uftap.blogg.se

I tried the following: grandtotal = np.round(np.sum(report),1)Īnd that just creates a terrible mess. This provides a total for each 'SUPER_TYPE' group, but I cannot create a grand total. Report = df.groupby().apply(lambda sub_df: sub_df.pivot_table(index=, values=,aggfunc=np.sum, margins=True,margins_name= 'TOTAL')) TableArray = arcpy.da.TableToNumPyArray(table,, where_clause = whereClause) Table = "\\\\filserver\\MAP_PROJECTS\\LV_WEB\\SDE_CONNECTIONS\\LV_NEXUS.sde\\LV_\\LV_HARVEST_OPS" In my code below I can successfully create the subtotaled pivot table I'm looking for but cannot produce a grand total.