5 Best Ways to Write a Python Program to Print Elements in a Series Within a Specific Range

Rate this post
5 Best Ways to Write a Python Program to Print Elements in a Series Within a Range

πŸ’‘ Problem Formulation: Given a sequence of numbers and a specific range, the task is to write a Python program that prints all elements falling within that range. For example, given the series [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] and a range of 4 to 8, the desired output would be elements 4, 5, 6, 7, and 8.

Method 1: Using a For Loop

This method involves iterating over each element in the series with a for loop and checking if it falls within the specified range. If it does, the element is printed. This method is very basic and easy to understand, making it ideal for beginners.

Here’s an example:

series = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
start, end = 4, 8

for number in series:
    if start <= number <= end:
        print(number)

Output:

4
5
6
7
8

This code snippet declares a series and a range. The for loop iterates through each number in the series. If a number falls within the start and end bounds, it gets printed to the console.

Method 2: Using List Comprehension

List comprehensions offer a more concise way to create lists. In this method, a new list is created that contains only the elements that fall within the specified range. The list is then printed. It is compact and idiomatic to Python.

Here’s an example:

series = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
start, end = 4, 8

filtered_series = [number for number in series if start <= number <= end]
print(filtered_series)

Output:

[4, 5, 6, 7, 8]

This code snippet uses list comprehension to filter out elements that are within the range from start to end. The resulting list, filtered_series, is then printed out, displaying the elements within the range.

Method 3: Using the filter() Function

Python’s built-in filter() function can be used to apply a filter on a series. The method takes a function and a sequence, returning an iterator that contains only items for which the function returns True. It’s considered more functional and Pythonic.

Here’s an example:

series = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
start, end = 4, 8

def in_range(number):
    return start <= number <= end

print(list(filter(in_range, series)))

Output:

[4, 5, 6, 7, 8]

The example uses the filter() function in conjunction with a user-defined function, in_range(), which verifies whether a number falls in the specified range. It filters the series correspondingly.

Method 4: Using itertools

Python’s itertools module has tools that allow for memory-efficient and fast iteration. Here, itertools.islice() can be used to slice the iterator returned by the range function, thus printing out the desired range of numbers.

Here’s an example:

import itertools

series = range(1, 11)
start, end = 4, 8

for number in itertools.islice(series, start - 1, end):
    print(number)

Output:

4
5
6
7
8

This code uses itertools.islice() to iterate over a subset of the series, specifically the elements within the start and end range. The off-by-one in the start index accounts for zero indexing in Python ranges.

Bonus One-Liner Method 5: Using Generator Expression

A generator expression is similar to a list comprehension, but it does not create the list in memory. Instead, it generates the elements on the fly. It is more memory-efficient, especially for large series.

Here’s an example:

series = range(1, 11)
start, end = 4, 8

print(*(number for number in series if start <= number <= end))

Output:

4 5 6 7 8

The example above uses a generator expression within the print() function to generate each number within the range on-demand and print them out in sequence.

Summary/Discussion

  • Method 1: For Loop. Easy to understand. Verbose. Not the most efficient if the series is large.
  • Method 2: List Comprehension. Pythonic and concise. Creates an intermediate list, which uses memory.
  • Method 3: Filter Function. Functional approach. Clean syntax. May be less intuitive for those not used to functional programming.
  • Method 4: Itertools. Efficient and Pythonic. However, understanding itertools can be complex for beginners.
  • Method 5: Generator Expression. Memory-efficient. Ideal for very large series. May be less readable to those unfamiliar with generator syntax.