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How to Convert CSV Column Types While Reading in Python
Read a CSV file and automatically convert column values to int, float, str, or bool based on type suffixes in the header names.
import csv
from pathlib import Path
from typing import Any
def read_csv_with_types(filepath: str) -> list[dict[str, Any]]:
"""Read CSV and convert column types based on header suffixes."""
converters = {
"int": int,
"float": float,
"str": str,
"bool": lambda v: v.strip().lower(…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…Check Invertible Mapping for Duplicate Values in Python
Detect duplicate values among (key, value) pairs to ensure the mapping is invertible, using a dictionary for O(1) lookups.
def invertible_after_dedup(pairs):
"""
Check whether a set of (key, value) pairs is invertible,
i.e., no duplicate values exist for different keys.
"""
seen = {}
for key, value in pairs:
if value in seen and seen[value] != key:
return False, f"Duplicate value '{value}' for k…How to Count Elements and Find Duplicates in a Python List
Count occurrences of each element in a list, extract unique values, and identify duplicates using Python dictionaries and sets.
def analyze_counts(data):
"""Count elements, return unique values, and find duplicates."""
# Count occurrences using a dictionary
counts = {}
for item in data:
counts[item] = counts.get(item, 0) + 1
# Alternative compact approach with set
unique_items = set(data)
# Fi…How to Filter a Dictionary by Predicate on Values in Python
This code defines a reusable function that builds a new dictionary containing only the items whose values satisfy a given predicate function.
def filter_dict_by_predicate(d, predicate):
"""Return a new dict with only items whose value passes the predicate."""
return {k: v for k, v in d.items() if predicate(v)}
if __name__ == "__main__":
scores = {"Alice": 85, "Bob": 42, "Charlie": 91, "Diana": 60}
# Keep only values greater than or equal t…How to Find Keys with Matching Values in Two Dictionaries in Python
Find dictionary keys where both dictionaries have the exact same value by iterating over key-value pairs and comparing them.
def find_matching_values(dict1, dict2):
"""Return list of keys that have the same value in both dicts."""
matches = []
for key, value in dict1.items():
if key in dict2 and dict2[key] == value:
matches.append(key)
return matches
if __name__ == "__main__":
# Example usage
di…How to Invert a Dictionary in Python Safely
Swap dictionary keys and values while detecting duplicate values to prevent silent data loss.
def invert_dict_safely(d):
inverted = {}
for key, value in d.items():
if value not in inverted:
inverted[value] = key
else:
raise ValueError(f"Duplicate value '{value}' would cause data loss")
return inverted
if __name__ == "__main__":
sample = {"a": 1, "b": 2,…How to Map Dictionary Values with a Transformation Function in Python
Create a reusable function that applies a transformation to every value in a dictionary and returns a new dict.
def transform_dict_values(d, func):
"""Apply a transformation function to every value in a dictionary."""
return {key: func(value) for key, value in d.items()}
if __name__ == "__main__":
original = {"a": 1, "b": 2, "c": 3}
doubled = transform_dict_values(original, lambda x: x * 2)
print(doubled)
…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 Normalize Data with Dictionaries and Sets in Python
Normalize dictionary entries to a fixed set of keys and extract unique values using sets in Python.
def normalize_entry(entry: dict, valid_keys: set) -> dict:
result = {}
for key in valid_keys:
result[key] = entry.get(key, "")
return result
def unique_values(entries: list[dict], key: str) -> set:
return {entry.get(key) for entry in entries if entry.get(key) is not None}
if __name__ == "__…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 Sort a Python Dictionary by Value Descending
Sort dictionary items by their values in descending order and return a new dictionary.
def sort_dict_by_value_desc(d):
return dict(sorted(d.items(), key=lambda item: item[1], reverse=True))
if __name__ == "__main__":
sample = {"apple": 5, "banana": 2, "cherry": 8, "date": 8}
result = sort_dict_by_value_desc(sample)
print(result)How to Use defaultdict(set) in Python to Group Unique Values
Group key-value pairs into a dictionary of sets, automatically creating a new set for each key using defaultdict.
from collections import defaultdict
def track_groups(pairs):
groups = defaultdict(set)
for key, value in pairs:
groups[key].add(value)
return groups
if __name__ == "__main__":
data = [
("fruit", "apple"),
("fruit", "banana"),
("fruit", "apple"),
("veg", "carrot…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…How to swap dict keys and values in Python when values are unique
Swap dict keys and values using a dict comprehension, with a guard that raises an error when values repeat.
def swap_dict_keys_values(d):
"""Swap keys and values in a dict, assuming values are unique."""
if len(set(d.values())) != len(d.values()):
raise ValueError("Values must be unique to swap keys and values")
return {v: k for k, v in d.items()}
if __name__ == "__main__":
original = {"a": 1, "b": …Add property getter setter validation in Python
Shows how to use @property with a setter to validate values before assigning them in a Python class.
class Temperature:
def __init__(self, celsius=0):
self._celsius = celsius # Use underscore to avoid recursion
@property
def celsius(self):
"""Getter returns the stored value."""
return self._celsius
@celsius.setter
def celsius(self, value):
"""Setter valid…Define an Enum for Status Codes in Python
Create a readable StatusCode enum with HTTP-style status values and iterate over its members using the standard library Enum class.
from enum import Enum
class StatusCode(Enum):
OK = 200
CREATED = 201
BAD_REQUEST = 400
UNAUTHORIZED = 401
NOT_FOUND = 404
INTERNAL_ERROR = 500
if __name__ == "__main__":
code = StatusCode.NOT_FOUND
print(f"Name: {code.name}")
print(f"Value: {code.value}")
print(f"Is it OK? {co…How to Define Dataclass Field Defaults in Python
Implement a Python dataclass with default values for simple fields and default factories for mutable collections.
from dataclasses import dataclass, field
from typing import List
@dataclass
class Product:
name: str
price: float = 0.0
quantity: int = 0
tags: List[str] = field(default_factory=list)
metadata: dict = field(default_factory=dict)
if __name__ == "__main__":
p1 = Product("Laptop", 999.99, 5)
…Validate dataclass fields with __post_init__ in Python
Add custom validation to a Python dataclass inside __post_init__, raising ValueError or TypeError for invalid field values.
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class Product:
name: str
price: float
quantity: int = 1
category: Optional[str] = None
def __post_init__(self):
if not self.name or not isinstance(self.name, str):
raise ValueError("name must be a…Filter List to Keep Only Whitelist Values in Python
Filter a list of values to keep only those present in a predefined whitelist set using a list comprehension.
def filter_whitelist(values, whitelist):
"""Return only values that are present in the whitelist set."""
return [value for value in values if value in whitelist]
if __name__ == "__main__":
raw_values = ["apple", "banana", "cherry", "date", "apple", "elderberry"]
allowed = {"apple", "banana", "date"}
…Generate Pascal's Triangle Rows in Python
Builds Pascal's triangle as a list of rows, where each inner value is the sum of the two values above it.
def generate_pascals_triangle(rows):
triangle = []
for row_num in range(rows):
row = [1] * (row_num + 1)
for col in range(1, row_num):
row[col] = triangle[row_num - 1][col - 1] + triangle[row_num - 1][col]
triangle.append(row)
return triangle
if __name__ == "__main__":
…How to Add Two Lists Elementwise in Python
Add two equal-length lists element by element using a list comprehension with zip, returning a new list of summed values.
def elementwise_add(list1, list2):
return [a + b for a, b in zip(list1, list2)]
if __name__ == "__main__":
list_a = [1, 2, 3, 4]
list_b = [10, 20, 30, 40]
result = elementwise_add(list_a, list_b)
print(result)How to Compare Two Lists Elementwise for Greater Flags in Python
Compare two equal-length lists element by element and return a list of booleans marking where list_a values are greater than list_b values.
def compare_lists_greater(list_a, list_b):
"""
Compare two lists elementwise and return a list of booleans
indicating whether each element in list_a is greater than the
corresponding element in list_b.
"""
if len(list_a) != len(list_b):
raise ValueError("Lists must have the same length"…How to Flatten List of Dict Values in Python
This code flattens the values of a list of dictionaries into a single list, handling both list values and scalar values.
def flatten_dict_values(dicts):
flattened = []
for d in dicts:
for value in d.values():
if isinstance(value, list):
flattened.extend(value)
else:
flattened.append(value)
return flattened
if __name__ == "__main__":
data = [
{"a": …Browse by section
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