Python Comparison Operators

Comparison Operators

• Comparison operators allow the comparison of variables
• The operator outputs a Boolean value (True or False)

Comparison Operators Examples

• 2 == 2 returns a True Boolean because the values are equal
• 1 == 0 returns a False Boolean because the values are not equal
• 2 < 4 returns a True Boolean
• 2 < 1 returns a False Boolean
• 2 >= 2 and 2 >= 1 returns a True Boolean since 2 is greater than or equal to 2, and greater than or equal to 1
• 2 <= 2 and 2 <= 4 returns a True Boolean since 2 is less than or equal to 2, and less than or equal to 4
• == is a comparison operator, while = is an assignment operator

Chained Comparison Operators

• Python allows the chaining of multiple comparisons to perform complex tests
• Chained comparisons are shorthand for larger Boolean expressions
• and statement examples: 1<2 and 2<3 returns a True Boolean because both conditions are true. 1<3 and 3>2 returns a True Boolean because the constraints are both still met
• or statement example: 1==2 or 2<3 returns a True Boolean because one condition is true
• With the or operator, only one of the conditions needs to be true for the total check to be true

Python Statement Introduction

• Overview of Python statements is helpful to emphasize the differences between Python, C++, and other languages
• Gaining an understanding of Python is made quick and simple for those migrating from different languages
• Learning about Python enables understanding and reading code in other languages more easily

Python vs Other Languages

• Compared to other languages, Python is less cluttered and more readable
• Python does away with () and {} by using a colon and whitespace/indentation practices
• The statement ends with a colon, and whitespace (indentation) describes what takes place in the statement
• Python does not use semicolons. Instead, the end of a line is the same as the end of a statement

Indentation

• Code readability is a core part of the design of Python
• Whitespace and indentation in Python serves the same function as parenthesis in other languages, defining the scope and execution block of statements

Print Multiple Variables

• To print multiple variable with an inline string use the following syntax:

band = 8
name = "Sarah Fier"
print("The band for ", name, "is", band, "out of 10")

• Use (+) before parameters

Statement: Nested If

• Nested if statements allow conditional checks within conditional checks
• Example:

if x>y:
  if y>10:
    print(x)
    print(y)
print(x+5) # always executed

If Elif & Else Statements

• Often, code should only should execute when a particular condition as been met
• Conditional flow of logic is controlled using the keywords: if, elif, and else
• if Statements allow the computer to perform actions based on a certain set of results/alternative actions
• Can be expressed verbally as: "Hey if this case happens, perform some action"
• elif and else statements allow expansion to tell the computer: "Hey if this case happens, perform some action. Else, if another case happens, perform some other action. Else, if none of the above cases happened, perform this action."
• Code example:

if x>y:
  print("X is greater than y:")
elif x<y:
  print(" X is less than y")
else:
  print("x equal y")

• A first example of how to use an If, elif and else statement demonstrates using inline logic using an if True statement:

if True:
  print('It was true!')

• Adding some else logic example:

x = False
if x:
  print('x was True!')
else:
  print('I will be printed in any case where x is not true')

Multiple Branches

• if, elif, and else can be used to take us far, can be a nested structure
• The if, elif, and else line up, showing what the if is related to, for elif and else statements
• The nested if statements are each checked until a True boolean causes the nested code below it to run
• It is possible to put in many elif statements before closing off with an else

For Loops

• Many objects in Python are iterable, meaning every element in the object can be iterated over
• For loops allows the program to execute a block of code for every iteration of said object
• Iterable means over every character in a string, every item in a list, and every key in a dictionary is accessible
• The syntax for a for loop is:

my_iterable = [1,2,3]
for item_name in my_iterable:
  print(item_name)

For Loops and Lists

• Iterating through a list can occur by implementing the following:

## Automate this sort of list, 
list1= [1,2,3,4,5,6,7,8,9,10]
for num in list1:
  print(num)

• When printing multiple iterations, the print command should be placed on the same line to display all results linearly
• Example:

list=[1,2,3,4,5,6,7,8,9]
for item in list:
  print(item,end=" ")

Asterisks for Unpacking into Function

• Asterisks unpack items into a function call

fruits = ['lemon', 'pear','watermelon', 'tomato']
print(fruits[0], fruits[1],fruits[2], fruits[3])
print(*fruits)

sep

• sep can be declared to specify parameters in the items that are unpacked

fruits = ['lemon', 'pear','watermelon', 'tomato']
print(*fruits,sep="**")

• In the result each word would be separated by two asterisks

Modulo operator

• Modulo gives the remainder in a division/uses %, returns the values inline with the original statement

For Loops / Lists

list=[1,2,3,4,5,6,7,8,9,10]
sum=0
for item in list:
  sum=sum +item
print(sum)

• Above example shows the sum of a list
• Important to note the effect of indentation here. Indentation inside an active for loop causes functions like print() to return a result on each iteration

For Loops

• end='' will return inline output if it's declared in iterative for loops

For Loops/Tuples

• Example of a for loop used with a tuple:

tup = (1,2,3,4,5)
for t in tup:
  print(t)

List of Tuples

• When iterating through a sequence that contains tuples, the item can be the tuple itself, serving as an example of tuple unpacking.

list = [(1,2), (3,4), (5,6), (7,8)]
for item in list:
  print (item)

Dictionary

• A for loop only produces the keys of a dictionary
• .keys() is a new dictionary method. Output = all keys in the dictionary
• .values() is a new dictionary method. Output = all values in the dictionary
• .items() is a new dictionary method. Output = all key/value pairs in dictionary
• Dictionaries are unordered
• Keys and values come back in arbitrary order
• A sorted list can be obtained using sorted()

Dictionary unpacking

d={'k1':1, 'k2':2, 'k3':3}
for k,v in d.items():
  print(k)
  print(v)

While Loops

• While loops will continue to execute a block of code while some condition remains True
• Example:

while some_boolean_condition:
  #do something
else:
  #do something different

• Another example:

x=0
while x < 10:
  print(x)
  x+=1
else:
  print('DONE')

Break, Continue and Pass

• break, continue, and pass, are statements added to loops to add additional functionality
• break: Breaks out of the current closest enclosing loop
• continue: Goes to the top of the closest enclosing loop
• pass: Does nothing at all
• Break and continue statements can appear anywhere inside the loop's body
• Often put them further nested in conjunction with an if statement to perform an action based on some condition
• Example:

x = 0
while x < 10:
  print('x is currently: ',x)
  x+=1
  if x==3:
    continue
    print('x==3')
    print('Continue')
    #continue
  elif x==8:
    print('Reach 8...')
    break

• The difference between Pass and Continue - "pass" statement

 s = "geeks"
 # Pass statement
  for i in s:
  if i == 'k':
  print('Pass executed')
  pass
  print(i)
  g
  e
  e
  Pass executed
  k

• The difference between Pass and Continue - "Continue" statement

s = "geeks"
## Continue statement
for i in s:
if i == 'k':
  print('Continue executed')
  continue
print(i)
g
e
e
Continue executed
s

Useful Operators

• "Operators" and built in functions that don't fit well into any category
• RANGE is a function allows the user to create a list of integers, requires that they be cast with the list() function to be properly implemented. You can include a start, stop, and steplength as range parameters

Enumerate

• Python Enumerate can be used in code when there is a frequent need to track how many loops have gone through
• List out the process without looping:

index_count = 0
for letter in 'abcde':
    print("At index {} the letter is {}".format(index_count, letter))
    index_count += 1

Enumerate - Tuple Unpacking

• For the code:

for i, letter in enumerate('abcde'):
    print("At index {} the letter is {}".format(i, letter))

• The output shows each letter and its place in the object

Zip

• Enumerate returns a list - format is enumerated using .list() - and meaning you can use tuple unpacking during our for loop
• The zip() function acts by quickly is used to create a list of tuples by "zipping" up together two lists

list1=[1,2,3,4,5]
list2=['A','B', 'C','D','E']
for a,b in zip(list1, list2):
  print(a)
  print(b)

The *in` Operator

• This operator is used to check to quickly check if an object is in a list

Combination Operators

• Example: combine in with not, to check if some object or variable is NOT present in a list

Min and Max operators

• Used to check the minimum or maximum of a list

Random Operators

• The Random function shuffle the list in place

from random import shuffle
mylist = [40, 10, 100, 30, 20]
shuffle(mylist)

• The Function "shuffle", shuffles the list in place - meaning it won't return

List Comprehensions

• List Comprehensions acts like a way of quickly is a unique way of creating lists with Python
• Can be used as a good alternative if the user is using a for loop along with .append() to create a list

Creating Lists with List Comprehension

1st = [x for x in 'word']

• Square numbers in a range and turn into a list

1st = [x**2 for x in range(0,11)]

• check for even numbers in a range

1st = [x for x in range(11) if x % 2 == 0]