code: def df_outliers(df,sensitivity = 1.5):
      
      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
docs: 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.