datamop.sweep_nulls
===================

.. py:module:: datamop.sweep_nulls


Functions
---------

.. autoapisummary::

   datamop.sweep_nulls.sweep_nulls


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

.. py:function:: sweep_nulls(data, strategy='mean', columns=None, fill_value=None)

   Handles missing values in a dataset using the specified strategy.

   :param data: The input dataset where missing values need to be handled.
   :type data: pandas.DataFrame
   :param strategy: The strategy to use for handling missing values. Supported options are:
                    - 'mean': For numeric columns only. Replace missing values with the mean of the respective column.
                    - 'median': For numeric columns only. Replace missing values with the median of the respective column.
                    - 'mode': Replace missing values with the mode (most frequent value) of the respective column.
                    - 'constant': Replace missing values with a specified constant value (requires `fill_value`).
                    - 'drop': Drop rows or columns containing missing values (depending on the `columns` parameter).
   :type strategy: {'mean', 'median', 'mode', 'constant', 'drop'}, optional, default='mean'
   :param columns: The specific columns to apply the missing value handling.
                   If None or an empty list, the strategy is applied to all columns.
   :type columns: list of str or None, optional, default=None
   :param fill_value: The constant value to use when `strategy='constant'`. Ignored for other strategies.
   :type fill_value: int, float, str, or None, optional, default=None

   :returns: A new DataFrame with missing values handled based on the specified strategy.
   :rtype: pandas.DataFrame

   :raises ValueError: - If the input data is not a pandas.DataFrame.
       - If the input strategy is not in 'mean', 'median', 'mode', 'constant', or 'drop'.
       - If `fill_value` is missing for the 'constant' strategy.
   :raises KeyError: If any specified column in `columns` does not exist in the pandas.DataFrame.
   :raises TypeError: If the input of `fill_value` is not a number or a string.

   .. rubric:: Examples

   a    b     c

   0  10.0  1.5     x
   1   NaN  2.5  None
   2  30.0  NaN     z

   >>> cleaned = sweep_nulls(data, strategy='mean')
   >>> print(cleaned)
           a    b     c
       0  10.0  1.5     x
       1  20.0  2.5  None
       2  30.0  2.0     z