feature-engineering-and-data-transformations/using-toy-exmaples/feature_cleaning/missing_data.py
def drop_missing(data,axis=0):
    """
    Listwise deletion:
    excluding all cases (listwise) that have missing values

    Parameters
    ----------
    axis: drop cases(0)/columns(1),default 0

    Returns
    -------
    Pandas dataframe with missing cases/columns dropped
    """    
    
    data_copy = data.copy(deep=True)
    data_copy = data_copy.dropna(axis=axis,inplace=False)
    return data_copy

    Listwise deletion:
    excluding all cases (listwise) that have missing values

    Parameters
    ----------
    axis: drop cases(0)/columns(1),default 0

    Returns
    -------
    Pandas dataframe with missing cases/columns dropped
    
Listwise deletion:
excluding all cases (listwise) that have missing values

Parameters



Returns

Pandas dataframe with missing cases/columns dropped
Listwise deletion : excluding all cases ( listwise ) that have missing values Parameters Returns Pandas dataframe with missing cases / columns dropped
def drop_missing(data,axis=0):
    data_copy = data.copy(deep=True)
    data_copy = data_copy.dropna(axis=axis,inplace=False)
    return data_copy
def drop_missing ( data , axis = 0 ) : data_copy = data . copy ( deep = True ) data_copy = data_copy . dropna ( axis = axis , inplace = False ) return data_copy
Listwise deletion:
excluding all cases (listwise) that have missing values
Listwise deletion : excluding all cases ( listwise ) that have missing values
"""
    Listwise deletion:
    excluding all cases (listwise) that have missing values

    Parameters
    ----------
    axis: drop cases(0)/columns(1),default 0

    Returns
    -------
    Pandas dataframe with missing cases/columns dropped
    """
data
axis