datamop.column_encoder
======================

.. py:module:: datamop.column_encoder


Functions
---------

.. autoapisummary::

   datamop.column_encoder.column_encoder


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

.. py:function:: column_encoder(data, columns, method='one-hot', order=None)

   Encodes categorical columns using one-hot or ordinal encoding based on user input.

   Parameters:
   -----------
   data : pandas.DataFrame
       The input DataFrame containing the dataset.
   columns : list
       The name of the columns to be encoded.
   method : str, optional, default='one-hot'
       The encoding method to use. Accepts either 'one-hot' for one-hot encoding
       or 'ordinal' for ordinal encoding.
   order : dict, optional, default=None
       A dictionary specifying the custom order for ordinal encoding.
       The keys should be column names, and the values should be lists
       defining the order of categories for each column.

   Returns:
   --------
   pd.DataFrame
       A new DataFrame with the specified column encoded. The original column
       will be dropped.

   Raises:
   -------
   TypeError:
       If input types are incorrect (e.g., non-DataFrame input, columns not a list of strings,
       method not a string, or order not a dictionary).
   ValueError:
       If required parameters are missing or invalid values are provided.
   KeyError:
       If specified columns are not found in the input DataFrame.
   UserWarning:
       If a column contains only one unique value or if there are missing values.

   Examples:
   ---------
   >>> import pandas as pd
   >>> data = pd.DataFrame({
   ...     'Sport': ['Tennis', 'Basketball', 'Football', 'Badminton'],
   ...     'Level': ['A', 'B', 'C', 'D']
   ... })

   >>> encoded_df_onehot = column_encoder(data, columns=['Sport'], method='one-hot')
   >>> print(encoded_df_onehot)
     Level  Sport_Badminton  Sport_Basketball  Sport_Football  Sport_Tennis
        A                0                 0               0             1
        B                0                 1               0             0
        C                0                 0               1             0
        D                1                 0               0             0

   >>> encoded_df_ordinal = column_encoder(data, columns=['Level'], method='ordinal', order={'Level': ['A', 'B', 'C', 'D']})
   >>> print(encoded_df_ordinal)
           Sport  Level
          Tennis      0
       Basketball     1
        Football      2
       Badminton      3