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Loads a CSV dataset from a specified filepath using pandas, with fallback to creating sample data if the file is not found.

Purpose

This function serves as a data loading utility that attempts to read a CSV file and provides informative feedback about the dataset's structure (shape and columns). It includes error handling to gracefully manage missing files by calling a fallback function 'create_sample_data()' to generate sample data instead of failing.

Source Code

def load_data(filepath='data.csv'):
    """Load the dataset"""
    try:
        df = pd.read_csv(filepath)
        print("Dataset loaded successfully!")
        print(f"Shape: {df.shape}")
        print(f"\nColumns: {df.columns.tolist()}")
        return df
    except FileNotFoundError:
        print("Error: data.csv not found. Creating sample dataset...")
        return create_sample_data()

Parameters

Parameter Details

filepath: String path to the CSV file to be loaded. Defaults to 'data.csv' in the current working directory. Can be an absolute or relative path. Expected to point to a valid CSV file readable by pandas.read_csv().

Return Value

Returns a pandas DataFrame object containing the loaded dataset. If the specified file exists, returns the DataFrame created from the CSV file. If the file is not found (FileNotFoundError), returns the result of create_sample_data() function (assumed to also return a DataFrame). The DataFrame structure depends on the CSV content or the sample data generation logic.

Dependencies

• pandas

Required Imports

import pandas as pd

Usage Example

import pandas as pd

# Assuming create_sample_data() is defined
def create_sample_data():
    return pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})

# Load data from default location
df = load_data()

# Load data from custom filepath
df = load_data(filepath='path/to/mydata.csv')

# Access the loaded data
print(df.head())

Best Practices

• Ensure the 'create_sample_data()' function is defined before calling load_data() to avoid NameError when file is not found
• Use absolute paths or ensure correct working directory when specifying custom filepaths
• Consider adding more specific exception handling for other pandas.read_csv() errors (e.g., parsing errors, encoding issues)
• The function prints to stdout which may not be ideal for production environments; consider using logging instead
• Validate the returned DataFrame structure matches expected schema before processing
• Consider adding parameters for pandas.read_csv() options (encoding, delimiter, etc.) for more flexibility

Tags

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