sample()

Generate synthetic data.

Syntax

def sample() -> pd.DataFrame

Parameters

None

Returns

• pd.DataFrame
  • The generated synthetic data
  • Same columns as original training data

Description

The sample() method is used to generate synthetic data from a trained model. This method must be called after training is completed with fit().

This method performs the following operations:

1. Checks if model is trained
2. Generates synthetic data rows (number determined by configuration)
3. Returns the generated synthetic data as a DataFrame

Example

from petsard import Synthesizer, Metadater
import pandas as pd

# Load and prepare data
df = pd.read_csv('data.csv')
metadata = Metadater.from_data(df)

# Initialize, create and train synthesizer
synthesizer = Synthesizer(method='default')
synthesizer.create(metadata=metadata)
synthesizer.fit(data=df)

# Generate synthetic data
synthetic_data = synthesizer.sample()
print(f"Generated {len(synthetic_data)} synthetic rows")

# Save to file if needed
synthetic_data.to_csv('synthetic_data.csv', index=False)

Notes

• Must complete fit() training before calling sample()
• The number of rows generated is determined during create() or fit() based on metadata or training data
• Large data generation may require significant time and memory
• Some synthesizers may have generation quantity limits
• To specify the number of rows to generate, set sample_num_rows parameter when initializing the Synthesizer