Python Pandas Data Analysis

# Create virtual environment
python -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

pandas
data-analysis
numpy
pytest>=7.0

from dataclasses import dataclass, field
from typing import List, Optional
from datetime import datetime


@dataclass
class DataProcessor:
    """Core processor for Python Pandas Data Analysis."""
    name: str
    created_at: datetime = field(default_factory=datetime.now)
    _items: List[dict] = field(default_factory=list, repr=False)

    def load(self, source: str) -> "DataProcessor":
        """Load data from source."""
        print(f"Loading data from {source}...")
        # Implementation depends on source type
        return self

    def transform(self, func) -> "DataProcessor":
        """Apply transformation function to all items."""
        self._items = [func(item) for item in self._items]
        return self

    def filter(self, predicate) -> "DataProcessor":
        """Filter items based on predicate."""
        self._items = [item for item in self._items if predicate(item)]
        return self

    def export(self, destination: str, format: str = "json") -> None:
        """Export processed data to destination."""
        import json
        with open(destination, "w") as f:
            json.dump(self._items, f, indent=2, default=str)
        print(f"Exported {len(self._items)} items to {destination}")

    @property
    def count(self) -> int:
        return len(self._items)

def main():
    processor = DataProcessor(name="Python Pandas Data Analysis")

    processor \
        .load("data/input.csv") \
        .transform(lambda x: {**x, "processed": True}) \
        .filter(lambda x: x.get("status") == "active") \
        .export("output/results.json")

    print(f"Processed {processor.count} records")


if __name__ == "__main__":
    main()

import pytest
from processor import DataProcessor


class TestDataProcessor:
    def test_create_processor(self):
        dp = DataProcessor(name="test")
        assert dp.name == "test"
        assert dp.count == 0

    def test_transform_chain(self):
        dp = DataProcessor(name="test")
        dp._items = [{"value": 1}, {"value": 2}]
        dp.transform(lambda x: {**x, "doubled": x["value"] * 2})
        assert dp._items[0]["doubled"] == 2
        assert dp._items[1]["doubled"] == 4