1. Datatypes in Python (Part II)
By Khodeza Begum

2. Outline
Dictionary
Nested Dictionary
Arrays
Matrix
List Comprehension

3. Dictionary Unordered collection of items
Optimized to retrieve value when key is known
{Key: value} pair
Type of keys
Must be unique
String, number or tuple (with immutable elements)
Type of values
Any data type and can repeat

4. Initialization and access
# empty dictionary
my_dict = {}
# dictionary with integer keys
my_dict = {1: 'John', 2: 'Martin'}
print (my_dict[1])
# dictionary with mixed keys (first->key type string, second->value type list )
my_dict = {'name': 'John', 1: [2, 4, 3]}
print (my_dict[1][0])
# using dict()
my_dict = dict(x=5, y=0)
print (my_dict['x’])
# from sequence having each item as a pair
my_dict = dict([(1,'apple'), (2,'ball')])
print (my_dict.get(1))
print (my_dict.get(3))
(Not a KeyError)
Output: 5
Output: John
Output: apple
Output: None
Output: 2

5. Change, Add, Delete & Remove
# Update
my_dict = {1: 'John', 2: 'Martin'}
my_dict[1] = 'Ashton'
for i in my_dict:
print (my_dict[i], end = " ")
# Add
my_dict[3] = 'Address'
for key,value in my_dict.items():
print (key,value)
print(my_dict.pop(3)) # or
del my_dict[3]
………..
my_dict.clear()
Output: 1 Ashton
2 Martin
3 Address
Output: Ashton Martin
Output: 1 Ashton
2 Martin

6. Dictionary comprehension and built-in functions
squares = {x: x*x for x in range(4)}
print(squares)
# Built-in functions
print(1 in squares)
print(9 in squares)
print(len(squares))
print(sorted(squares))
#Slicing
l = [0,3]
print (dict([(key, squares[key]) for key in l]))
Output:{0: 0, 1: 1, 2: 4, 3: 9}
Output:{0: 0, 3: 9}
Output: True
False
Output: 4
[0,1,2,3]

7. Other functions copy() fromkeys(seq[, v]) get(key[,d]) keys() values()
popitem()
pop(key[,d])
setdefault(key[,d])
update([other])
all()
any()
cmp()

8. Nested Dictionary An unordered collection of dictionary
Slicing Nested Dictionary is not possible.
We can shrink or grow nested dictionary as need.
Like Dictionary, it also has key and value.

9. Nested Dictionary example
nested_dict = { 'dictA': {'key_1': 'value_1’},
'dictB': {'key_2': 'value_2’}}
example
customer = {1: {'User_ID': ' ', 'age': '32', 'gender': 'Female', 'Estimated_salary': '150000', 'Purchased': '1'},
2: {'User_ID': ' ', 'age': '25', 'gender': 'Male', 'Estimated_salary': '33000', 'Purchased': '0’}}
print(customer[1]['Estimated_salary'])
print(customer[2]['User_ID'])
Output:

10. Nested Dictionary (continued)
#add
customer[3] = {'User_ID':' ','age':'470','gender’: 'Male','Estimated_salary':'25000','Purchased' :'1'}
#update
customer[3]['age'] = '47'
print(customer[3])
#del
del customer[3]
# iterate through each item for p_id, u_info in customer.items(): print("\nPerson ID:", p_id) for key in u_info: print(key + ':', u_info[key])
Output: Person ID: 1
User_ID:
age: 32
gender: Female
Estimated_salary:
Purchased: 1
…………………………………

11. Array Collection of elements of the same type
More popular in Java, C/C++, Javascript
Lists are better choice than arrays in Python
array module
Only advised to use array when needed to be interfaced with a C code

12. Array (continued)
import array as arr numbers = arr.array('i', [1, 2, 3]) numbers.append(4) print(numbers) numbers.extend([5, 6, 7])
# delete item for the given index
del numbers[2] #3rd index
print (numbers)
# delete item
numbers.remove(7)
#delete item for the given index
print(numbers.pop(3))
print(numbers)
Output: array('i', [1, 2, 4, 5, 6, 7])
Output: array('i', [1, 2, 3, 4])
Output: array('i', [1, 2, 4, 5, 6])
Output: array('i', [1, 2, 3, 4,5,6,7])
Output: 5
array('i', [1, 2, 4, 6])

13. Matrix 1 2 3 4 5 6 7 8 9  (Nested list) 4 5 6  3 6 9 
print(A[1])
column = [] # empty list
for row in A:
column.append(row[2])
print(column)

14. NumPy array 1 2 3 4 5 6 7 8 9  4 5 6  3 6 9  9  import numpy as np
B = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print(B[1])
print(B[:,-1])
print(B[-1][-1])

15. Matrix operations A = np.array([[2, 4], [5, -6]])
B = np.array([[9, -3], [3, 6]])
Addition  C = A + B
Multiplication  M = A.dot(B)
Transpose  T = np.transpose(A)
Slicing
S = np.array([[1, 4, 5, 12, 14], [-5, 8, 9, 0, 17], [-6, 7, 11, 19, 21]])
print( S[:2,:4] ) # 2 rows 4 columns
1 4 −

16. List Comprehension
An elegant way to define and create lists based on existing lists
Generally more compact and faster than normal functions and loops for creating list
However, we should avoid writing very long list comprehensions in one line to ensure that code is user-friendly.
Every list comprehension can be rewritten in for loop, but every for loop can’t be rewritten in the form of list comprehension.

17. List Comprehension Syntax : [expression for item in existing_list]
# iterating through using for loop
cubes = []
num_list = [2, 3, 5]
for num in numbers:
num=num*num*num
cubes.append(num)
print (cubes)
# iterating through using list comprehension
num_list = [2, 3, 5]
cubes_le = [num*num*num for num in num_list]
print (cubes_le)
# iterating through using list comprehension via lambda
cubes_lambda = list(map(lambda x:x*x*x, num_list))
print (cubes_lambda)
Output: [8, 27, 125]

18. List Comprehension Syntax : [expression for item in existing_list]
# iterating through using for loop
cubes = []
num_list = [2, 3, 5]
for num in numbers:
if num%2 != 0:
num=num*num*num
cubes.append(num)
print (cubes)
# iterating through using list comprehension
num_list = [2, 3, 5]
cubes_le = [num*num*num for num in num_list if num%2 != 0]
print (cubes_le)
# iterating through using list comprehension via lambda
num_new_list=[num for num in num_list if num %2 != 0]
cubes_lambda = list(map(lambda x:x*x*x,num_new_list))
print (cubes_lambda)
Output: [27, 125]

19. Quiz How can you change num = {'one': 1, 'two': 3} to
num[2] = ‘two’
num[1] = ‘two’
num[‘two’] = 2
num[‘two’] = ‘2’

20. Quiz What is the output of the following program?
cubes = {1: 1, 2: 8, 3: 27, 4: 64, 5: 125}
print(cubes.pop(4))
print(cubes)
a) 64
{1: 1, 2: 8, 3: 27, 5: 125}
b) {1: 1, 2: 8, 3: 27, 4:64, 5: 125}

21. Quiz What is the output of the following program?
dict = {'c': 97, 'a': 96, 'b': 98}
for _ in sorted(dict):
print (dict[_])
NameError

22. Quiz What is the output of the following program?
a = {'a':1,'b':2,'c':3}
print (a['a','b'])
Key Error
[1,2]
 {‘a’:1,’b’:2}
 (1,2)

23. Extra practice
transposed = [] matrix = [[1, 2, 3, 4], [4, 5, 6, 8]] for i in range(len(matrix[0])): transposed_row = [] for row in matrix: transposed_row.append(row[i]) transposed.append(transposed_row) print(transposed)

24. Thank you