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Python Code Samples

Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.

3 matches
Data pipelines & processing medium

How to Find Missing Values in Large Datasets in Python

Analyze missing values across multiple large pandas DataFrames with counts and percentages.

pandas missing-data data-cleaning
Python
import pandas as pd
import numpy as np

def find_missing_values_summary(datasets):
    """Analyze missing values across multiple datasets (dict of name: DataFrame)."""
    summary = {}
    for name, df in datasets.items():
        missing_count = df.isnull().sum()
        total_rows = len(df)
        missing_pct = (mi…
41 0 Open
Modern tooling easy

How to Validate Data with a Simple Dict-Based Rules Helper in Python

Validates a dictionary against a set of callable rules, printing pass/fail per field and returning an overall boolean.

validation dictionary helper
Python
import json
from pathlib import Path
from typing import Any, Callable


def validate_data(
    data: dict[str, Any],
    rules: dict[str, Callable[[Any], bool]],
    path: Path | None = None,
) -> bool:
    """Validate a dict against a set of simple rules."""
    all_valid = True
    for field, validator in rules.item…
15 0 Open
Database scaling & optimization easy

How to Validate Data Before Scaling in Python

A reusable Python helper that validates required fields and constraint checks on data rows before entering a database pipeline, improving data quality and throughput.

validation data-quality scaling
Python
def validate_data(data, required_fields, constraints=None):
    """
    Basic validation helper demonstrating data-quality workflows
    before scaling (catches bad rows early, improves throughput).
    """
    constraints = constraints or {}

    errors = []
    for field in required_fields:
        if field not in d…
15 0 Open

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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.