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How to Normalize a List of Numbers in Python
This Python function normalizes a list of numeric values to the range [0, 1] using min-max scaling, returning a new list and leaving the original unchanged.
def normalize(data):
"""
Normalize a list of numeric values to the range [0, 1].
Returns a new list, leaving the original unchanged.
"""
if not data:
return []
min_val = min(data)
max_val = max(data)
# Handle the edge case where all values are identical
if min_val …How to Normalize a List of Numbers to the 0-1 Range in Python
Scale a list of numbers so the minimum becomes 0 and the maximum becomes 1 using min-max normalization.
def min_max_normalize(values):
"""Normalize a list of numbers to the [0, 1] range."""
if not values:
return []
min_val = min(values)
max_val = max(values)
if min_val == max_val:
return [0.0] * len(values)
return [(x - min_val) / (max_val - min_val) for x in values]
if __name__…How to Validate CLI Integer Option Within a Range in Python
Use argparse with integer type and bounds checking to validate a command-line option falls within a specified min-max range.
import argparse
def main():
parser = argparse.ArgumentParser(description="Validate an integer within a range.")
parser.add_argument("--value", type=int, required=True, help="Integer to validate")
parser.add_argument("--min", type=int, default=0, help="Minimum allowed value")
parser.add_argument("--max…Normalize Data in Python with Comprehensions and Generators
Clean a list by dropping None values with a comprehension, then min-max normalize it using a lazy generator expression — a beginner-friendly data preparation pattern.
import statistics
# Sample raw data including missing and outlier-ish values
raw = [22, 18, None, 25, 30, 19, 22, 17, None, 28, 24]
# Clean the data: drop None values using a list comprehension
clean = [x for x in raw if x is not None]
# Normalize using min-max scaling with a generator expression
min_val = min(clea…Browse by section
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Copy-ready Python snippets for learners and developers
PythonSkillset code samples are short, focused examples organised by topic and difficulty. Every snippet is server-rendered HTML — readable by search engines and easy to copy. Open any sample, read the notes, copy the code, then press Try in editor to run it in the browser with Pyodide.
How to use this library
- Pick a topic section — strings, lists, files, functions, and more
- Open a sample, read How it works, and copy the code block
- Run it in the IDE, tweak values, then take a related quiz or tutorial lesson
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.