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 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 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 Find the Mode in a Python List
Find the most frequent value (mode) in a Python list using the collections.Counter class, handling empty lists and ties.
from collections import Counter
def find_mode(numbers):
if not numbers:
return None
counts = Counter(numbers)
max_count = max(counts.values())
modes = [num for num, count in counts.items() if count == max_count]
return modes[0] if len(modes) == 1 else modes
if __name__ == "__main__":
…
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 check list items by type and emptiness in Python
Loop through a list with enumerate(), classify each item as empty, number, or text, and print a formatted status for each element.
def check_data(data):
"""Check each item in a list and print whether it's valid."""
for i, item in enumerate(data):
if item is None or item == "":
status = "empty"
elif isinstance(item, (int, float)):
status = "number"
else:
status = "text"
pr…
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):
…
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Lists & loops — Python code examples
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