code: def scatterplot(self, cycle_data):
          
  
          columns = list(cycle_data.columns)
          columns.remove('cycle_time')
          columns.remove('completed_timestamp')
          columns = ['completed_timestamp', 'cycle_time'] + columns
  
          data = (
              cycle_data[columns]
              .dropna(subset=['cycle_time', 'completed_timestamp'])
              .rename(columns={'completed_timestamp': 'completed_date'})
          )
  
          data['cycle_time'] = data['cycle_time'].astype('timedelta64[D]')
          data['completed_date'] = data['completed_date'].map(pd.Timestamp.date)
  
          return data
docs: Return scatterplot data for the cycle times in `cycle_data`. Returns
          a data frame containing only those items in `cycle_data` where values
          are set for `completed_timestamp` and `cycle_time`, and with those two
          columns as the first two, both normalised to whole days, and with
          `completed_timestamp` renamed to `completed_date`.