[Python] Relational Operators with Examples Explained

As you embark on your programming journey in Python, you'll encounter an array of operators. In this article, we'll delve deep into relational operators. These operators play a pivotal role in comparing relationships between variables or values and are predominantly employed in conditional statements. Let's explore how these operators function, illustrated with examples.

== Operator

The '==' operator discerns "equivalence". At its core, it evaluates whether the contents of two values are identical. For instance, it is employed to determine if the two strings "apple" and "apple" match. However, its sensitivity to data types is noteworthy; the number 5 and the string "5" are deemed distinct by the '==' operator.

# Declare two variables and assign them the same value (10).
a = 10
b = 10

# Check if both variables hold the same value.
result = a == b

# Display the result. It should print True.
print(result)  # Output: True

!= Operator

The '!=' operator signifies "inequality". It assesses whether two values differ. For instance, to check if the numbers 10 and 20 vary, one would use the '!=' operator. Like its counterpart '==', it also exhibits sensitivity to data types.

# Declare two variables with distinct values.
x = "apple"
y = "orange"

# Check if the two strings are different.
is_different = x != y

# Display the result. It should print True.
print(is_different)  # Output: True

> Operator

The '>' operator designates "greater than". It returns True if the value on the left exceeds that on the right. For example, it can be used to verify if the number 15 is greater than 10. Nevertheless, be cautious when applied to strings or other data types as its behavior might slightly differ.

# Declare two numeric variables.
m = 15
n = 10

# Determine if m is greater than n.
is_greater = m > n

# Display the result. It should print True.
print(is_greater)  # Output: True

< Operator

The '<' operator represents "less than". It returns True if the value on the left is smaller than the one on the right. For instance, it's utilized to ascertain whether the number 5 is less than 10. This operator, too, necessitates attention when used with strings or other data types.

# Declare two numeric variables.
i = 5
j = 8

# Determine if i is smaller than j.
is_smaller = i < j

# Display the result. It should print True.
print(is_smaller)  # Output: True

>= Operator

The '>=' operator determines "greater than or equal to". It returns True if the value on the left is either greater than or equivalent to the one on the right. For example, it can be applied to assess if the number 15 is equal to 15, or if 16 is greater than 15.

# Declare two numeric variables.
p = 20
q = 20

# Ascertain if p is greater than or equivalent to q.
is_equal_or_greater = p >= q

# Display the result. It should print True.
print(is_equal_or_greater)  # Output: True

<= Operator

The '<=' operator signifies "less than or equal to". It returns True if the value on the left is either smaller than or matches the one on the right. For instance, to determine if the number 5 equals 5, or if 4 is less than 5, this operator is employed.

# Declare two numeric variables.
s = 4
t = 5

# Check if s is either smaller than or matches t.
is_equal_or_smaller = s <= t

# Display the result. It should print True.
print(is_equal_or_smaller)  # Output: True

In Python, relational operators are indispensable for evaluating and analyzing relationships between variables or values. They streamline the implementation of conditional programming and validate data.

However, while employing relational operators, several considerations merit attention:

1. Data Types: Being dynamically typed, Python might yield different outcomes for identical values, contingent on their data type. For example, the number 5 and the string "5" are discerned as distinct.
2. Floating-point Numbers: Owing to approximations, floating-point numbers can sometimes generate unexpected outcomes during comparisons. To circumvent this, it's prudent to allow a slight margin of error.
3. Complex Object Comparison: When comparing user-defined objects or intricate data structures, it's imperative to be conversant with the object's underlying comparison mechanism.

By adhering to these guidelines, relational operators can augment your prowess in data analysis and condition assessment in programming.