python-csv-generation

name	python-csv-generation
description	Generate structured CSV files from Python data using the csv module for tabular data export.

Python CSV Generation

Overview

The Python csv module provides functionality to read and write CSV (Comma-Separated Values) files. CSV is a standard format for tabular data that's widely compatible with spreadsheet applications.

Installation

Built-in to Python, no installation needed.

Basic Usage

Writing CSV with DictWriter (Recommended)

import csv

# Data to write
data = [
    {'frame_id': '/root/keyframes_001.png', 'coins': 5, 'enemies': 2, 'turtles': 1},
    {'frame_id': '/root/keyframes_002.png', 'coins': 3, 'enemies': 1, 'turtles': 0},
    {'frame_id': '/root/keyframes_003.png', 'coins': 7, 'enemies': 3, 'turtles': 2},
]

# Write to CSV file
with open('output.csv', 'w', newline='') as csvfile:
    fieldnames = ['frame_id', 'coins', 'enemies', 'turtles']
    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)

    # Write header row
    writer.writeheader()

    # Write data rows
    writer.writerows(data)

Writing CSV with writer (Simple approach)

import csv

with open('output.csv', 'w', newline='') as csvfile:
    writer = csv.writer(csvfile)

    # Write header
    writer.writerow(['frame_id', 'coins', 'enemies', 'turtles'])

    # Write data rows
    writer.writerow(['/root/keyframes_001.png', 5, 2, 1])
    writer.writerow(['/root/keyframes_002.png', 3, 1, 0])

Complete Example: Frame Analysis Results

import csv
import os
from pathlib import Path

def write_counting_results(results, output_path):
    """
    Write object counting results to CSV.

    Args:
        results: List of dicts with keys:
                 'frame_id', 'coins', 'enemies', 'turtles'
        output_path: Path to output CSV file
    """
    fieldnames = ['frame_id', 'coins', 'enemies', 'turtles']

    with open(output_path, 'w', newline='') as csvfile:
        writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
        writer.writeheader()
        writer.writerows(results)

    print(f"Results written to {output_path}")

# Example usage
results = [
    {
        'frame_id': '/root/keyframes_001.png',
        'coins': 5,
        'enemies': 2,
        'turtles': 1
    },
    {
        'frame_id': '/root/keyframes_002.png',
        'coins': 3,
        'enemies': 1,
        'turtles': 0
    }
]

write_counting_results(results, '/root/counting_results.csv')

Tips

1. newline='': Always use newline='' when opening CSV files to handle line endings correctly
2. Fieldnames: Define fieldnames in the exact order you want them in the CSV
3. Data Consistency: Ensure all rows have the same keys/columns
4. Path Handling: Convert Path objects to strings if using pathlib
5. Reading CSV: Use csv.DictReader to read back CSV files as dictionaries

Reading CSV Files

import csv

with open('output.csv', 'r') as csvfile:
    reader = csv.DictReader(csvfile)
    for row in reader:
        print(row)  # Each row is a dictionary

Common Issues

• Extra blank rows: Use newline='' parameter
• Encoding errors: Specify encoding='utf-8' if needed
• Quote handling: Use quoting=csv.QUOTE_MINIMAL for automatic quoting