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Utilities Module

This module contains utility functions that support various operations of the data analysis library, including data splitting, logging, and file operations.

Data Splitting (helpers.py)

Functions:

split_data(data, target_column)

  • Description: Splits the dataset into features (X) and target (y) based on the target column.
  • Parameters:
    • data: A pandas DataFrame.
    • target_column: A string, the name of the target variable column.
  • Returns: Two pandas DataFrames, the features (X) and the target (y).

train_test_split_data(X, y, test_size=0.2, random_state=42)

  • Description: Splits the dataset into training and test sets.
  • Parameters:
    • X: A pandas DataFrame, the feature variables.
    • y: A pandas Series or DataFrame, the target variable.
    • test_size: A float, the proportion of the dataset to include in the test split. Default is 0.2.
    • random_state: An int, random_state is the seed used by the random number generator. Default is 42.
  • Returns: Four pandas DataFrames/Series, X_train, X_test, y_train, y_test.

Logging (logger.py)

Functions:

configure_logging(level=logging.INFO)

  • Description: Configures the logging settings for the library.
  • Parameters:
    • level: The root logger level. Defaults to logging.INFO.
  • Returns: None.

log_message(message, level=logging.INFO)

  • Description: Logs a message at the specified log level.
  • Parameters:
    • message: A string, the log message.
    • level: The log level for this message. Defaults to logging.INFO.
  • Returns: None.

File Operations (file_operations.py)

Functions:

read_csv(file_path)

  • Description: Reads data from a CSV file.
  • Parameters:
    • file_path: A string, the path to the CSV file.
  • Returns: A pandas DataFrame.

write_csv(data, file_path)

  • Description: Writes data to a CSV file.
  • Parameters:
    • data: A pandas DataFrame.
    • file_path: A string, the path where to save the CSV file.
  • Returns: None.