths instead

13. L = [" cccc ", "b", " dd ", " aaa "] Print(“Normal sort :", sorted(L)) print ("Sort with len :", sorted(L, key = len )) Output : Normal sort : [' aaa ', 'b', ' cccc ', ' dd '] Sort with len : ['b', ' dd ', ' aaa ', ' cccc ']

14. Key also takes user-defined functions as its value for the basis of sorting. # Sort a list of integers based on # their remainder on dividing from 7   def func (x):     return x % 7   L = [15, 3, 11, 7] print "Normal sort :", sorted(L) print "Sorted with key:", sorted(L, key = func ) Output : Normal sort : [3, 7, 11, 15] Sorted with key: [7, 15, 3, 11]

15. Example: Sorting based on more than one value. a = [] def fun(v): return (v[1],v[2]) # create the table (name, age, job) a.append (["Nick", 30, "Doctor"]) a.append (["John", 8, "Student"]) a.append (["Paul", 8,"Car Dealer"]) a.append (["Mark", 66, "Retired"]) a.sort (key=fun) print(a) Output: [['Paul', 8, 'Car Dealer'], ['John', 8, 'Student'], ['Nick', 30, 'Doctor'], ['Mark', 66, 'Retired']]

16. Sort() vs sorted() sorted()  returns a new sorted list , leaving the original list unaffected.  sort() sorts the list  in-place , mutating the list indices, and returns None  (like all in-place operations). Sort() works only with the lists. sorted() works on any iterable , not just lists. Works on Strings, tuples , dictionaries etc and returns a list containing all elements, sorted. Use  list.sort () when you want to mutate the list , sorted() when you want a new sorted object back and iterable is not list. For lists,  list.sort ()  is faster than sorted()  because it doesn't have to create a copy. For any other iterable , you have no choice. You cannot retrieve the original positions . Once you called  list.sort () the original order is gone. You can retrieve the original positions after the call to sorted() using the original object.

17. Operator module Operator is a built-in module providing a set of convenient operators . The function operator.itemgetter (n) constructs a callable that assumes an iterable object (e.g. list, tuple , set) as input, and fetches the n- th element out of it.

18. Example: a = [] # create the table (name, age, job) a.append (["Nick", 30, "Doctor"]) a.append (["John", 8, "Student"]) a.append (["Paul", 22, "Car Dealer"]) a.append (["Mark", 66, "Retired"]) # sort the table by age import operator a.sort (key= operator.itemgetter (1)) # print the table print(a) Output: [['John', 8, 'Student'], ['Paul', 22, 'Car Dealer'], ['Nick', 30, 'Doctor'], ['Mark', 66, 'Retired']]

19. Example 1.py Write a Python program to sort (ascending and descending) a dictionary by value .

20. 1.py import operator d = {'1': 2, '3': 4, '4': 3, '2': 1, '0': 0} print('Original dictionary : ',d) sorted_d = sorted( d.items (), key= operator.itemgetter (1)) print('Dictionary in ascending order by value : ', sorted_d ) sorted_d = sorted( d.items (), key= operator.itemgetter (1),reverse=True) print('Dictionary in descending order by value : ', sorted_d )

21. Dictionary Methods Update() Keys() Values() Items() Has_key () Clear() Copy()

22. Update() The update() method updates the dictionary with the elements from the another dictionary object or from an iterable of key/value pairs. The update() method adds element(s) to the dictionary if the key is not in the dictionary. If the key is in the dictionary, it updates the key with the new value. The syntax of update() is: dict.update ([other])

23. update() Parameters The update() method takes either a  dictionary  or an iterable object of key/value pairs (generally  tuples ). If update() is called without passing parameters, the dictionary remains unchanged.

24. Return Value from update()  The update() method updates the dictionary with elements from a dictionary object or an iterable object of key/value pairs. It doesn't return any value (returns None).

25. Example-1 d = {1: "one", 3: "three"} d1 = {2: "two"} # updates the value of key 2 d.update (d1) print(d) d1 = {3: "three"} # adds element with key 3 d.update (d1) print(d) OutPut : {1: 'one', 2: 'two'} {1: 'one', 2: 'two', 3: 'three'}

26. Example-2 d = {'x': 2} d.update (y = 3, z = 0) print(d) Output: {'x': 2, 'y': 3, 'z': 0}

27. Keys() keys method takes a dictionary and returns a list of the keys that appear, but instead of the function syntax keys(eng2sp), we use the method syntax eng2sp.keys(). keys() Parameters The keys() doesn't take any parameters. >>> eng2sp.keys() ['one', 'three', 'two'] A method call is called an invocation; in this case, we say that we are invoking methods keys on the object eng2sp.

28. Keys(): Example-1 person = {'name': ' Phill ', 'age': 22, 'salary': 3500.0} print( person.keys ()) empty_dict = {} print( empty_dict.keys ()) Output: dict_keys (['name', 'age', 'salary']) dict_keys ([])

29. Keys(): Example-2 How keys() works when dictionary is updated? person = {'name': ' Phill ', 'age': 22, } print('Before dictionary is updated') keys = person.keys () print(keys) # adding an element to the dictionary person.update ({'salary': 3500.0}) print('\ nAfter dictionary is updated') print(keys) Output: Before dictionary is updated dict_keys (['name', 'age']) After dictionary is updated dict_keys (['name', 'age', 'salary'])

30. Values() The values method is similar; it returns a list of the values in the dictionary: >>> eng2sp.values() [' uno ', ' tres ', 'dos'] values() Parameters The values() method doesn't take any parameters. Return value from values() The values() method returns a view object that displays a list of all values in a given dictionary.

31. Example 1: Get all values from the dictionary # random sales dictionary sales = { 'apple': 2, 'orange': 3, 'grapes': 4 } print( sales.values ()) Output: dict_values ([2, 3, 4])

32. Example 2: How values() works when dictionary is modified? # random sales dictionary sales = { 'apple': 2, 'orange': 3, 'grapes': 4 } values = sales.values () print('Original items:', values) # delete an item from dictionary del[sales['apple']] print('Updated items:', values) Output: Original items: dict_values ([2, 3, 4]) Updated items: dict_values ([3, 4])

33. Items() The items() method returns a view object that displays a list of dictionary's (key, value) tuple pairs. The items() method is similar to dictionary's  viewitems () method in Python 2.7 items() Parameters The items() method doesn't take any parameters. Return value from items() The items() method returns a view object that displays a list of a given dictionary's (key, value) tuple pair. >>> eng2sp.items() [(' one','uno '), ('three', ' tres '), ('two', 'dos')]

34. Example 1: Get all items of a dictionary with items() # random sales dictionary sales = { 'apple': 2, 'orange': 3, 'grapes': 4 } print( sales.items ()) Output: dict_items ([('apple', 2), ('orange', 3), ('grapes', 4)])

35. Example 2: How items() works when a dictionary is modified? # random sales dictionary sales = { 'apple': 2, 'orange': 3, 'grapes': 4 } items = sales.items () print('Original items:', items) # delete an item from dictionary del[sales['apple']] print('Updated items:', items) Output: Original items: dict_items ([('apple', 2), ('orange', 3), ('grapes', 4)]) Updated items: dict_items ([('orange', 3), ('grapes', 4)])

36. has_key () The method  has_key ()  returns true if a given  key  is available in the dictionary, otherwise it returns a false. Syntax Following is the syntax for  has_key ()  method − dict.has_key (key) Parameters key  − This is the Key to be searched in the dictionary. Return Value This method return true if a given key is available in the dictionary, otherwise it returns a false. NOTE: has_key is removed in python 3.x and was present in python versions earlier than 2.3

37. has_key (): Example dict = {'Name': 'Zara', 'Age': 7} print("Value : ", dict.has_key ('Age')) print("Value : ", dict.has_key (‘Gender'))

38. Clear() The clear() method removes all items from the dictionary. The syntax of clear() is: dict.clear () clear() Parameters The clear() method doesn't take any parameters. Return Value from clear() The clear() method doesn't return any value (returns None).

39. Example 1: How clear() method works for dictionaries? d = {1: "one", 2: "two"} d.clear () print('d =', d) Output: d = {}

40. Example 2: Another way for clearing the items of the dictionary You can also remove all elements from the dictionary by assigning empty dictionary {}. However, there is a difference between calling clear() and assigning {} if there is another variable referencing the dictionary.

41. d = {1: "one", 2: "two"} d1 = d d.clear () print('Removing items using clear()') print('d =', d) print('d1 =', d1) d = {1: "one", 2: "two"} d1 = d d = {} print('Removing items by assigning {}') print('d =', d) print('d1 =', d1) Output: Removing items using clear() d = {} d1 = {} Removing items by assigning {} d = {} d1 = {1: 'one', 2: 'two'} Example 2: Another way for clearing the items of the dictionary

42. Copy() The copy() method returns a shallow copy of the dictionary. The syntax of copy() is: dict.copy () copy() Parameters The copy() method doesn't take any parameters. Return Value from copy() This method returns a shallow copy of the dictionary. It doesn't modify the original dictionary.

43. Example 1: How copy works for dictionaries? original = {1:'one', 2:'two'} new = original.copy () print(' Orignal : ', original) print('New: ', new) Output: Original: {1: 'one', 2: 'two'} New: {1: 'one', 2: 'two'}

44. Difference in Using copy() method, and = Operator to Copy Dictionaries When copy() method is used, a new dictionary is created which is filled with a copy of the references from the original dictionary. When = operator is used, a new reference to the original dictionary is created.

45. Example 2: Using = Operator to Copy Dictionaries original = {1:'one', 2:'two'} new = original # removing all elements from the list new.clear () print('new: ', new) print('original: ', original) Output: new: {} original: {} Note: Here, when the new dictionary is cleared, the original dictionary is also cleared.

46. Example 3: Using copy() to Copy Dictionaries original = {1:'one', 2:'two'} new = original.copy () # removing all elements from the list new.clear () print('new: ', new) print('original: ', original) Output: new: {} original: {1: 'one', 2: 'two'}

47. Copy() and deepcopy () in copy module copy()  shallow copy deepcopy () deep copy

48. Copy an Object in Python In Python, we use = operator to create a copy of an object. You may think that this creates a new object; it doesn't. It only creates a new variable that shares the reference of the original object. Let's take an example where we create a list named  old_list  and pass an object reference to  new_list  using = operator.

49. Example 1: Copy using = operator old_list = [[1, 2, 3], [4, 5, 6], [7, 8, 'a']] new_list = old_list new_list [2][2] = 9 print('Old List:', old_list ) print('ID of Old List:', id( old_list )) print('New List:', new_list ) print('ID of New List:', id( new_list )) Output: Old List: [[1, 2, 3], [4, 5, 6], [7, 8, 9]] ID of Old List: 983119760520 New List: [[1, 2, 3], [4, 5, 6], [7, 8, 9]] ID of New List: 983119760520

50. Copy Module Essentially, sometimes you may want to have the original values unchanged and only modify the new values or vice versa. In Python, there are two ways to create copies: Shallow Copy Deep Copy To make these copy work, we use the copy module.

51. Shallow Copy A shallow copy creates a new object which stores the reference of the original elements. So, a shallow copy doesn't create a copy of nested objects, instead it just copies the reference of nested objects. This means, a copy process does not recurse or create copies of nested objects itself.

52. Example 2: Create a copy using shallow copy import copy old_list = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] new_list = copy.copy ( old_list ) print("Old list:", old_list ) print("New list:", new_list ) Output: Old list: [[1, 2, 3], [4, 5, 6], [7, 8, 9]] New list: [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

53. Example 3: Adding [4, 4, 4] to old_list , using shallow copy import copy old_list = [[1, 1, 1], [2, 2, 2], [3, 3, 3]] new_list = copy.copy ( old_list ) old_list.append ([4, 4, 4]) print("Old list:", old_list ) print("New list:", new_list ) Output: Old list: [[1, 1, 1], [2, 2, 2], [3, 3, 3], [4, 4, 4]] New list: [[1, 1, 1], [2, 2, 2], [3, 3, 3]]

54. Example 4: Adding new nested object using Shallow copy import copy old_list = [[1, 1, 1], [2, 2, 2], [3, 3, 3]] new_list = copy.copy ( old_list ) old_list [1][1] = 'AA' print("Old list:", old_list ) print("New list:", new_list ) Output: Old list: [[1, 1, 1], [2, 'AA', 2], [3, 3, 3]] New list: [[1, 1, 1], [2, 'AA', 2], [3, 3, 3]]

55. Deep Copy A deep copy creates a new object and recursively adds the copies of nested objects present in the orig The deep copy creates independent copy of original object and all its nested objects.

56. Example 5: Copying a list using deepcopy () import copy old_list = [[1, 1, 1], [2, 2, 2], [3, 3, 3]] new_list = copy.deepcopy ( old_list ) print("Old list:", old_list ) print("New list:", new_list ) Output: Old list: [[1, 1, 1], [2, 2, 2], [3, 3, 3]] New list: [[1, 1, 1], [2, 2, 2], [3, 3, 3]]

57. Example 6: Adding a new nested object in the list using Deep copy import copy old_list = [[1, 1, 1], [2, 2, 2], [3, 3, 3]] new_list = copy.deepcopy ( old_list ) old_list [1][0] = 'BB' print("Old list:", old_list ) print("New list:", new_list ) Output: Old list: [[1, 1, 1], ['BB', 2, 2], [3, 3, 3]] New list: [[1, 1, 1], [2, 2, 2], [3, 3, 3]]

58. Example 2.py Write a Python program to add a new (key, value) pair to an existing dictionary . Sample Dictionary : {0: 10, 1: 20} Expected Result : {0: 10, 1: 20, 2: 30}

59. 2.py d = {0:10, 1:20} print(d) d.update ({2:30}) print(d)

60. Example 3.py  Write a Python script to concatenate following dictionaries to create a new one.  Sample Dictionary :  dic1={1:10, 2:20}  dic2={3:30, 4:40}  dic3={5:50,6:60} Expected Result : {1: 10, 2: 20, 3: 30, 4: 40, 5: 50, 6: 60}

61. 3.py dic1={1:10, 2:20} dic2={3:30, 4:40} dic3={5:50,6:60} dic4 = {} for d in (dic1, dic2, dic3): dic4.update(d) print(dic4)

62. Example 4.py Write a Python program to check if a given key already exists in a dictionary.

63. 4.py d = {1: 10, 2: 20, 3: 30, 4: 40, 5: 50, 6: 60} def is_key_present (x): if x in d: print('Key %s is present in the dictionary' % x) else: print('Key %s is not present in the dictionary' % x) is_key_present (5) is_key_present (9)

64. Example 5.y Write a Python program to remove a key from a dictionary.

65. 5.py myDict = {'a':1,'b':2,'c':3,'d':4} print( myDict ) if 'a' in myDict : del myDict ['a'] print( myDict )

66. Example 6.py Write a python program to register participants to events. The program should use functions addparticipants () and viewparticipants () functions defined and included as module in main program. If a participant has already registered the program should say already registered.

67. 6-m.py import events while 1: print("1. Add Participant:") print("2. See Participants:") choice= int (input("Enter your Choice:")) if choice==1: events.participants () elif choice==2: events.view () else: quit()

68. events.py import csv from tabulate import tabulate dict ={} def participants(): print("Enter Participant Details:") name=input("Enter Name of the Participant") eventname =input("Enter Event name:") with open(" data.csv","a ", newline="") as myfile : wr = csv.writer ( myfile,dialect ="excel") if name not in dict.keys (): dict [name]={' event':eventname } print( dict ) wr.writerow ([ name,eventname ]) else: print("Already Registered") def view(): print("Participant Details") with open(" data.csv","r ") as myfile : # # wr = csv.writer ( myfile,dialect ="excel") # wr.writerow ([ name,gender,email ]) reader= csv.reader ( myfile ) for row in reader: # print(row[0], row[1]) print(tabulate( reader,tablefmt ="simple"))

69. Dictionary as a set of counters word = 'brontosaurus' d= dict () for c in word: if c not in d: d[c] = 1 else: d[c] = d[c] + 1 print(d) Here’s the output of the program: {'a': 1, 'b': 1, 'o': 2, 'n': 1, 's': 2, 'r': 2, 'u': 2, 't': 1}

70. Get() method Get that takes a key and a default value. If the key appears in the dictionary, get returns the corresponding value; otherwise it returns the default value. For example: >>> counts = { 'chuck' : 1 , ' annie ' : 42, ' jan ': 100} >>> print( counts.get (' jan ', 0)) 100 >>> print( counts.get (' tim ', 0))

71. word = 'brontosaurus' d = dict () for c in word: d[c ] = d.get (c,0) + 1 print(d)

72. Example 7.py fname = input('Enter the file name: ') try: fhand = open( fname ) except: print('File cannot be opened:', fname ) exit() counts = dict () for line in fhand : words = line.split () for word in words: if word not in counts: counts[word] = 1 else: counts[word] += 1 print(counts)

73. Looping and dictionaries For loop traverses the keys of the dictionary. This loop prints each key and the corresponding value: counts = { 'chuck' : 1 , ' annie ' : 42, ' jan ': 100} for key in counts: print(key , counts[key ]) Here’s what the output looks like: jan 100 chuck 1 annie 42

74. Advanced text parsing romeo.txt But, soft! what light through yonder window breaks? It is the east, and Juliet is the sun. Arise , fair sun, and kill the envious moon, Who is already sick and pale with grief , Since the Python split function looks for spaces and treats words as tokens separated by spaces, we would treat the words “soft!” and “soft” as different words and create a separate dictionary entry for each word . Also since the file has capitalization, we would treat “who” and “Who” as different words with different counts.

75. Solution We can solve both these problems by using the string methods lower, punctuation, and translate . The translate is more important method. Here is the documentation for translate: line.translate ( str.maketrans ( fromstr , tostr , deletestr )) Replace the characters in fromstr with the character in the same position in tostr and delete all characters that are in deletestr . The fromstr and tostr can be empty strings and the deletestr parameter can be omitted.

76. Example # first string firstString = " abc " secondString = " ghi " thirdString = " ab " string = " abcdef " print("Original string:", string) translation = string.maketrans ( firstString , secondString , thirdString ) # translate string print("Translated string:", string.translate (translation)) Output Original string: abcdef Translated string: idef

77. Python tell us the list of characters that it considers as “punctuation”: >>> import string >>> string.punctuation '!"#$%&\'()*+,-./:;<=>?@[\\]^_`{|}~'

78. Updated Program import string fname = input('Enter the file name: ') try: fhand = open( fname ) except: print('File cannot be opened:', fname ) exit() counts = dict () for line in fhand : line = line.rstrip () line = line.translate ( line.maketrans ('', '', string.punctuation )) line = line.lower () words = line.split () for word in words: if word not in counts: counts[word] = 1 else: counts[word] += 1 print(counts)