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1 of 77Module 4 : Variables, Data types, and Operators
Introduction to       
Computational Thinking
Module 4 :                                     
Variables, Data types, and Operators
Asst Prof Chi‐Wing FU, Philip
Office: N4‐02c‐104
email: cwfu[at]ntu.edu.sg
2 of 77Module 4 : Variables, Data types, and Operators
Topics
• Variables
• Assignment Operator
• Data Types
• Data Conversion
• Operators
• Powerful Data Types and Random Module
• Case Study: Calculator Example
3 of 77Module 4 : Variables, Data types, and Operators
What is a Variable?
• In most computer programs, we need data
storage to represent and store “something”
(data) temporarily in programs
This is like M+ and
MR in calculator
4 of 77Module 4 : Variables, Data types, and Operators
What is a Variable?
• We can use names to make our program
more readable, so that the “something” is
easily understood, e.g., radiusFloat
Variable radiusFloat
5 of 77Module 4 : Variables, Data types, and Operators
Variable Objects
• For each variable, Python keeps a pair of info.:
• variable’s name
• variable’s value
• A variable is created when a value is assigned
to it for the first time. It associates a name with
a value.
• We say name references value
Name Value
X 7.1
X = 7.1
6 of 77Module 4 : Variables, Data types, and Operators
Variable Objects
• Operations: Once a variable is created, we
can store, retrieve, or modify the value
associated with the variable name
• Subsequent assignments can update the
associated value
Name Value
X 3.14
X = 3.14
Name Value
X 5.16
X = 5.16
7 of 77Module 4 : Variables, Data types, and Operators
Namespace
• A namespace is the table that contains (and
keeps track of) the association of names with
values
• We will see more about namespaces as we get
further into Python, but it is an essential part of
the language.
8 of 77Module 4 : Variables, Data types, and Operators
Namespace
9 of 77Module 4 : Variables, Data types, and Operators
Namespace
10 of 77Module 4 : Variables, Data types, and Operators
Python Naming Conventions
• How to name variables?
(as well as other things that you will see later in
this course, e.g., user-defined functions, etc.)
One basic practice!!!
Chooses the names of the variables carefully and
explains what each variable means
11 of 77Module 4 : Variables, Data types, and Operators
Python Naming Conventions
VS
Same program!!!
Though both programs work…
Different names for the variables
Readability counts!!!
What is c?
Not immediately clear
12 of 77Module 4 : Variables, Data types, and Operators
Python Naming Conventions
Syntax rules in Python:
• must begin with a letter or _
Ab123 and _b123 are OK, but 123ABC is not.
• may contain letters, digits, and underscores
this_is_an_identifier_123
• may be of any length
• upper and lower case letters are different
LengthOfRope is not lengthofrope
• names starting with _ have special meaning.
Be careful!!!
Python is
case sensitive!!
13 of 77Module 4 : Variables, Data types, and Operators
A Common Pitfall in Python
Can we interpret and run this program?
But what’s wrong?
English scores are all 60
Hint: a typo!
14 of 77Module 4 : Variables, Data types, and Operators
Topics
• Variables
• Assignment Operator
• Data Types
• Data Conversion
• Operators
• Powerful Data Types and Random Module
• Case Study: Calculator Example
15 of 77Module 4 : Variables, Data types, and Operators
Assignment Operator
• As mentioned in previous module
The = sign is the assignment operator but not
the equality in mathematics
• So, when we see
a = 5
a = a + 7
First, we create a variable called a and assign a
value of 5 to it. Second, we recall the value of a,
add 7 to it, and assign the expression result to a
16 of 77Module 4 : Variables, Data types, and Operators
Assignment Operator
• Basic syntax:
Left Hand Side (LHS) = Right Hand Side (RHS)
• RHS is an expression and LHS is a variable
• What “assignment” means is:
1) Evaluate the expression on RHS
2) Take the resulting value and associate
(assign) it with the name (variable) on the LHS
(in the namespace)
17 of 77Module 4 : Variables, Data types, and Operators
Examples
• Example: x = 2 + 3 * 5
evaluate expression (2+3*5): 17
update the value of x to reference 17
• Example (y has value 2): y = y + 3
evaluate expression (y+3): 5
update the value of y to reference 5
NOTE: If the variable name appears for the
first time, create the variable in namespace!
18 of 77Module 4 : Variables, Data types, and Operators
Examples
• Examples:
myInt = 5 Ok
myInt + 5 = 7 Invalid Syntax
myInt = print("hello") Invalid Syntax
print myInt = 5 Invalid Syntax
Why?
19 of 77Module 4 : Variables, Data types, and Operators
More Examples
Both aInt and bFloat got the same reference!!!
20 of 77Module 4 : Variables, Data types, and Operators
Exercise: What printed out?
21 of 77Module 4 : Variables, Data types, and Operators
Result… Reference is Tricky!!!
Result:
A new
reference
22 of 77Module 4 : Variables, Data types, and Operators
Chained assignment
• Let’s say we want more variables to
take the same value:
a = b = 1
a = b = c = 10
1. Don’t make it too long or clumsy…
Readability!!!
2. How about this? a = b = 5 = c = 10
23 of 77Module 4 : Variables, Data types, and Operators
Swapping two values
• Let’s say we want to swap values
a = 1
b = 2
• Can we do this?
a = b
b = a
Then??? Correct???
Computationally incorrect!!! Why?
24 of 77Module 4 : Variables, Data types, and Operators
Swapping two values
• One standard way in many programming
languages is to use a temporary variable
as a buffer:
tmp = a
a = b
b = tmp
We can then swap the reference (computationally)!
25 of 77Module 4 : Variables, Data types, and Operators
Multiple Assignment
• But Python has a special feature
a = 1
b = 2
a,b = b,a
• Use comma for multiple assignment
• Swapping can be done in one line!!!
• Note: it supports more than two elements
a,b,c = 10,11,12
• Make sure same number of
elements on LHS and RHS
• Python makes the tmp buffer for u
(implicitly, hidden from your sight)
26 of 77Module 4 : Variables, Data types, and Operators
CASE STUDY: Fibonacci sequence
• Problem: Generate the Fibonacci sequence
1,1,2,3,5,8,13,21,…
• Mechanism
1 + 1 -> 2 1,1,2
1 + 2 -> 3 1,1,2,3
2 + 3 -> 5 1,1,2,3,5
3 + 5 -> 8 1,1,2,3,5,8
……
27 of 77Module 4 : Variables, Data types, and Operators
• Python implementation:
• Use a and b to keep track of two consecutive
values in the sequence for each iteration
• and update them iteratively using
multiple assignment
Python is simple and
good for rapid prototyping
CASE STUDY: Fibonacci sequence
28 of 77Module 4 : Variables, Data types, and Operators
Topics
• Variables
• Assignment Operator
• Data Types
• Data Conversion
• Operators
• Powerful Data Types and Random Module
• Case Study: Calculator Example
29 of 77Module 4 : Variables, Data types, and Operators
Data types
• In Python, every “thing” is an object with
type and name(s) (in case referenced by
more than one variables), e.g.,
• integers: 5
• floats: 1.2
• booleans: True
• strings: “anything” or ‘something’
• lists: [,]: [‘a’,1,1.3]
• others we will see
In Python, both
single & double
quotes are for string
30 of 77Module 4 : Variables, Data types, and Operators
What is a Data Type?
• A type in Python essentially defines:
• the internal structure (the kind of data it
contains)
• the kinds of operations you can perform
• 'abc'.capitalize() is a method you
can call on strings, but not integers
• Some types have multiple elements
(collections), we’ll see those later
31 of 77Module 4 : Variables, Data types, and Operators
Basic Types in Python
• Numbers:
• Integers
1, -27
• Floating point numbers (Real)
3.14, 10., .001, 3.14e-10, 0e0
• Complex Numbers: 2 + 3j
• Booleans: True, False
• String and other types
32 of 77Module 4 : Variables, Data types, and Operators
Numbers: Integers
• Designated “int”
• Note: Python 3
• Unlimited precision!!!!!!!
1 + 1000 + 10000000000000000000000000
• Note: Python 2 (if you know…)
• There are two categories of integers: “long”
and “int”, but they are combined into one
type, basically “long,” in Python 3
33 of 77Module 4 : Variables, Data types, and Operators
Numbers: Floating Point
• Designated “float”
• Floating point numbers are real numbers
with decimal points:
3.14, 10., .001, 3.14e-10, 0e0
• Values stored in floating point are usually
approximated, e.g.,
Integers have
exact precision!!!
But not float…
34 of 77Module 4 : Variables, Data types, and Operators
Numbers: Complex Numbers
• Designated “complex”
• Python provides also complex numbers:
real part + imaginary part J
(J can be upper or lower case)
• Real and imaginary
parts input can be
in integer or floating
point numbers
• No space before J
No space here
35 of 77Module 4 : Variables, Data types, and Operators
Numbers: Complex Numbers
• Use z.real and z.imag to extract the
real and imaginary parts
Note: we use the
dot operator here to
get the parameters
(similar syntax like
math.pi for modules)
36 of 77Module 4 : Variables, Data types, and Operators
Boolean
• Designated “bool”
• For logical operations, see Module 6
• Either True or False (capitalize T and F!)
Python is case
sensitive!!!
37 of 77Module 4 : Variables, Data types, and Operators
String
• Designated “str”
• First collection type you learnt
• Collection type contains multiple objects
organized as a single object type
• String is basically a sequence, typically a
sequence of characters delimited by
single (‘…’) or double quotes (“…”)
38 of 77Module 4 : Variables, Data types, and Operators
Duck-typing
• Compared to C and Java, you may wonder
“How Python know the data types?”
• Python uses Duck-typing:
“When I see a bird that walks like a duck
and swims like a duck and quacks like a
duck, I call that bird a duck.”
Four variables!
Their types?
39 of 77Module 4 : Variables, Data types, and Operators
Keep Track of Data Types!!!
• Python does not have variable
declaration like Java or C to announce
or create a variable
• We create a variable by just assigning
a value to it and the type of the value
defines the type of the variable
• If we re-assign another value to the
variable, its type can change!!!
• So… KEEP TRACK!!!
40 of 77Module 4 : Variables, Data types, and Operators
Keep Track of Data Types!!!
• A variable in Python can have different
type at different time
41 of 77Module 4 : Variables, Data types, and Operators
The type function
• In Python, the type function allows you to
know the type of a variable or literal:
42 of 77Module 4 : Variables, Data types, and Operators
Textbook: Hungarian notation
• Variable naming: append the name of the
type to the variable name:
Note the name!
43 of 77Module 4 : Variables, Data types, and Operators
Topics
• Variables
• Assignment Operator
• Data Types
• Data Conversion
• Operators
• Powerful Data Types and Random Module
• Case Study: Calculator Example
44 of 77Module 4 : Variables, Data types, and Operators
Data Conversion
• Converting a value to other type by
returning a new value of that type
• Must be compatible and reasonable
e.g., cannot convert "abc" to integer
• There are conversion operations
associated with the type itself:
int(someVar) converts and returns an integer
float(someVar) converts and returns a float
str(someVar) converts and returns a string
45 of 77Module 4 : Variables, Data types, and Operators
What are the types?
Let’s keep track of them!
46 of 77Module 4 : Variables, Data types, and Operators
What happens if we
convert a float to an
integer?
Truncated!!!!!!!!
(remove anything after
the decimal point)
Want to round off?
… int(a+0.5)
47 of 77Module 4 : Variables, Data types, and Operators
Topics
• Variables
• Assignment Operator
• Data Types
• Data Conversion
• Operators
• Powerful Data Types and Random Module
• Case Study: Calculator Example
48 of 77Module 4 : Variables, Data types, and Operators
What are Operators?
• For each type, there is a set of operators
allowing us to perform computation on that type
• Some symbols are used for different purposes
for different types; we call this operator
overloaded (this is called overloading)
• E.g., “+” is addition for integers but
concatenation for strings (see module 8)
49 of 77Module 4 : Variables, Data types, and Operators
Types of Operators
Basic types of operators:
1. Assignment operator = (covered already)
2. Arithmetic operators
3. Relational operators (comparison)
4. Logical operators
5. is operator
Note: bitwise operators – see next module
50 of 77Module 4 : Variables, Data types, and Operators
#2: Arithmetic Operators
• Integer operators
• addition and subtraction: +, -
• multiplication: *
• division
• quotient: /
• remainder: %
• exponent (exp): **
• Floating point operators
• add, subtract, multiply, divide, exp: +, -, *, /, **
quotient
remainder
51 of 77Module 4 : Variables, Data types, and Operators
#2: Arithmetic Operators
* Note: do not mix up / and  (backslash)
52 of 77Module 4 : Variables, Data types, and Operators
Issue #1: Binary Operators
• Binary operators generally take two
values (operands) of the same type *
and return values of the same type
But… for division:
Integer division
produces float!!!
A new feature in
Python 3 but not in
Python 2, C/C++, etc.
Note: Unary operator – one value, e.g., -3 or +2.0
53 of 77Module 4 : Variables, Data types, and Operators
Issue #2: Division in Python
• Difference between Python versions:
• In Python 2.x:
Integer / integer → integer
Integer division
8 / 3 → 2
• In Python 3.x:
Integer / integer → float
8 / 3 → 2.6666666666666665
• Note: Division by Zero
• 1 / 0 -> run time error
A Trick in Python 3:
54 of 77Module 4 : Variables, Data types, and Operators
Issue #3: Mixed Operations
• We have seen 8/3 and 8.0/3.0
• How if 8 / 3.0? Different types: int and float
• This is called mixed operation
• In Python
• Python will automatically convert the
data to the most detailed result. Thus,
8 → 8.0, and the result is 2.6666666
• Detail: int < float
• So… actually no mixed operations.
Rather, data are implicitly converted.
55 of 77Module 4 : Variables, Data types, and Operators
Issue #4: Order of Calculation
• General mathematical rules apply:
Operators Description
() Parenthesis (grouping)
** Exponentiation
+x, -x Positive, Negative
*, /, % Multiplication, division, remainder
+, - Addition, Subtraction
• Note: always use parenthesis if in doubt… safe!!!
3 * (4 + 5) ** 2
Increaseinpriorty
56 of 77Module 4 : Variables, Data types, and Operators
Issue #5: Augmented Assignments
• These operations are shortcut
• Make the code easier to read
Shortcut Equivalence
myInt += 2 ↔ myInt = myInt + 2
myInt -= 2 ↔ myInt = myInt - 2
myInt /= 2 ↔ myInt = myInt / 2
myInt *= 2 ↔ myInt = myInt * 2
myInt %= 2 ↔ myInt = myInt % 2
57 of 77Module 4 : Variables, Data types, and Operators
• Compare two numbers (float or int) and
return a boolean: either True or False
greater than or equal tof >= 6.0>=
greater thanf > 5.0>
less than or equal tod <= 4<=
less thanc < 3<
not equal tob != 2!=
equal toa == 1==
meaningexampleoperator
#3: Relational Operators
58 of 77Module 4 : Variables, Data types, and Operators
Return True
if either one
is True
(num1 > num2) or (num2 >num3)or
Return True
only if both
are True
(num1 > num2) and (num2 >num3)and
Flip T/Fnot num < 0not
meaningexampleoperator
#4: Logical Operators
• Logical operators connect boolean values
and expressions and return a boolean value
as a result: not, and, or
59 of 77Module 4 : Variables, Data types, and Operators
Examples
• Examples:
have_holidays == True and saving >= 10000
temperature > 37.5 and hasMedicine == False
MathScore < 50 or EngScore < 50 or …
MathScore < 50 and EngScore < 50 and …
Num % 2 == 0 and Num % 3 == 0
-> Num % 6 == 0
What do they meaning?
60 of 77Module 4 : Variables, Data types, and Operators
Short circuit
Given p=True, q=True, r=False, s=False
• Short-circuit for and
If we evaluate:
( p and q and r and s )
• Short-circuit for or
If we evaluate:
( s or r or q or p )
We know the expression
is False when we reach r
We know the expression
is True when we reach q
Think about the logical meaning!!
http://docs.python.org/library/stdtypes.html#boolean-operations-and-or-not
61 of 77Module 4 : Variables, Data types, and Operators
• In Python (not in most languages), chained
comparisons work just like you would expect
in a mathematical expression:
• Say, myInt has a value 5
0 <= myInt and myInt <= 5
True
0 <= myInt <= 5
True
0 <= myInt <= 5 > 10
False
Chained Comparisons
Just apply each
operator to compare its
two neighboring values
Even for this
same meaning
(implicit “and”)
62 of 77Module 4 : Variables, Data types, and Operators
Exercise
Want to check your answers? Just try it in Python
63 of 77Module 4 : Variables, Data types, and Operators
Cast study:
Google Search uses Booleans
• All terms are and’ed together by default
• You can specify or (using OR)
• You can specify not (using -)
Example is:
‘Punch’ and (‘Bill’ or ‘William’) and not ‘gates’
64 of 77Module 4 : Variables, Data types, and Operators
#5: is operator
• Recall the namespace concept:
float1 = 2.5
float2 = 2.5
float3 = float2
• When we run “float3 = float2,”
both float3 and float2 get the same reference
65 of 77Module 4 : Variables, Data types, and Operators
#5: is operator
• It checks if two variables have the same
reference while == compares values only
Function id returns the
identity number of a variable
66 of 77Module 4 : Variables, Data types, and Operators
Topics
• Variables
• Assignment Operator
• Data Types
• Data Conversion
• Operators
• Powerful Data Types and Random Module
• Case Study: Calculator Example
67 of 77Module 4 : Variables, Data types, and Operators
Powerful Data types
• Some very powerful data types in Python
• List – sequence of values
• Dictionary – values with keys
• Set – a collection of unique elements
• Point – XYZ
• Line Segment – two points
(See textbook and Python website for detail;
note: they are very useful; not examinable
unless covered in 2nd part of this course)
68 of 77Module 4 : Variables, Data types, and Operators
A glimpse: List
• Python allows us to create a list of elements
• Like string, a list is also a sequence but uses [ ]
69 of 77Module 4 : Variables, Data types, and Operators
Module random
• Provides some powerful functions:
• randint( a , b ):
Return a random integer in [a,b] (inclusive)
• choice( x ):
Return a random element in sequence x;
x has to be non-empty
• shuffle( x ):
Shuffle the sequence x in place; x can be a
string and can be a set
You need to import random!!!
70 of 77Module 4 : Variables, Data types, and Operators
Different
elements picked
at different time
(same statement)
s1 is changed!
71 of 77Module 4 : Variables, Data types, and Operators
But hold on…
• Is random really random?
• Computation are deterministic. Computers
cannot generate true random numbers.
• So what?
Pseudo random!!!
* Pseudo random number generator
created by mathematical functions !!
(Example? See the end of next lecture module)
72 of 77Module 4 : Variables, Data types, and Operators
Topics
• Variables
• Assignment Operator
• Data Types
• Data Conversion
• Operators
• Powerful Data Types and Random Module
• Case Study: Calculator Example
73 of 77Module 4 : Variables, Data types, and Operators
Calculator Example
• Before the example, let’s learn an interesting
and powerful Python function: exec
• It takes a string as an input and execute it like a
Python statement in the command shell
Execute this string
74 of 77Module 4 : Variables, Data types, and Operators
Calculator Example
• Why powerful? Check this:
Repeat the indented block
User input
Execute it
Note: + is the concatentation
operator to connect strings
75 of 77Module 4 : Variables, Data types, and Operators
• We can read user inputs from command shell
and dynamically execute them like “code”!!!
• Not many programming languages can do this
Note: Python - interpreter!!!
Calculator Example
76 of 77Module 4 : Variables, Data types, and Operators
Take Home Messages
• Variables:
– Namespace and name reference concept
• Assignment Operator: Single, Chained, Multiple
• Data Types:
– Numbers (integers and float), Booleans, String
(collection types)
– Duck-typing, type function, data conversion
• Operators
– Division, mixed operators, order of operations and
parentheses, augmented assignments, relational and
logical operators
• Additional: list, random module, and exec
77 of 77Module 4 : Variables, Data types, and Operators
Reading Assignment
• Textbook
Chapter 1: Beginnings
1.4 to 1.7
(and also Chapter 0.8 about representing data)

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