build/lib/AutoMxL/Preprocessing/Missing_Values.py
def fit_transform(self, df, l_var=None, verbose=False):
        """fit and transform dataset with encoder

        Parameters
        ----------
        df : DataFrame
            input dataset
        l_var : list
            features to encode.
            If None, all features identified as dates (see Features_Type module)
        verbose : boolean (Default False)
            Get logging information
        """
        df_local = df.copy()
        # fit
        self.fit(df_local, l_var=l_var, verbose=verbose)
        # transform
        df_local = self.transform(df_local, verbose=verbose)

        return df_local
fit and transform dataset with encoder

        Parameters
        ----------
        df : DataFrame
            input dataset
        l_var : list
            features to encode.
            If None, all features identified as dates (see Features_Type module)
        verbose : boolean (Default False)
            Get logging information
        
fit and transform dataset with encoder
Parameters

df : DataFrame
input dataset
l_var : list
features to encode.
If None, all features identified as dates
verbose : boolean (Default False)
Get logging information
fit and transform dataset with encoder Parameters df : DataFrame input dataset l_var : list features to encode . If None all features identified as dates verbose : boolean ( Default False ) Get logging information
def fit_transform(self, df, l_var=None, verbose=False):
        df_local = df.copy()
        self.fit(df_local, l_var=l_var, verbose=verbose)
        df_local = self.transform(df_local, verbose=verbose)
        return df_local
def fit_transform ( self , df , l_var = None , verbose = False ) : df_local = df . copy ( ) self . fit ( df_local , l_var = l_var , verbose = verbose ) df_local = self . transform ( df_local , verbose = verbose ) return df_local
fit and transform dataset with encoder
Parameters
fit and transform dataset with encoder Parameters
"""fit and transform dataset with encoder

        Parameters
        ----------
        df : DataFrame
            input dataset
        l_var : list
            features to encode.
            If None, all features identified as dates (see Features_Type module)
        verbose : boolean (Default False)
            Get logging information
        """ # fit # transform
self
df
l_var
verbose