Data Wrangler I/O Operations

This tutorial covers the I/O capabilities of data-wrangler, including loading and saving data from various sources and formats.

Overview

The datawrangler.io module provides seamless loading and saving of data from:

• Local files: CSV, JSON, text files, images, and more

• URLs: Load data directly from web sources

• Multiple formats: Automatic format detection based on file extensions

• Mixed sources: Handle lists of files/URLs with different formats

Let’s explore these capabilities with practical examples.

import datawrangler as dw
from datawrangler.io import load, save
import pandas as pd
import numpy as np
import os
from pathlib import Path

Loading Different File Formats

Data-wrangler automatically detects file formats and loads them appropriately. Let’s demonstrate with different file types:

# Create sample data files for demonstration
import tempfile

# Create a temporary directory for our examples
temp_dir = tempfile.mkdtemp()
print(f\"Working in temporary directory: {temp_dir}\"

# Create sample CSV file
csv_data = pd.DataFrame({
    'product': ['laptop', 'mouse', 'keyboard', 'monitor'],
    'price': [999.99, 25.50, 75.00, 300.00],
    'category': ['electronics', 'accessories', 'accessories', 'electronics']
})

csv_file = os.path.join(temp_dir, 'products.csv')
csv_data.to_csv(csv_file, index=False)

# Create sample text file
text_content = \"\"\"Data science is transforming industries worldwide.
Machine learning enables computers to learn from data.
Natural language processing helps computers understand human language.
Data visualization makes complex data insights accessible.\"\"\"

text_file = os.path.join(temp_dir, 'sample_text.txt')
with open(text_file, 'w') as f:
    f.write(text_content)

# Create sample JSON file
json_data = {
    'users': [
        {'name': 'Alice', 'age': 30, 'city': 'New York'},
        {'name': 'Bob', 'age': 25, 'city': 'San Francisco'},
        {'name': 'Charlie', 'age': 35, 'city': 'Chicago'}
    ]
}

json_file = os.path.join(temp_dir, 'users.json')
import json
with open(json_file, 'w') as f:
    json.dump(json_data, f)

print(f\"Created files:\"
print(f\"- CSV: {csv_file}\"
print(f\"- Text: {text_file}\"
print(f\"- JSON: {json_file}\")