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Python Continue Statement - GeeksforGeeks

Last Updated : 12 Jul, 2025

Python continue statement is a loop control statement that forces to execute the next iteration of the loop while skipping the rest of the code inside the loop for the current iteration only, i.e. when the continue statement is executed in the loop, the code inside the loop following the continue statement will be skipped for the current iteration and the next iteration of the loop will begin.

Example:

for i in range(1, 11):
    if i == 6:
        continue
    print(i, end=" ")

Explanation: When i == 6, the continue statement executes, skipping the print operation for 6.

while True:
...
if x == 10:
continue
print(x)

Parameters : The continue statement does not take any parameters.

Returns: It does not return any value but alters the flow of the loop execution by skipping the current iteration.

Example 1: Skipping specific characters in a string

for char in "GeeksforGeeks":
    if char == "e":
        continue
    print(char, end=" ")

Explanation: Whenever char == 'e', the continue statement executes, skipping the print function for that iteration.

Example 2. Using continue in nested loops

a = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

for row in a:
    for num in row:
        if num == 3:
            continue
        print(num, end=" ")

Explanation: continue statement skips printing 3 and moves to the next iteration, so all numbers except 3 are printed in a single line.

Example 3. Using continue with a while loop

i = 0
while i < 10:
    if i == 5:
        i += 1  # ensure the loop variable is incremented to avoid infinite loop
        continue
    print(i)
    i += 1

Explanation: When i == 5, the continue statement skips printing and jumps to the next iteration.

We should use the continue statement when we need to control the flow of loops efficiently by skipping specific iterations while still executing the rest of the loop. Here are some key scenarios:

• Skipping Specific Values: When certain values should be ignored while continuing with the remaining iterations.
• Filtering Data Dynamically: When applying conditional checks to exclude specific elements from processing.
• Optimizing Loop Performance: When unnecessary computations can be avoided to improve efficiency.

For more loop control statements, refer to:

• Python break Statement
• Python pass Statement

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