datamop.column_scaler
=====================

.. py:module:: datamop.column_scaler


Functions
---------

.. autoapisummary::

   datamop.column_scaler.column_scaler


Module Contents
---------------

.. py:function:: column_scaler(data, column, method='minmax', new_min=0, new_max=1, inplace=True)

   Scales the values of a specified column in a DataFrame.

   :param data: The DataFrame containing the column of interest for scaling.
   :type data: pandas.DataFrame
   :param column: The name of the numeric column to scale.
   :type column: str
   :param method:
                  The method used for scaling. Options include:
                      - `minmax`: Scales values between `new_min` and `new_max`, used as default method.
                      - `standard`: Scales values with mean of 0 and standard deviation of 1.
   :type method: str
   :param new_min: The lower boundary value for min-max scaling. Default value is 0.
   :type new_min: float
   :param new_max: The upper boundary value for min-max scaling. Default value is 1.
   :type new_max: float
   :param inplace: If `True` the original column is replaced with new scaled values.
                   If `False` the original column is retained and the new scaled column is
                   added to the dataframe with title `<column-name>-scaled`.
                   Default is True.
   :type inplace: bool

   :returns: A copy of the DataFrame with the scaled column
             replacing the original column if `inplace` is set to `True`.
             If `inplace` is set to `False`,
             the copy of DataFrame is returned with the new scaled column added,
             keeping the original column.
   :rtype: pandas.DataFrame

   :raises TypeError: If the input `data` is not a pandas DataFrame.
   :raises KeyError:: If the column passed for scaling does not exist in the DataFrame.
   :raises ValueError:: If the column passed for scaling is not numeric.
       If the `method` is not `minmax` or `standard`.
       If the `new_min` value is greater or equal to the `new_max` when using `minmax` method.

   .. rubric:: Examples

   >>> import pandas as pd
   >>> df = pd.DataFrame({"price": [25, 50, 75]})
   >>> df_scaled = column_scaler(df, column = 'price', method='minmax', new_min=0, new_max=1)
   >>> print(df_scaled)
           price
           0.0
           0.5
           1.0