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How to Sum a CSV Column by Group in Python
This code reads a CSV string and sums a specified column for each unique value of a group key using the csv module and defaultdict.
import csv
from collections import defaultdict
from io import StringIO
def aggregate_csv(csv_data, group_key, sum_column):
totals = defaultdict(float)
reader = csv.DictReader(StringIO(csv_data))
for row in reader:
key = row[group_key]
totals[key] += float(row[sum_column])
return dict(t…Parse CSV with Custom Delimiter and Quote Character in Python
Reads a CSV string with a custom delimiter and quote character using the csv module, returning a list of rows.
import csv
from io import StringIO
def parse_csv(data, delimiter='|', quotechar='"'):
reader = csv.reader(StringIO(data), delimiter=delimiter, quotechar=quotechar)
rows = [row for row in reader]
return rows
if __name__ == "__main__":
sample = 'Alice|"Smith, Jr."|25\nBob|"Johnson, Sr."|30'
result …Parse Fixed Width Data File by Column Slices in Python
Extract fields from fixed-width text by slicing each line at defined column offsets, with a dictionary describing the boundaries.
from pathlib import Path
def parse_fixed_width(data: str, slices: dict[str, tuple[int, int]]) -> list[dict[str, str]]:
lines = data.strip().splitlines()
records = []
for line in lines:
record = {}
for name, (start, end) in slices.items():
record[name] = line[start:end].strip()…Read Entire File into String with read Method in Python
Open a file, read its entire content into a string using the .read() method, and clean up with a context manager.
from pathlib import Path
def read_file_to_string(file_path: str) -> str:
"""Read the entire file content into a string using the read method."""
with open(file_path, 'r', encoding='utf-8') as file:
content = file.read()
return content
if __name__ == "__main__":
# Create a temporary file for d…Count word frequency in Python with dict and Counter
Count how often each word appears in a string using Counter, converted to a plain dict, and print results alphabetically.
from collections import Counter
import re
def count_word_frequency(text):
words = re.findall(r'\b\w+\b', text.lower())
return dict(Counter(words))
if __name__ == "__main__":
sample_text = "The quick brown fox jumps over the lazy dog. The dog barks, and the fox runs."
frequency = count_word_frequency(…How to Count Word Frequencies in Python
Count how often each word appears in a string and list the unique words using Python dictionaries and sets.
def text_processor(text):
words = text.lower().split()
word_count = {}
for word in words:
word_count[word] = word_count.get(word, 0) + 1
unique_words = set(words)
return word_count, unique_words
if __name__ == "__main__":
sample_text = "The quick brown fox jumps over the lazy dog and t…How to Count Word Frequencies in Python with Counter and Sets
This code processes a text string by lowercasing, splitting into words, counting frequencies with Counter, and extracting unique and sorted word lists using sets.
from collections import Counter
def process_text(text):
words = text.lower().split()
word_counts = Counter(words)
unique_words = set(words)
sorted_words = sorted(unique_words)
return {
"total_words": len(words),
"unique_words": len(unique_words),
"word_frequencies": di…How to Normalize Data in Python with Dictionaries and Sets
Normalize a list of dicts by keeping selected keys, stripping/lowercasing strings, and extracting unique sorted values using set comprehension.
def normalize_data(data, keys):
"""
Normalize a list of dictionaries by keeping only specified keys
and converting values to proper types.
"""
normalized = []
for item in data:
clean_item = {}
for key in keys:
value = item.get(key)
if isinstance(value, st…How to Parse Data Into Dictionaries and Sets in Python
Parses raw student strings into a dictionary of lists and finds unique courses using a set.
from collections import defaultdict
def parse_students(raw_data):
"""Parse raw student strings into a dictionary of lists."""
parsed = defaultdict(list)
for entry in raw_data:
name, _, course = entry.partition(":")
parsed[course.strip()].append(name.strip())
return dict(parsed)
def fi…How to Parse Query String to Dict with Duplicate Keys in Python
Convert a URL query string into a Python dictionary, merging duplicate keys into lists while keeping single values as scalars.
from urllib.parse import parse_qs
def parse_query_to_dict(query_string):
parsed = parse_qs(query_string, keep_blank_values=True)
return {key: values if len(values) > 1 else values[0] for key, values in parsed.items()}
if __name__ == "__main__":
query = "name=John&name=Jane&age=30&city=&city=Paris&empty…How to Serialize a Dictionary to a Query String in Python
Convert a Python dictionary into a URL-encoded query string using the standard library's urllib.parse.urlencode function.
import urllib.parse
def dict_to_query_string(params):
"""Serialize a dictionary to a URL query string."""
return urllib.parse.urlencode(params)
if __name__ == "__main__":
data = {
"name": "Alice Johnson",
"age": 30,
"city": "New York",
"interests": ["coding", "hiking"]
…How to convert string values to int or float in Python dicts
Recursively convert string values in nested dicts and lists to ints or floats when possible, leaving other strings untouched.
def coerce_str_values(data):
"""Recursively convert string values that look like ints or floats."""
if isinstance(data, dict):
return {key: coerce_str_values(val) for key, val in data.items()}
elif isinstance(data, list):
return [coerce_str_values(item) for item in data]
elif isinstance…Parse Env Vars into Typed Dict in Python
Convert a list of environment variable names into a dictionary with automatically detected types (bool, int, float, or string), defaulting missing vars to None.
import os
from typing import Any, Dict
def parse_env_vars(env_names: list[str], env: Dict[str, str] | None = None) -> Dict[str, Any]:
"""Parse a list of environment variable names into a typed dict.
Each variable is parsed as:
- bool: "true"/"false" (case-insensitive)
- int: if it can be converted t…Filtering data with a Python class helper
A beginner-friendly DataFilter class that filters lists of dictionaries by exact match, greater-than, and substring conditions.
class DataFilter:
"""A beginner-friendly helper to filter lists of dictionaries."""
def __init__(self, data):
self.data = data
def filter_by(self, key, value):
"""Return items where data[key] == value."""
return [item for item in self.data if item.get(key) == value]
…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 Create a Data Formatter Class in Python
A beginner-friendly helper class to format lists, dictionaries, and stored records into readable strings.
class DataFormatter:
"""Helper class for beginners to format common data types."""
def __init__(self, name="data"):
self.name = name
self.records = []
def add_record(self, key, value):
"""Add a key-value record to the formatter."""
self.records.append({"key": key, …How to Define a Simple Class with __init__ and __repr__ in Python
Defines a Person class with __init__ to store name and age, and __repr__ to give a readable string representation.
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def __repr__(self):
return f"Person(name='{self.name}', age={self.age})"
if __name__ == "__main__":
p1 = Person("Alice", 30)
p2 = Person("Bob", 25)
print(p1)
print(p2)How to Implement a Stack Class in Python
A complete Stack class implemented with a Python list, featuring push, pop, peek, is_empty, size, and a readable string representation.
class Stack:
def __init__(self):
self._items = []
def push(self, item):
"""Add an item to the top of the stack."""
self._items.append(item)
def pop(self):
"""Remove and return the top item. Raises IndexError if empty."""
if self.is_empty():
raise IndexE…How to Sort Data in Python with a Class Helper
This beginner-friendly class wraps the built-in sorted() function to sort numbers, strings ignoring case, and dictionaries by a specified key.
class DataSorter:
def __init__(self, data):
self.data = data
def sort_numbers(self, reverse=False):
return sorted(self.data, reverse=reverse)
def sort_strings_ignore_case(self, reverse=False):
return sorted(self.data, key=str.lower, reverse=reverse)
def sort_dicts_by_key(self…How to Use StrEnum with auto() in Python
Define string-valued enum members automatically by using StrEnum with the auto() helper, making each member's value its own uppercase name.
from enum import StrEnum, auto
class Color(StrEnum):
RED = auto()
GREEN = auto()
BLUE = auto()
class Language(StrEnum):
PYTHON = auto()
JAVASCRIPT = auto()
RUST = auto()
print(list(Color))
print(list(Language))
print(Color.RED == "RED")
print(Language.PYTHON == "PYTHON")
print(f"Color: {Co…How to Validate Data Types in Python with a Class
A beginner-friendly Python class that checks if a value is a string, integer, float, list, or empty, using simple methods and isinstance checks.
class DataValidator:
"""A simple data validation helper for beginners."""
def __init__(self, data):
self.data = data
def is_string(self):
return isinstance(self.data, str)
def is_integer(self):
return isinstance(self.data, int) and not isinstance(self.data, bool)
…Python Factory Method: Create Shapes by Type String
A factory method that maps a type string to a concrete shape class and returns an instance, with runtime error handling.
class Shape:
def draw(self):
raise NotImplementedError
class Circle(Shape):
def draw(self):
return "Drawing a circle"
class Square(Shape):
def draw(self):
return "Drawing a square"
class Triangle(Shape):
def draw(self):
return "Drawing a triangle"
class ShapeFact…How to Map Strings to Uppercase in Python
Loops through a list of strings and builds a new list with each string converted to uppercase.
strings = ["hello", "world", "python", "skillset"]
uppercased = []
for s in strings:
uppercased.append(s.upper())
print(uppercased)How to compress consecutive numbers into range strings in Python
Convert a sorted list of consecutive integers into compact range strings like '1-3', '5-6', and '15'.
def compress_ranges(nums):
"""Convert a list of sorted consecutive numbers into range strings."""
if not nums:
return []
ranges = []
start = prev = nums[0]
for num in nums[1:]:
if num == prev + 1:
prev = num
else:
if start == prev:
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