Lists & loops
Iterate, transform, and combine sequences with readable loop patterns.
Generate Data Helper for Beginners in Python
Define two functions that create a random list of integers and then compute basic summary statistics like count, total, average, maximum, and minimum using simple loops.
from random import randint
def build_dataset(size: int, max_val: int) -> list[int]:
data = []
for _ in range(size):
data.append(randint(1, max_val))
return data
def summarize(data: list[int]) -> dict[str, float]:
total = 0
maximum = data[0]
minimum = data[0]
for value in data:
…
How to Build a Running Maximum List in Python
Compute a list where each element is the maximum of all numbers seen so far from an input list.
def running_maximum(numbers):
result = []
current_max = float('-inf')
for num in numbers:
if num > current_max:
current_max = num
result.append(current_max)
return result
if __name__ == "__main__":
numbers = [3, 1, 4, 1, 5, 9, 2, 6]
max_list = running_maximum(number…
How to Calculate the Average of a List of Numbers in Python
Compute the arithmetic mean of a numeric list using Python's built-in sum() and len() functions, returning 0.0 for an empty list.
def calculate_average(numbers):
if not numbers:
return 0.0
return sum(numbers) / len(numbers)
if __name__ == "__main__":
sample_numbers = [10, 20, 30, 40, 50]
result = calculate_average(sample_numbers)
print(f"Average: {result}")
How to Compute Percentile Value from Sorted List in Python
Compute any percentile value from a sorted list using linear interpolation between ranks.
def percentile(sorted_data, percentile_value):
"""Return the value below which `percentile_value`% of data falls."""
if not sorted_data:
raise ValueError("Cannot compute percentile of empty list")
if not 0 <= percentile_value <= 100:
raise ValueError("Percentile must be between 0 and 100")
…
How to Compute Sliding Window Sum of Size k in Python
Compute the sum of every contiguous subarray of a fixed size k using an efficient O(n) sliding window technique.
def sliding_window_sum(nums, k):
"""Return a list of sums for each contiguous subarray of size k."""
if not nums or k <= 0 or k > len(nums):
return []
result = []
window_sum = sum(nums[:k])
result.append(window_sum)
for i in range(k, len(nums)):
window_sum += nums[i] -…
How to Compute a Moving Average in Python
This code computes the moving average over a numeric list using an efficient sliding window sum, avoiding recomputation of each window.
def moving_average(data, window_size):
"""
Compute the moving average over a numeric list.
Args:
data: List of numeric values
window_size: Size of the sliding window (positive integer)
Returns:
List of moving averages, each representing the mean of a window
"""
…
How to Filter Even Numbers and Square Them in Python
Create two beginner-friendly helper functions that filter even numbers and compute squares of a number list using loops, then print the results along with the sum and average.
def get_even_numbers(numbers):
evens = []
for num in numbers:
if num % 2 == 0:
evens.append(num)
return evens
def get_squares(numbers):
squares = []
for num in numbers:
squares.append(num ** 2)
return squares
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
even_numbers …
How to Find the Median of a List in Python
Compute the median of an unsorted numeric list using the statistics module in Python.
import statistics
def median_of_list(numbers):
return statistics.median(numbers)
if __name__ == "__main__":
sample = [7, 3, 1, 4, 9, 2, 8]
print(median_of_list(sample))
How to Flatten One Level of a Nested List in Python
Flattens exactly one level of a nested list by extending the output with each inner list and appending non-list items.
def flatten_one_level(nested_list):
"""Flatten one level of a nested list."""
flattened = []
for item in nested_list:
if isinstance(item, list):
flattened.extend(item)
else:
flattened.append(item)
return flattened
if __name__ == "__main__":
# Example with mi…
How to Parse a Comma String into a List of Integers in Python
Converts a comma-separated string into a list of integers, handling spaces and empty inputs.
def parse_csv_to_ints(text: str) -> list[int]:
"""Parse a comma-separated string into a list of integers."""
if not text.strip():
return []
return [int(part.strip()) for part in text.split(",") if part.strip()]
if __name__ == "__main__":
sample = "10, 20, 30, 40, 50"
result = parse_csv_to_…
How to Standardize a List with Z-Score Normalization in Python
This code computes the z-score for each number in a list, standardizing the data to have zero mean and unit variance using the statistics module.
import statistics
def z_score_normalize(values):
"""Standardize a list of numbers using z-score normalization."""
if not values or len(values) < 2:
raise ValueError("Need at least 2 values for meaningful z-score normalization")
mean = statistics.mean(values)
std_dev = statistics.stdev(val…
How to Summarize a List of Numbers in Python
Loop over a list of numbers to compute total, count, average, min, and max, then return them in a dictionary.
def summarize_numbers(numbers):
"""Return a dict with basic stats for a list of numbers."""
total = 0
count = 0
smallest = numbers[0]
largest = numbers[0]
for num in numbers:
total += num
count += 1
if num < smallest:
smallest = num
if num > largest:…
How to summarize and transform lists in Python
Compute count, sum, min, max, and average for a list and multiply each element by a factor using simple loops and built-in functions.
def summarize(data):
"""Return a summary of a list: count, sum, min, max, average."""
count = len(data)
total = sum(data)
minimum = min(data)
maximum = max(data)
average = total / count if count else 0
return count, total, minimum, maximum, average
def multiply_elements(data, factor=2):
…
How to unzip a list of pairs into two lists in Python
Split a list of (a, b) tuples into two separate lists by iterating with a for loop and appending each element to its own output list.
def unzip(pairs):
"""Split a list of (a, b) pairs into two separate lists."""
if not pairs:
return [], []
firsts = []
seconds = []
for a, b in pairs:
firsts.append(a)
seconds.append(b)
return firsts, seconds
if __name__ == "__main__":
pairs = [(1, 'a'), (…
Pairwise Adjacent Differences in a Python List
Computes the absolute differences between each pair of adjacent elements in a list using a concise list comprehension.
def adjacent_differences(nums):
"""Return list of absolute differences between adjacent elements."""
return [abs(nums[i] - nums[i + 1]) for i in range(len(nums) - 1)]
if __name__ == "__main__":
sample = [3, 7, 2, 9, 5]
diffs = adjacent_differences(sample)
print("Original list:", sample)
print…
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