#Creating df that creates the datetime range

range_max = rtbinds['pricedate'].max()
range_min = range_max - datetime.timedelta(days=7)

sliced_df = rtbinds[(rtbinds['pricedate'] >= range_min) & (rtbinds['pricedate'] <= range_max)]

#grouping by 'shadow'

sliced_df.groupby(['pricedate','cons_name']).aggregate(np.mean).sort_values('shadow').head(10)

#returns for the first week of data.
pricedate   cons_name       shadow
2019-04-26  TEMP71_24753    -643.691
2019-04-27  TMP175_24736    -508.062
2019-04-25  TMP109_22593    -383.263
2019-04-23  TEMP48_24759    -376.967
2019-04-29  TEMP71_24753    -356.476