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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Check Palindrome in Python (Ignore Case and Spaces)
Check whether a string is a palindrome while ignoring case, spaces, and all non-alphanumeric characters using Python's filter and string reversal.
def is_palindrome(text: str) -> bool:
cleaned = ''.join(char.lower() for char in text if char.isalnum())
return cleaned == cleaned[::-1]
if __name__ == "__main__":
test_cases = [
"A man, a plan, a canal: Panama",
"race a car",
"Was it a car or a cat I saw?",
"hello",
…How to Check if a String is Alphanumeric in Python
Uses the built-in str.isalnum() method to test whether a string contains only letters and numbers.
def is_alphanumeric(s: str) -> bool:
return s.isalnum()
if __name__ == "__main__":
test_cases = ["Hello123", "Hello World", "12345", "", "Hello@World", "Python3"]
for case in test_cases:
result = is_alphanumeric(case)
print(f"{case!r:15} -> {result}")How to Check if a String is Numeric in Python
This code provides a function to determine if a string represents a valid numeric value using Python's built-in float() conversion.
def is_numeric(s):
"""Check if a string represents a valid numeric value."""
try:
float(s)
return True
except (ValueError, TypeError):
return False
if __name__ == "__main__":
test_cases = ["123", "-45.67", "3.14e10", "0x1A", "abc", "12.5.6", " 42 ", ""]
for case in test_c…Extract Data by Type from a List in Python: Numbers and Strings
Loop through a mixed list to filter out numeric and string values into separate lists.
def extract_numbers(items):
"""Extract all numeric values from a mixed list."""
numbers = []
for item in items:
if isinstance(item, (int, float)) and not isinstance(item, bool):
numbers.append(item)
return numbers
def extract_strings(items):
"""Extract all string values from a…Find Local Minima (Valleys) in a Numeric List in Python
This code finds indices of all local minima (valleys) in a numeric list, including edge cases, using a simple loop that compares each element with its neighbors.
def find_local_minima(numbers):
"""Find indices of local minima (valleys) in a numeric list.
A value is a local minimum if it's less than or equal to its neighbors.
Edge elements are considered minima if they're less than or equal to their single neighbor.
"""
if not numbers:
return []…Find Maximum Value in a List of Numbers in Python
Iterate through a list with a for loop to manually find and return the maximum numeric value.
def find_max(numbers):
"""Return the maximum value in a list of numbers."""
if not numbers:
return None
max_value = numbers[0]
for num in numbers[1:]:
if num > max_value:
max_value = num
return max_value
if __name__ == "__main__":
sample_list = [3, 7, 2, 15, 9, 11]
…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 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 Find Local Maxima in a Python List
Return the indices of all local maxima in a numeric list, where a peak is an element greater than both its immediate neighbors.
def find_peaks(numbers):
"""
Return the indices of local maxima in a numeric list.
A local maximum is an element greater than both its neighbors.
"""
if len(numbers) < 3:
return []
peaks = []
for i in range(1, len(numbers) - 1):
if numbers[i] > numbers[i - 1] and number…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 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 Catch ValueError in Python (try except)
Handle invalid numeric input by catching ValueError in a try/except block and returning a friendly error message.
def parse_number(text):
try:
number = int(text)
return f"Parsed number: {number}"
except ValueError as error:
return f"Error: '{text}' is not a valid number ({error})"
if __name__ == "__main__":
examples = ["42", "hello", "3.14", "100"]
for item in examples:
print(pars…Detect Outliers in CSV Data Using Z-Score in Python
Read a CSV file and detect outliers in a numeric column by computing z-scores, flagging those exceeding a given threshold — no machine learning required.
import csv
import statistics
from math import sqrt
def detect_outliers(csv_path, column_name, threshold=2.0):
"""Detect outliers in a numeric column using z-score method."""
values = []
with open(csv_path, 'r', newline='') as f:
reader = csv.DictReader(f)
if column_name not in reader.field…How to Handle Missing Values in a CSV Numeric Column in Python
Clean missing entries in a CSV numeric column by filling them with the mean, median, a custom value, or dropping rows.
import csv
from pathlib import Path
import statistics
def clean_csv_numeric(input_path: str, output_path: str, column: str, strategy: str = "mean") -> None:
"""
Handles missing values in a numeric column of a CSV file.
Strategies: 'mean', 'median', 'drop', or 'fill' with a specified value.
"""
row…How to Convert Data Types in Python with a Helper Class
This code defines a beginner-friendly OOP helper class for common data conversions like string to list, list to dict, JSON string, and CSV row, with an advanced subclass for numeric casting.
class DataConverter:
"""A beginner-friendly helper class for common data conversions."""
def __init__(self, data):
self.data = data
def to_list(self):
"""Convert string data (comma-separated) to a list."""
if isinstance(self.data, str):
return [item.strip() for…How to Compute Cosine Similarity Between Two Vectors in Python
This code calculates the cosine similarity between two numeric vectors using the dot product and Euclidean norms, returning a value between -1 and 1.
import math
def cosine_similarity(vec_a, vec_b):
if len(vec_a) != len(vec_b):
raise ValueError("Vectors must have the same length")
dot_product = sum(a * b for a, b in zip(vec_a, vec_b))
norm_a = math.sqrt(sum(a * a for a in vec_a))
norm_b = math.sqrt(sum(b * b for b in vec_b))
i…How to Compute the Dot Product of Two Lists in Python
Compute the dot product of two equal-length numeric lists using a generator expression with zip and sum.
def dot_product(list1, list2):
"""
Compute the dot product of two numeric lists.
The lists must have the same length.
"""
if len(list1) != len(list2):
raise ValueError("Lists must have the same length")
return sum(a * b for a, b in zip(list1, list2))
if __name__ == "__main__":
…How to Use Comprehensions and Generators to Check Data in Python
A beginner-friendly helper that filters numeric values, computes squares and cubes with comprehensions and a generator, and returns a summary dictionary.
def check_data(iterable):
"""Return a summary of numeric data using comprehensions and a generator."""
values = [item for item in iterable if isinstance(item, (int, float))]
squares = [x ** 2 for x in values if x > 0]
cubes = (x ** 3 for x in values if x > 0)
cube_list = list(cubes)
return {
…How to Use List Comprehensions and Generators in Python
Analyze a list of numbers using a list comprehension to square evens, a generator for sum, and a generator expression for the maximum squared value.
def analyze_numbers(numbers):
squared = [n ** 2 for n in numbers if n % 2 == 0]
total = sum(n for n in numbers)
max_squared = max((n ** 2 for n in numbers), default=0)
return squared, total, max_squared
if __name__ == "__main__":
data = [1, 2, 3, 4, 5, 6]
evens_squared, total_sum, max_sq = an…Automatically Generate Charts from CSV Files with One Command
Read a CSV file with headers, extract the first two numeric columns, and save a matplotlib line chart as a PNG image.
import csv
import sys
from pathlib import Path
import matplotlib.pyplot as plt
def generate_chart(csv_path: str) -> None:
"""Read a CSV file with headers and plot the first two numeric columns."""
data = []
with open(csv_path, 'r', newline='') as f:
reader = csv.reader(f)
headers = next(re…Rename Files in Folder with Numeric Prefix in Python
Renames all files in a folder by adding a sequential numeric prefix (e.g., 01_, 02_) to each filename using pathlib.
from pathlib import Path
def rename_with_numeric_prefix(folder_path):
folder = Path(folder_path)
for index, file_path in enumerate(folder.iterdir(), start=1):
if file_path.is_file():
new_name = f"{index:02d}_{file_path.name}"
new_path = file_path.with_name(new_name)
…ETL in Python: Extract CSV, Transform Dict, Load JSON
Build a simple ETL pipeline in Python that reads a CSV file, transforms each row (stripping whitespace and converting numeric fields), and writes the result to JSON.
import csv
import json
from pathlib import Path
def extract_csv(file_path):
"""Read CSV file and return list of row dictionaries."""
with Path(file_path).open('r', newline='', encoding='utf-8') as f:
reader = csv.DictReader(f)
return list(reader)
def transform_dicts(rows):
"""Transform ro…How to Filter Data in Python
Filter a list of dictionaries by exact key-value matches or numerical ranges using concise list comprehensions.
from typing import List, Dict, Any
def filter_data(
data: List[Dict[str, Any]], key: str, value: Any
) -> List[Dict[str, Any]]:
"""Return records where data[key] equals value."""
return [record for record in data if record.get(key) == value]
def filter_by_range(
data: List[Dict[str, Any]], key: str…How to Process CSV Data in Python with a Data Helper
Build a beginner-friendly data helper in Python that loads a CSV file, filters rows by a condition, and summarizes numeric fields.
import csv
from pathlib import Path
DATA = [
{"name": "Alice", "score": 88, "passed": True},
{"name": "Bob", "score": 42, "passed": False},
{"name": "Carol", "score": 95, "passed": True},
]
def load_csv(file_path: Path) -> list[dict]:
with file_path.open(newline="", encoding="utf-8") as f:
r…Browse by section
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