MinMaxScaler

A custom implementation of a MinMaxScaler class for scaling numerical data in a pandas DataFrame. The class scales the features to a specified range, typically between 0 and 1.

Features

• fit: Calculate the minimum and maximum values of the data.
• transform: Scale the data to the specified feature range.
• fit_transform: Fit the scaler and transform the data in one step.
• get_params: Retrieve the minimum and maximum values calculated during fitting.

Methods

1. __init__(self, feature_range=(0, 1))
   • Initializes the MinMaxScaling class.
   • Parameters:
     • feature_range (tuple): Desired range of transformed data. Default is (0, 1).
2. fit(self, data)
   • Calculates the minimum and maximum values of the data.
   • Parameters:
     • data (pandas.DataFrame): The data to fit.
3. transform(self, data)
   • Transforms the data to the specified feature range.
   • Parameters:
     • data (pandas.DataFrame): The data to transform.
   • Returns:
     • pandas.DataFrame: The scaled data.
4. fit_transform(self, data)
   • Fits the scaler to the data and transforms the data in one step.
   • Parameters:
     • data (pandas.DataFrame): The data to fit and transform.
   • Returns:
     • pandas.DataFrame: The scaled data.
5. get_params(self)
   • Retrieves the minimum and maximum values calculated during fitting.
   • Returns:
     • dict: Dictionary containing the minimum and maximum values.

Error Handling

• Raises a TypeError if the input data is not a pandas DataFrame in the fit method.
• Raises an error if transform is called before fit or fit_transform.
• Raises an error in get_params if called before fit.

Use Case

Output

Installation

No special installation is required. Just ensure you have pandas installed in your Python environment.