Finds outliers in the dataframe.
    Parameters:
    df - DataFrame
        The DataFrame to analyze.
    sensitivity - number, default 1.5
        The value to multipy by the iter-quartile range when determining outliers. This number is used
        for categorical data as well.

def df_outliers(df,sensitivity = 1.5):
    """ Finds outliers in the dataframe.
    Parameters:
    df - DataFrame
        The DataFrame to analyze.
    sensitivity - number, default 1.5
        The value to multipy by the iter-quartile range when determining outliers. This number is used
        for categorical data as well.
    """
    outlier_df = df.copy()
    dtypes = _basics.col_dtypes(df)
    for col_name in df.columns:
        outlier_df.loc[~outliers(df[col_name],'bool',dtypes[col_name],sensitivity),col_name] = np.nan
    outlier_df = outlier_df.dropna(how = 'all')
    return outlier_df